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Tag: Science & Technology

  • AI Could Lead to Mass Joblessness Within the Next 5 Years | Entrepreneur

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    A computer science professor is warning that advanced AI could be developed within the next couple of years, leading to mass unemployment by 2030.

    On a recent episode of “The Diary of a CEO” podcast, University of Louisville Computer Science Professor Roman Yampolskiy warned that AI could cause “99%” of all workers to be unemployed by 2030. Yampolskiy said that artificial general intelligence systems (AGI) that are as capable as humans would likely be developed by 2027, leading to a labor market collapse three years later. He predicted that AI would provide “trillions of dollars” of “free labor,” giving employers a better option for their employment needs.

    “You have free labor, physical and cognitive, trillions of dollars of it,” Yampolskiy said. “It makes no sense to hire humans for most jobs if I can just get a $20 subscription or a free model to do what an employee does.”

    Related: Microsoft AI CEO Warns That ‘Dangerous’ and ‘Seemingly Conscious’ AI Models Could Arrive in the Next 2 Years: ‘Deserves Our Immediate Attention’

    Yampolskiy predicted that any job on a computer would immediately be automated once AGI arrives and that humanoid robots would take over physical labor jobs within the next five years, leading to unprecedented levels of unemployment.

    “So we’re looking at a world where we have levels of unemployment we’ve never seen before,” Yampolskiy said on the podcast. “Not talking about 10% unemployment, which is scary, but 99%.”

    The only jobs left will be those that humans prefer another human to do for them, Yampolskiy said. AI will “very quickly” gain the capacity to take over other human occupations, including teachers, analysts, and accountants, he predicted.

    Yampolskiy claims to have coined the term “AI safety” in a 2011 article and has since published more than 100 papers on AI’s dangers. He has written multiple books, including his 2025 book “Considerations on the AI Endgame: Ethics, Risks and Computational Frameworks.”

    Related: The ‘Godfather of AI’ Says Artificial Intelligence Needs Programming With ‘Maternal Instincts’ or Humans Could End Up Being ‘Controlled’

    In the podcast interview, Yampolskiy said that even coding and prompt engineering weren’t safe from automation. AI can design prompts for AI “way better” than any human, he stated.

    Retraining is also impossible in this new reality because AI will automate all jobs and “there is no plan B,” Yampolskiy said.

    Yampolskiy’s predictions match the forecasts made by other AI experts. Geoffrey Hinton, known as the “Godfather of AI” due to his pioneering work in the subject, stated in June that AI is going to “replace everybody” in white collar jobs. He challenged the idea that AI would create new jobs, pointing out that if AI automates tasks, there would be no jobs for people to do.

    Meanwhile, in May, Anthropic CEO Dario Amodei stated that AI would eliminate half of all entry-level, white-collar jobs within the next one to five years, causing unemployment to reach a high of 20%.

    Related: ‘When I Get Paid, You Get Paid’: Software Engineers Looking for Work Are Promising $10,000 or More to Anyone Who Can Help Them Land a Job

    A computer science professor is warning that advanced AI could be developed within the next couple of years, leading to mass unemployment by 2030.

    On a recent episode of “The Diary of a CEO” podcast, University of Louisville Computer Science Professor Roman Yampolskiy warned that AI could cause “99%” of all workers to be unemployed by 2030. Yampolskiy said that artificial general intelligence systems (AGI) that are as capable as humans would likely be developed by 2027, leading to a labor market collapse three years later. He predicted that AI would provide “trillions of dollars” of “free labor,” giving employers a better option for their employment needs.

    “You have free labor, physical and cognitive, trillions of dollars of it,” Yampolskiy said. “It makes no sense to hire humans for most jobs if I can just get a $20 subscription or a free model to do what an employee does.”

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    Sherin Shibu

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  • Adding AI Skills to Your Resume Can Boost Your Salary: Study | Entrepreneur

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    It pays to have AI skills — nearly $20,000 more per year on average.

    A recent study conducted by the job insight website LightCast analyzed over a billion job postings and found that employers are not only looking for workers with AI skills — they are also paying them more.

    “Job postings are increasingly emphasizing AI skills, and there are signals that employers are willing to pay premium salaries for them,” LightCast’s Head of Global Research Elena Magrini told CNBC.

    Related: Google Reportedly Told Its Staff to Use AI More or Risk Falling Behind: ‘It Seems Like a No-Brainer’

    The study found that job postings that asked for AI skills paid 28% more, or around $18,000, than jobs that didn’t require AI. Jobs requiring two or more AI skills paid 43% more.

    The roles with the highest differences in pay between workers with AI skills and those without were in the fields of customer support, sales, and manufacturing.

    There are now over 300 possible AI skills, according to LightCast, from generative AI to AI ethics to autonomous driving and robotics. But the most common AI skills employers requested were two of the most mainstream — ChatGPT or Microsoft Copilot.

    In a surprising twist, non-technical sectors demanded AI skills more than technical ones, according to LightCast’s report. Since November 2022, when ChatGPT launched, demand for generative AI skills shot up by 800% for non-technical roles.

    Related: These 3 Professions Are Most Likely to Vanish in the Next 20 Years Due to AI, According to a New Report

    A recent report from The Wall Street Journal found that entry-level college graduates are getting six- or seven-figure salaries right out of school because of their proficiency with AI. Databricks, a data analytics firm, is planning to hire triple the number of recent graduates this year compared to last year because of these young workers’ ability to use AI, the company told The Journal.

    While learning AI may give workers a boost in salary negotiations, the technology also has the potential to replace entry-level employees. A Stanford University study released last week found that AI-impacted jobs, like software developers, customer service representatives, and accountants, saw employment for workers ages 22 to 25 decline by 13% over the past three years.

    “There’s definitely evidence that AI is beginning to have a big effect,” the study’s first author and Stanford Professor Erik Brynjolfsson told Axios about the report.

    It pays to have AI skills — nearly $20,000 more per year on average.

    A recent study conducted by the job insight website LightCast analyzed over a billion job postings and found that employers are not only looking for workers with AI skills — they are also paying them more.

    “Job postings are increasingly emphasizing AI skills, and there are signals that employers are willing to pay premium salaries for them,” LightCast’s Head of Global Research Elena Magrini told CNBC.

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    Sherin Shibu

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  • Anthropic Is One of the Most Valuable Startups Ever | Entrepreneur

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    Anthropic, the AI startup behind the chatbot Claude, finalized a deal on Tuesday for a new, $13 billion Series F funding round that catapults its valuation from $61.5 billion to $183 billion, making it one of the most valuable startups ever.

    Anthropic has more than 300,000 business customers and has seen a sevenfold increase in its number of large clients with projects above $100,000 in the past year, the company said in a statement.

    “We are seeing exponential growth in demand across our entire customer base,” Anthropic CFO Krishna Rao said.

    Related: ‘We Don’t Negotiate’: Why Anthropic CEO Is Refusing to Match Meta’s Massive 9-Figure Pay Offers

    The funding round, which was led by investment firm Iconiq Capital, with Fidelity Management and Lightspeed Venture Partners, was one of the largest financing rounds so far for an AI startup, Bloomberg notes.

    Anthropic was initially planning to raise $5 billion, but raised the target to $10 billion following strong demand. The end $13 billion figure arose from more investors wanting to get a stake in the popular startup.

    In the statement, Anthropic noted that its run-rate revenue makes it “one of the fastest-growing technology companies in history,” skyrocketing from $1 billion at the start of the year to more than $5 billion in August. (Run-rate revenue refers to a company’s future annual revenue based on a shorter period of current performance.)

    Anthropic CEO and co-founder Dario Amodei. Photo by Chesnot/Getty Images

    Anthropic joins startups like SpaceX (valued at $350 billion in December) and TikTok’s parent company, ByteDance (valued at $300 billion in November), in the high valuation club.

    While Anthropic may be raising ample funds, its main competitor is further ahead. OpenAI, the creator of ChatGPT, announced in March that it had raised $40 billion in the biggest tech funding round for a private company, elevating its valuation to $300 billion.

    Anthropic was founded four years ago by former OpenAI staff and has since differentiated itself from its competitors with an emphasis on AI safety. It launched its chatbot Claude in March 2023 and Claude Code, an AI coding tool that enables users to generate, edit, and debug code, in February.

    Related: The CEO of $61 Billion Anthropic Says AI Will Take Over a Crucial Part of Software Engineers’ Jobs Within a Year

    Creating functional AI is a costly endeavor, requiring startups like Anthropic to raise as much funding as possible. In July 2024, Anthropic CEO Dario Amodei told Norges Bank CEO Nicolai Tangen in an “In Good Company” podcast episode that training an AI model costs around $100 million, but there are models today that cost “more like a billion.”

    “I think there is a good chance that by [2027] we’ll be able to get models that are better than most humans at most things,” Amodei said in the podcast.

    Anthropic, the AI startup behind the chatbot Claude, finalized a deal on Tuesday for a new, $13 billion Series F funding round that catapults its valuation from $61.5 billion to $183 billion, making it one of the most valuable startups ever.

    Anthropic has more than 300,000 business customers and has seen a sevenfold increase in its number of large clients with projects above $100,000 in the past year, the company said in a statement.

    “We are seeing exponential growth in demand across our entire customer base,” Anthropic CFO Krishna Rao said.

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    Sherin Shibu

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  • How AI Is Turning Hugh School Students Into Entrepreneurs | Entrepreneur

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    Opinions expressed by Entrepreneur contributors are their own.

    This is the third installment in the “1,000 Days of AI” series. I’ve had a front-row seat to K-12 education’s transformation — working with school systems worldwide as an AI education consultant to develop school district AI strategies and watching something remarkable unfold. The change didn’t come from curriculum committees or federal mandates, but from students who, as always, refused to wait for permission.

    While educators debated whether ChatGPT constituted cheating, 17-year-old high schooler Zach Yadegari built an AI app generating $1.12 million in monthly revenue. He began coding at age seven, initially creating a gaming website to bypass his elementary school’s firewalls. By 16, he’d already sold his first company for $100,000.

    Related: How AI Is Transforming Education Forever — and What It Means for the Next Generation of Thinkers

    The stark reality: AI has already changed everything

    Within 1,000 days, ChatGPT has fundamentally challenged traditional K-12 education. According to ACT research, 70% of high school students used AI tools in 2023-24, up from 58% the previous year. Pew Research confirms ChatGPT usage for schoolwork doubled from 2023 to 2024. But these statistics miss the real story: Students aren’t just using AI to complete assignments — they’re using it to build businesses, forcing schools to rapidly develop AI policies that balance innovation with responsible AI use in education.

    The traditional model assumed knowledge was scarce and teachers were gatekeepers. AI shattered both assumptions overnight. Every student now has access to infinite tutoring, instant expertise and tools that turn ideas into products in hours, not years. The question isn’t whether students should learn entrepreneurship — they already are.

    From high school hallways to revenue streams

    The most successful young entrepreneurs started as intrapreneurs within the school system itself. High school students across the country are transforming their AI skills into real businesses. Students nationwide are selling AI-generated study guides to classmates for $50-$500 monthly.

    The irony isn’t lost on me: What adults call cheating, these students call market research. What teachers label shortcuts, investors recognize as minimum viable products. In my work helping districts with developing AI policy for schools, I’ve seen how these entrepreneurial students actually exemplify AI education best practices — they’re solving real problems with real tools.

    The intrapreneurs inside our schools

    Not all innovation happens outside school walls. Student intrapreneurs are creating AI tutoring programs for struggling peers, building attendance apps for their schools and developing mental health chatbots for counselors. They see school problems as product opportunities, transforming education while living it.

    Teachers are becoming intrapreneurs, too. Forward-thinking educators use AI to create personalized learning paths, automate grading to spend more time with students and build tools that spread district-wide. These educator-intrapreneurs bridge institutional requirements and student innovation, creating space for experimentation within existing structures while contributing to AI curriculum development for K-12.

    Related: Why We Shouldn’t Fear AI in Education (and How to Use It Effectively)

    The federal framework meets grassroots reality

    In April 2025, President Trump signed “Advancing Artificial Intelligence Education for American Youth,” establishing the White House Task Force on AI Education. The executive order creates the Presidential AI Challenge to “encourage and highlight student and educator achievements in AI” across multiple age categories. This isn’t just another science fair — it’s federal recognition that K-12 students are already AI practitioners, validating the school district AI strategies that forward-thinking administrators have been developing.

    Crucially, the Presidential AI Challenge calls for students to “use AI to address community challenges,” validating what student entrepreneurs have been doing all along. The framework emphasizes that AI education must “spark curiosity and creativity,” but students aren’t preparing to participate — they’re already leading. This federal backing provides the cover innovative schools need to transform detention into incubation and homework into hackathons, establishing new AI education best practices along the way.

    3 practical steps for schools right now

    1. Implement “innovation hours” aligned with the Presidential AI Challenge:

    Dedicate weekly time for students to work on AI projects addressing real community problems. Let students form ventures, not just groups. Let them pursue customers, not just grades. Schools implementing this now will have students ready when the Presidential AI Challenge launches. This approach to AI curriculum development for K-12 turns theory into practice.

    2. Transform detention into incubation:

    Every student “caught” using AI creatively should be redirected, not punished. Create an “AI Innovation Council” where rule-benders become rule-makers. Have them develop your school’s AI policy and teach AI literacy to younger students. The White House Task Force calls for student-educator collaboration — make your “problem students” your problem solvers. This is responsible AI use in education at its best.

    3. Create intrapreneurship pathways:

    Establish formal recognition for students improving school operations through AI. Give course credit for building tools the school actually uses. Partner with local businesses for real-world projects. Every pizza shop and dental office needs AI help. Your students can provide it while earning money and credits. These pathways should be central to any school district AI strategy.

    The next 1,000 days: Bigger challenges, bigger opportunities

    The first 1,000 days proved that students could use AI. The next 1,000 days will prove they can lead with it. As AI becomes more powerful, the gap between students with access and support versus those without will widen exponentially. A student with ChatGPT, supportive teachers and entrepreneurial parents will build companies. A student with restricted access and punitive policies will fall behind — not by years, but by generations.

    The mental health implications are staggering. When 14-year-olds can build million-dollar businesses, what happens to those who can’t? When AI can do homework in seconds, how do we measure learning? These aren’t distant philosophical questions; they’re immediate challenges requiring thoughtful approaches to developing AI policy for schools.

    The next 1,000 days will see AI-native students enter the workforce. I can’t wait to see how they reshape entire industries. The concept of “entry-level” will dissolve when teenagers arrive with more AI experience than senior executives.

    Related: What The UAE’s AI Education Revolution Could Mean for the Future of Classroom Activities: Insights from a Young Entrepreneur

    The entrepreneurial imperative

    Schools that thrive won’t be those with the best AI policies or detection tools. They’ll be those cultivating intrapreneurs — students and teachers who transform systems from within. Every student who builds a tool to help classmates is an intrapreneur. Every teacher experimenting with AI to improve outcomes is an intrapreneur. Every administrator creating space for innovation enables intrapreneurship.

    After 1,000 days of ChatGPT in K-12 education, one truth emerges: Students who embraced AI as a tool for creation rather than completion are building the future economy. They’re intrapreneurs transforming schools from within and entrepreneurs building alternatives from without.

    The next 1,000 days will be exponentially more complex. AI will become more powerful, accessible and essential. Students who start building now will have compounded advantages. For educators, parents and policymakers seeking guidance from an AI keynote speaker for education or looking to establish AI education best practices, the path forward is clear: Embrace intrapreneurship, enable entrepreneurship, and expect transformation. The federal government has provided the framework through the Presidential AI Challenge. Now it’s time for local action.

    The kids aren’t just alright — they’re already ahead. The question for the next 1,000 days isn’t whether students will use AI to transform education and the economy. They will. The question is whether we’ll help them build something better or watch them build around us.

    Coming next in the “1,000 Days of AI” series: Legal’s AI transformation — where precedent meets algorithms, and why your next lawyer might be an AI that passed the bar exam on its first try.

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    Alex Goryachev

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  • Building Tech With No Experience Taught Me This Key Skill | Entrepreneur

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    Opinions expressed by Entrepreneur contributors are their own.

    In today’s world, not every founder comes from a technical background, and that’s no longer a dealbreaker. With AI projected to grow 28.5% by the end of the decade, even specialists are racing to keep up with emerging innovations. In such a fast-moving environment, the expectation that any one person, founder or otherwise, will master every detail is both unrealistic and counterproductive.

    The reality is this: You don’t need to code to build in tech, but you do need to translate. The ability to connect across disciplines has become the most important skill to develop — not just as someone building a company, but as someone leading one.

    If my experience in the NBA has taught me anything, it’s that every good team is made up of strong translators: people who understand both the locker room and the boardroom, coaches who can speak to data analysts and players, and leaders who can turn strategy into execution. Unsurprisingly, this is exactly what tech startups need, too.

    Related: Having No Experience Doesn’t Mean You Can’t Start a Business

    Clarity beats jargon

    When I started building Tracy AI, I quickly learned that trying to sound technical wasn’t helpful and actually slowed things down. Translating product decisions into clear, outcome-based language helped us move much faster. We didn’t always need to build models from scratch, but we did need to understand what those models were aiming for. That’s the real distinction between technical literacy and technical fluency: One is about credibility, but the other is about clarity. When everyone’s on the same page, people align, and products get better.

    Having this approach enabled us to bring in outside subject-matter experts, test assumptions early and avoid costly missteps that often come from internal echo chambers. Regardless of whether your team is fluent in Python, the ability to communicate clearly across complexity is what ultimately drives the company’s momentum.

    Hire smart

    I once read a quote from David Ogilvy that stuck with me: “Hire people who are better than you are, and then leave them to get on with it.” In tech, that means surrounding yourself with brilliant engineers, designers and product minds, and focusing your own energy on alignment, direction and decision-making.

    Building a company is about asking better questions, setting the right priorities and making sure your team is rowing in the same direction. That requires trust, communication and discipline, not technical depth. It also means knowing how to translate business needs into technical priorities, and vice versa.

    When it comes down to it, a founder’s job is to build bridges. Between vision and execution. Between product and people. Between strategy and reality. The most valuable skill in business isn’t your ability to code; it’s your ability to connect. Not being afraid of connecting strong, self-motivated individuals in your business is not only a recipe for success — it’s just good business sense.

    Related: How (Not Why) You Need to Start Hiring People Smarter Than Yourself

    Letting go

    Rapid-growth companies face a specific leadership challenge: knowing when to direct and when to step back. For founders, especially those without technical backgrounds, there’s a strong temptation to stay hands-on with every detail. According to a Harvard Business Review study, 58% of founders struggle to let go of control, often remaining stuck in what’s known as “founder mode,” even when the company is ready to scale.

    Being stuck in founder mode can slow down progress, stifle creativity and burn out the very experts hired to build. The job of the founder is to hold the vision and define the “what” and “why,” while trusting the team to figure out the “how.” That means giving engineers autonomy to explore solutions and trusting their understanding of the mechanics.

    At the same time, it’s important to stay connected to the people you’re building for. From my experience, I made sure to spend time with athletes, coaches and trainers — not just as a former player, but as a product owner committed to learning. That user feedback wasn’t just helpful; it became a compass for the tech. Just because we may need to let go of day-to-day, doesn’t mean we can’t get involved in other ways.

    At a certain point in any startup’s life, there is a transition from idea to alignment. Engineers speak in sprints and system architecture. Investors speak in ROI and risk. Users speak in frustrations, workarounds and outcomes. As a founder, your job is to be the connector between all of them, bridging the gap between engineers, users and investors, often speaking three very different languages in the same meeting.

    Related: Are You Running Your Business — or Is It Running You? How to Escape ‘Founder Mode’ and Learn to Let Go

    That means being able to explain what users actually want to your developers, breaking down technical constraints in a way your investors can understand and communicating a vision clearly enough that everyone in the business can see where they fit in. This is what makes a product usable, turns a group of builders into a team and ultimately transforms a good idea into a lasting company.

    In today’s world, not every founder comes from a technical background, and that’s no longer a dealbreaker. With AI projected to grow 28.5% by the end of the decade, even specialists are racing to keep up with emerging innovations. In such a fast-moving environment, the expectation that any one person, founder or otherwise, will master every detail is both unrealistic and counterproductive.

    The reality is this: You don’t need to code to build in tech, but you do need to translate. The ability to connect across disciplines has become the most important skill to develop — not just as someone building a company, but as someone leading one.

    If my experience in the NBA has taught me anything, it’s that every good team is made up of strong translators: people who understand both the locker room and the boardroom, coaches who can speak to data analysts and players, and leaders who can turn strategy into execution. Unsurprisingly, this is exactly what tech startups need, too.

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    Tristan Thompson

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  • How Generative AI Is Completely Reshaping Education | Entrepreneur

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    Opinions expressed by Entrepreneur contributors are their own.

    This is the second installment in the “1,000 Days of AI” series. As an AI keynote speaker and strategic advisor on AI university strategy, I’ve seen firsthand how generative AI is transforming education — and why aligning with the future of learning is now a leadership imperative.

    I’m starting with education, not because it was the most disrupted, but because it was the first to show us what disruption actually looks like in real time.

    Why start here?

    Education is upstream to everything. Every future engineer, policymaker, manager and founder is shaped by what happens in a classroom, a lecture hall or a late-night interaction with a search engine. When generative AI arrived, education didn’t have the luxury to wait. It was forced to adapt on the fly.

    ChatGPT didn’t quietly enter higher education. It detonated. Assignments unraveled. Grading frameworks collapsed. Students accessed polished answers in seconds. Faculty were blindsided. Institutional responses were reactive, inconsistent and exposed deep fractures in how learning was being defined and delivered.

    The idea that education meant memorization and regurgitation cracked almost overnight.

    Related: How AI Is Transforming Education Forever — and What It Means for the Next Generation of Thinkers

    AI in education didn’t break higher ed — It exposed the disconnect

    Long before AI, colleges were already straining under somewhat outdated models — rigid lectures, static syllabi, compliance-heavy assessments and a widening chasm between classroom instruction and workforce reality. Students were evolving faster than the systems designed to serve them.

    Generative AI made that gap impossible to ignore. Within months of its release, a majority of students admitted to using ChatGPT or similar tools for coursework. Meanwhile, most college presidents acknowledged they had no formal AI policy in place. The dissonance was loud, and it created not just urgency, but opportunity.

    In the past year, I’ve partnered with some of the largest education systems in the world to help develop their AI strategies. We co-developed governance frameworks, launched executive working groups, crafted responsible use guidelines and trained thousands of faculty across campuses. The goal wasn’t just to respond; it was to lead.

    At the same time, I’ve worked with community colleges — the frontline of workforce development. These institutions feel disruption first and move fastest. I’ve helped their leaders connect generative AI to student outcomes, integrate tools into classroom experimentation and align innovation with workforce readiness and equity.

    Whether it’s a flagship university or a high-impact college, the principle is the same: Strategy must align with people, culture and mission. The institutions making the biggest strides aren’t the ones with perfect AI plans. They’re the ones willing to move while others wait. This momentum is powered by intrapreneurship on the inside, and increasingly, by student-driven entrepreneurship on the outside.

    Students are becoming entrepreneurs

    Students aren’t waiting for permission; they’re reinventing how learning works. They adapt quickly, embrace emerging technologies and experiment boldly. Some might call it cheating. I’d call it testing the system.

    Today’s students no longer see education as a linear path to a degree. They see it as a launchpad for ideas.

    They’re using not just ChatGPT, but a full arsenal of AI tools — Perplexity, Gemini, Claude and more — to write business plans, generate branding, build MVPs and pressure-test real-world ideas. In fact, some aren’t just using tools; they’re creating their own. They’re not waiting to be taught. They’re teaching themselves how to build, launch and iterate.

    And yes, some of it is used for shortcuts. For cutting corners. For getting around assignments. Academic integrity is a real issue and one that institutions must address. But it’s also a signal that the system itself needs to evolve. These students are not just bypassing rules — they’re stress-testing the relevance of education as it exists today. And this is where intrapreneurs inside the system become critical to bridging the gap.

    Related: Why We Shouldn’t Fear AI in Education (and How to Use It Effectively)

    Intrapreneurs are moving institutions forward

    We all know that innovation rarely happens in the corner offices. The most powerful change isn’t coming from executive memos. It’s coming from the ground up.

    I’ve seen faculty members redesign assessments to include AI. Academic advisors build GPT-powered chatbots for student support. Department chairs test automated grading workflows while central IT is still writing policy. These are intrapreneurs — internal innovators leading with agility.

    My work has always been to help them scale and to get out of their way. Real transformation happens when governance, incentives and innovation align — and when execution is taken seriously.

    What institutions are doing that works

    Here are five moves I’ve seen deliver the greatest impact across leadership, faculty and students alike.

    1. Accept that change is inevitable: Ignoring, shaming or regulating innovation won’t stop it. Institutions must choose to engage with change, not resist it.

    2. Acknowledge that learning is now co-created: In many cases, students are more fluent in new tools than faculty. It may feel awkward — but that discomfort is the birthplace of co-creation and collaborative innovation.

    3. Support intrapreneurship and entrepreneurship: Encourage faculty and staff to experiment internally while also supporting students who are launching startups or prototyping ideas using AI.

    Institutions that move now are defining the next decade of learning. That doesn’t mean ignoring issues of academic integrity or the risks of cognitive offloading — we don’t know what we don’t know. But that uncertainty should inform us, not paralyze us.

    The institutions that will thrive in the next 1,000 days aren’t those with the most tech. They’re the ones that create space to adapt, listen and lead from every level — through both intrapreneurship and entrepreneurship.

    Related: How AI, Funding Cuts and Shifting Skills Are Redefining Education — and What It Means for the Future of Work

    Leadership is no longer a title; it’s a posture. Every instructor redesigning a course, every student experimenting with AI, every staffer who builds a better workflow is shaping the future of education.

    According to the World Economic Forum, over 40% of core job skills will shift in the next five years. That’s not a prediction — it’s a mandate.

    The only way forward is to build systems that learn as fast as the people in them. Presidents and provosts can provide vision, but it’s intrapreneurs who will make it real. Transformation won’t be dictated from above. It will be powered from within.

    AI is not the end. It’s the beginning of a new way of learning and a new kind of leadership.

    Coming next in the “1,000 Days of AI” series: Higher education wasn’t ready for AI, but students forced the conversation. K-12 is even more essential because critical thinking, ethical reasoning and digital fluency must begin long before college.

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    Alex Goryachev

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  • The New Number 1 AI Agent to Build a Profitable One-Person Business That Runs While You Sleep | Entrepreneur

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    Opinions expressed by Entrepreneur contributors are their own.

    Most entrepreneurs are still stuck treating AI like a writing assistant — pumping out blog posts, captions or emails and hoping it moves the needle. But OpenAI’s latest update just changed the game.

    This isn’t another “AI tool.” It’s ChatGPT’s new Agent — a fully autonomous virtual worker that can predict trends, reverse-engineer your competitors and even scan your Instagram for untapped revenue hiding in forgotten DMs.

    In this video, you’ll see exactly how solopreneurs are using it to run profitable one-person businesses on autopilot — replacing tasks that once took entire teams.

    Here’s what you’ll discover:

    • Viral trend prediction: How this Agent spots breakout topics before they hit the mainstream — helping you publish first and ride the wave.
    • Competitor edge: A real-time playbook that reveals where your competitors are weak — and hands you the exact moves to outrank them.
    • Free PR on demand: How the Agent finds podcasts, researches hosts and drafts custom pitches that actually get you booked.
    • Revenue recovery: The hidden sales buried in your inbox and social DMs — and how this Agent brings them back to life.

    The bottom line: this isn’t about saving time. It’s about building a business that grows without burning you out — one that works even when you’re not online.

    The AI Success Kit is available to download for free, along with a chapter from my new book, The Wolf is at The Door.

    Most entrepreneurs are still stuck treating AI like a writing assistant — pumping out blog posts, captions or emails and hoping it moves the needle. But OpenAI’s latest update just changed the game.

    This isn’t another “AI tool.” It’s ChatGPT’s new Agent — a fully autonomous virtual worker that can predict trends, reverse-engineer your competitors and even scan your Instagram for untapped revenue hiding in forgotten DMs.

    In this video, you’ll see exactly how solopreneurs are using it to run profitable one-person businesses on autopilot — replacing tasks that once took entire teams.

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    Ben Angel

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  • How to Protect Your Company From Deepfake Fraud | Entrepreneur

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    In 2024, a scammer used deepfake audio and video to impersonate Ferrari CEO Benedetto Vigna and attempted to authorize a wire transfer, reportedly tied to an acquisition. Ferrari never confirmed the amount, which rumors placed in the millions of euros.

    The scheme failed when an executive assistant stopped it by asking a security question only the real CEO could answer.

    This isn’t sci-fi. Deepfakes have jumped from political misinformation to corporate fraud. Ferrari foiled this one — but other companies haven’t been so lucky.

    Executive deepfake attacks are no longer rare outliers. They’re strategic, scalable and surging. If your company hasn’t faced one yet, odds are it’s only a matter of time.

    Related: Hackers Targeted a $12 Billion Cybersecurity Company With a Deepfake of Its CEO. Here’s Why Small Details Made It Unsuccessful.

    How AI empowers imposters

    You need less than three minutes of a CEO’s public video — and under $15 worth of software — to make a convincing deepfake.

    With just a short YouTube clip, AI software can recreate a person’s face and voice in real time. No studio. No Hollywood budget. Just a laptop and someone ready to use it.

    In Q1  2025, deepfake fraud cost an estimated $200 million globally, according to Resemble AI’s Q1 2025 Deepfake Incident Report. These are not pranks — they’re targeted heists hitting C‑suite wallets.

    The biggest liability isn’t technical infrastructure; it’s trust.

    Why the C‑suite is a prime target

    Executives make easy targets because:

    • They share earnings calls, webinars and LinkedIn videos that feed training data

    • Their words carry weight — teams obey with little pushback

    • They approve big payments fast, often without red flags

    In a Deloitte poll from May 2024, 26% of execs said someone had tried a deepfake scam on their financial data in the past year.

    Behind the scenes, these attacks often begin with stolen credentials harvested from malware infections. One criminal group develops the malware, another scours leaks for promising targets — company names, exec titles and email patterns.

    Multivector engagement follows: text, email, social media chats — building familiarity and trust before a live video or voice deepfake seals the deal. The final stage? A faked order from the top and a wire transfer to nowhere.

    Common attack tactics

    Voice cloning:

    In 2024, the U.S. saw over 845,000 imposter scams, according to data from the Federal Trade Commission. This shows that seconds of audio can make a convincing clone.

    Attackers hide by using encrypted chats — WhatsApp or personal phones — to skirt IT controls.

    One notable case: In 2021, a UAE bank manager got a call mimicking the regional director’s voice. He wired $35 million to a fraudster.

    Live video deepfakes:

    AI now enables real-time video impersonation, as nearly happened in the Ferrari case. The attacker created a synthetic video call of CEO Benedetto Vigna that nearly fooled staff.

    Staged, multi-channel social engineering:

    Attackers often build pretexts over time — fake recruiter emails, LinkedIn chats, calendar invites — before a call.

    These tactics echo other scams like counterfeit ads: Criminals duplicate legitimate brand campaigns, then trick users onto fake landing pages to steal data or sell knockoffs. Users blame the real brand, compounding reputational damage.

    Multivector trust-building works the same way in executive impersonation: Familiarity opens the door, and AI walks right through it.

    Related: The Deepfake Threat is Real. Here Are 3 Ways to Protect Your Business

    What if someone deepfakes the C‑suite

    Ferrari came close to wiring funds after a live deepfake of their CEO. Only an assistant’s quick challenge about a personal security question stopped it. While no money was lost in this case, the incident raised concerns about how AI-enabled fraud might exploit executive workflows.

    Other companies weren’t so lucky. In the UAE case above, a deepfaked phone call and forged documents led to a $35 million loss. Only $400,000 was later traced to U.S. accounts — the rest vanished. Law enforcement never identified the perpetrators.

    A 2023 case involved a Beazley-insured company, where a finance director received a deepfaked WhatsApp video of the CEO. Over two weeks, they transferred $6 million to a bogus account in Hong Kong. While insurance helped recover the financial loss, the incident still disrupted operations and exposed critical vulnerabilities.

    The shift from passive misinformation to active manipulation changes the game entirely. Deepfake attacks aren’t just threats to reputation or financial survival anymore — they directly undermine trust and operational integrity.

    How to protect the C‑suite

    • Audit public executive content.

    • Limit unnecessary executive exposure in video/audio formats.

    • Ask: Does the CFO need to be in every public webinar?

    • Enforce multi-factor verification.

    • Always verify high-risk requests through secondary channels — not just email or video. Avoid putting full trust in any one medium.

    • Adopt AI-powered detection tools.

    • Use tools that fight fire with fire by leveraging AI features for AI-generated fake content detection:

      • Photo analysis: Detects AI-generated images by spotting facial irregularities, lighting issues or visual inconsistencies

      • Video analysis: Flags deepfakes by examining unnatural movements, frame glitches and facial syncing errors

      • Voice analysis: Identifies synthetic speech by analyzing tone, cadence and voice pattern mismatches

      • Ad monitoring: Detects deepfake ads featuring AI-generated executive likenesses, fake endorsements or manipulated video/audio clips

      • Impersonation detection: Spots deepfakes by identifying mismatched voice, face or behavior patterns used to mimic real people

      • Fake support line detection: Identifies fraudulent customer service channels — including cloned phone numbers, spoofed websites or AI-run chatbots designed to impersonate real brands

    But beware: Criminals use AI too and often move faster. At the moment, criminals are using more advanced AI in their attacks than we are using in our defense systems.

    Strategies that are all about preventative technology are likely to fail — attackers will always find ways in. Thorough personnel training is just as crucial as technology is to catch deepfakes and social engineering and to thwart attacks.

    Train with realistic simulations:

    Use simulated phishing and deepfake drills to test your team. For example, some security platforms now simulate deepfake-based attacks to train employees and flag vulnerabilities to AI-generated content.

    Just as we train AI using the best data, the same applies to humans: Gather realistic samples, simulate real deepfake attacks and measure responses.

    Develop an incident response playbook:

    Create an incident response plan with clear roles and escalation steps. Test it regularly — don’t wait until you need it. Data leaks and AI-powered attacks can’t be fully prevented. But with the right tools and training, you can stop impersonation before it becomes infiltration.

    Related: Jack Dorsey Says It Will Soon Be ‘Impossible to Tell’ if Deepfakes Are Real: ‘Like You’re in a Simulation’

    Trust is the new attack vector

    Deepfake fraud isn’t just clever code; it hits where it hurts — your trust.

    When an attacker mimics the CEO’s face or voice, they don’t just wear a mask. They seize the very authority that keeps your company running. In an age where voice and video can be forged in seconds, trust must be earned — and verified — every time.

    Don’t just upgrade your firewalls and test your systems. Train your people. Review your public-facing content. A trusted voice can still be a threat — pause and confirm.

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    Ivan Shkvarun

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  • 3 Continuity Plan Failures That Toppled Industry Giants | Entrepreneur

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    A Business Continuity Plan (BCP) is often something that many professionals do not pay close attention to. History has shown us that even industry giants can be humbled and collapse or lose significant income when they overlook critical vulnerabilities in their preparation for crises.

    This can range from overconfidence in their abilities and technologies used to geopolitical unawareness. If the blind spots are not managed carefully, severe crises can be escalated, which can even threaten the future of the business.

    This article will look at three catastrophic BCP failures that brought down industry titans. Every organization or company can learn lessons from these in order to ensure that they do not make the same mistakes.

    Related: The Cost of Unpreparedness: Why Many Businesses Lack a Continuity Strategy

    Overconfidence in technology — How Facebook lost brand value

    Many leading social networks were a few years ago always confident that their AI and automation would help them to solve crises without the need for human intervention. The overreliance can pose severe problems when complex problems arise.

    In 2018, Facebook was dealt severe embarrassment for its overreliance on its automation after an automated network configuration tool misapplied changes, which caused the disruption of its services to millions. The incident exposed a critical flaw in that no manual override was in place to be able to correct the error quickly.

    Facebook not only suffered reputational damage as users and advertisers lost trust in its reliability, but it also exposed its slow response as engineers struggled to diagnose the issue due to opaque system dependencies. There was also a lack of redundancy as no backup systems were activated in order to bypass the faulty automation.

    The big lesson to be learned from Facebook’s error is that automation is still just a tool and not yet a replacement for human judgment. BCPs must always include fail-safes — i.e., manual overrides for critical systems, scenario testing, which means regular drills for technology failures, and transparency in order to ensure clear communication protocols during outages.

    Related: Do You Have a ‘Business Continuity Plan’?

    A failure to recognize geopolitical certainty led to Adobe usurping Kodak

    It is important for major companies to always pay attention to geopolitical shifts and understand that a company has to regularly adapt depending on what happens in the world. Kodak was guilty of treating geopolitical shifts as distant risks, and this shortsightedness led to its downfall.

    It was actually Kodak that invented the digital camera, but rather than further developing it, they opted to bury the technology in order to protect their film business. Upon noticing that humans were migrating to digital systems, Adobe migrated earlier than Kodak, embracing cloud-based tools and recurring revenue models. Kodak paid the price for reacting too late and had to file for bankruptcy in 2012.

    Kodak paid the price as their leadership clung to legacy revenue streams, they didn’t have a BCP for disruptive tech adaptation and as they had ignored hard trends such as digital migration, which was inevitable.

    Learning from the example of Kodak, it is always important for companies to monitor trends and especially identify hard trends such as demographics and technology evolution in order to predict disruptions. Flexible frameworks should be developed in order to allow rapid pivots, and there should be shareholder alignment to ensure that leadership and teams are prepared enough for transformational change.

    The semiconductor shortage crisis was caused by underestimating supply chain vulnerabilities

    Many BCPs opt to focus on internal risks, such as cyberattacks, and neglect external dependencies such as global supply chains. The 2020-2022 semiconductor shortage was an example of this, as it crippled industries from automotive to consumer electronics.

    The Covid-19 pandemic disrupted most industries — global logistic networks and many companies that rely on “just in time” manufacturing, such as Toyota, faced massive production delays. Companies that did not have diversified suppliers and inventory buffers lost billions in income. Ford is estimated to have lost $2.5B due to chip shortages.

    Because of single-point failures and the fact that there was an overreliance on a handful of suppliers, some were toppled. There was also a lack of contingency stock, and the lack of buffer inventory for critical components greatly impacted businesses, while slow adaptation delayed reshoring and supplier diversification.

    Related: Your Business Faces More Risks Than Ever — Here’s How to Ensure You’re Prepared For Any Disaster

    The lesson from all of this is that for a BCP to be resilient, it must include supplier diversification, stress testing and inventory buffers. There should be partnerships with vendors across regions. Stress testing will stimulate supply chain disruptions in BCP drills, and inventory buffers help to maintain strategic reserves for critical materials.

    In today’s day and age, the difference between survival and collapse will often lie in analyzing and recognizing blind spots before they become problems. All businesses should aim to learn from the above scenarios because, in business continuity, complacency is the greatest risk of all, as it can lead to a business’s downfall.

    With the world and technology now constantly evolving, a company must embrace change and continuously work on finding ways to be relevant for the far future.

    A Business Continuity Plan (BCP) is often something that many professionals do not pay close attention to. History has shown us that even industry giants can be humbled and collapse or lose significant income when they overlook critical vulnerabilities in their preparation for crises.

    This can range from overconfidence in their abilities and technologies used to geopolitical unawareness. If the blind spots are not managed carefully, severe crises can be escalated, which can even threaten the future of the business.

    This article will look at three catastrophic BCP failures that brought down industry titans. Every organization or company can learn lessons from these in order to ensure that they do not make the same mistakes.

    The rest of this article is locked.

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    Chongwei Chen

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  • What Leaders Can Learn From the First 1,000 Days of ChatGPT | Entrepreneur

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    This September marks 1,000 days since ChatGPT entered public consciousness. In that short time, the world has undergone a seismic shift. AI, once a buzzword, has become a foundational force — reshaping workflows, boardroom agendas and entire industries. No organization or country, large or small, was immune. Generative AI, alongside Claude, Gemini and open-source models, hasn’t merely added features. It has reset the pace of innovation, widened performance gaps and exposed how few institutions were equipped to turn experiments into execution.

    Across verticals — from education and enterprise to pharma and public sector — one insight has proven consistent: The organizations that thrive with AI don’t start with tools. They start with people.

    Since the release of ChatGPT, I’ve worked with hundreds of organizations worldwide as an AI keynote speaker, transformation advisor and strategic consultant. My work has included delivering keynotes, facilitating AI innovation workshops and guiding C-suite leaders across industries through the turbulence of AI adoption. From global corporations and top universities to national governments and biotech pioneers, the same patterns — and the same roadblocks — have emerged.

    This article opens the “1,000 Days of AI” series: a practical, cross-vertical exploration of what AI has already changed, what lies ahead and what leaders must do now to build alignment, trust and momentum in the age of intelligent systems.

    Related: The World Is Splitting Between Those Who Use ChatGPT to Get Better, Smarter, Richer — and Everyone Else

    This isn’t an IT project

    Many organizations began their AI journey by outsourcing it to IT. Generative tools like ChatGPT were handed to CIOs. Roadmaps were requested. Pilots were announced. Platforms were compared. Meanwhile, momentum stalled.

    In contrast, the most adaptive organizations began by engaging employees. They looked at workflows, not tech stacks. They asked: Where does friction live, and who understands it best? Then they launched internal sprints to solve meaningful problems. Not everything scaled, but what did revealed where the real opportunity lies.

    AI is not a dashboard or chatbot. It is a system-level catalyst. It touches every department — legal, HR, finance, operations, marketing. It raises questions about ethics, accountability and the future of work. It requires organizations to stop thinking in silos and start working across them.

    The most effective transformation doesn’t come from strategy decks; it comes from people trusted to rethink their daily work. When organizations create space for this kind of thinking, momentum follows.

    The intrapreneur era has arrived

    Some of the most impactful applications of AI in the last 1,000 days didn’t come from senior leadership or external consultants. They came from within. Employees who noticed inefficiencies, tested generative tools and found a better way forward. These internal changemakers — intrapreneurs — are rebuilding their organizations from the inside out.

    During the strategy sessions I’ve led, it’s often the customer support agent who builds an AI-powered knowledge base, the compliance analyst who uses large language models to automate documentation or the professor who reinvents grading. These aren’t isolated moments; they’re the new standard of innovation.

    The most agile organizations surface these efforts early, reward the behavior and scale what works. They don’t wait for formal initiatives. They build cultures where permission is replaced by participation. And they move quickly — not recklessly, but with confidence.

    Related: How Corporate ‘Intrapreneurs’ Can Harness the Power of AI to Transform Their Businesses and Supercharge Their Careers

    AI is a multiplier of culture

    AI doesn’t transform culture — it reflects it. An organization grounded in rigidity and control will experience more of the same. One built on curiosity, collaboration and transparency will scale faster, learn faster and lead the market.

    The highest-performing organizations start with a clear principle: alignment precedes acceleration. They ask employees what slows them down and then act on the answers. They replace static org charts with cross-functional teams. They move from policies to prototypes.

    Governance isn’t an afterthought — it’s embedded in the process. Legal, HR and compliance are not blockers. They’re design partners. Together, they build systems that are ethical, inclusive and scalable from day one.

    AI is not just a toolset. It’s a leadership challenge. The organizations that rise to meet it build trust and transformation in parallel.

    What’s working now

    After delivering hundreds of AI keynotes and partnering with organizations across the globe, a new set of success principles has emerged:

    • Start with employees. Those closest to the work understand the friction and how to fix it.

    • Distribute capability. Don’t limit training to tech teams. The best ideas often come from HR, legal and finance.

    • Run AI sprints like business design. These aren’t software pilots. They’re rapid experiments in new ways of working.

    • Make governance collaborative. Build ethical and compliance guardrails with — not after — the business.

    • Scale internal wins. Share success stories. Build intrapreneur networks. Turn momentum into muscle.

    These practices aren’t aspirational. They’re already creating measurable outcomes for organizations willing to lead the change.

    Related: 2025 AI Innovation Insights — Lessons Learned From Over 127 Global Speaking Sessions

    The next 1,000 days demand boldness

    The experimentation phase is over. The next 1,000 days require depth, speed and alignment. Pilots must become platforms. Strategy must move beyond decks and into daily action.

    The real divide is no longer between AI adopters and skeptics. It’s between those who integrate AI into culture and decision-making — and those who simply deploy tools without changing the system around them.

    What defines leadership in this next wave isn’t technology. It’s the ability to build trust in AI, connect siloed teams and redesign work at scale. The future of work is already arriving. The organizations that act now will shape it.

    Those who move with courage and clarity will thrive. Others will find themselves part of someone else’s success story.

    Coming next in the “1,000 Days of AI” series: How AI is transforming education — and what schools, faculty and students must do now to stay ahead.

    This September marks 1,000 days since ChatGPT entered public consciousness. In that short time, the world has undergone a seismic shift. AI, once a buzzword, has become a foundational force — reshaping workflows, boardroom agendas and entire industries. No organization or country, large or small, was immune. Generative AI, alongside Claude, Gemini and open-source models, hasn’t merely added features. It has reset the pace of innovation, widened performance gaps and exposed how few institutions were equipped to turn experiments into execution.

    Across verticals — from education and enterprise to pharma and public sector — one insight has proven consistent: The organizations that thrive with AI don’t start with tools. They start with people.

    Since the release of ChatGPT, I’ve worked with hundreds of organizations worldwide as an AI keynote speaker, transformation advisor and strategic consultant. My work has included delivering keynotes, facilitating AI innovation workshops and guiding C-suite leaders across industries through the turbulence of AI adoption. From global corporations and top universities to national governments and biotech pioneers, the same patterns — and the same roadblocks — have emerged.

    The rest of this article is locked.

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    Alex Goryachev

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  • AI Clones Are No Longer Science Fiction — They’re Real | Entrepreneur

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    In a quiet conference room, a startup founder’s digital doppelgänger delivers a pitch to investors, answering questions with the founder’s voice and expertise, even as the real founder is elsewhere.

    This scenario is no longer science fiction. A wave of AI personas, “digital twins” and self-replicating agents is emerging, allowing individuals to outsource aspects of themselves to AI. From celebrity coaches to tech icons, these AI-powered avatars promise to scale human presence and productivity in unprecedented ways. Yet they also raise profound questions about identity, authenticity and the very nature of work in a post-human era.

    The rise of personal AI personas and digital twins

    The concept of a “digital twin” originated in industry, a virtual replica of a physical system for simulation and optimization. Now, it’s being reimagined on a personal level. AI digital twins are dynamic, evolving AI models that replicate a person’s knowledge and grow it over time. Instead of static data, these twins use custom AI models to mirror an individual’s unique perspectives, expertise and even communication style. The goal is a “living, breathing representation” of one’s thought processes.

    Crucially, personal AI personas aren’t just parroting facts. They aim to capture how you think and speak. A true digital twin can replicate an individual’s unique perspectives, experiences and knowledge base, assisting with recall, generating insights and even communicating in your own voice.

    Related: Digital Twins Are the Future — Here Are 5 Ways to Keep Them Secure While Manufacturing Innovation

    Tools enabling “self-replication”

    A growing ecosystem of platforms and tools is making AI self-cloning accessible:

    • Personal.ai: Offers a personal language model trained on your content, effectively becoming your memory and voice in digital form. It emphasises privacy and user control, positioning the AI twin as a secure asset that continuously learns and updates with you.
    • Lindy: A no-code AI agent builder that acts like a personal or business assistant. Lindy allows users to create custom AI “assistants” that integrate with email, calendars, CRM and more.
    • OpenAI’s Custom GPTs: OpenAI’s ChatGPT now lets users build custom GPTs, essentially personal chatbots turned to a specific persona or knowledge base. With a ChatGPT Plus account, you can create a bespoke AI and share it in a GOT marketplace.
    • ElevenLabs and Synthesia: Provide ultra-realistic voice and video cloning, enabling AI personas to speak and appear as their human counterparts. Reid Hoffman used these tools to create a deepfake avatar of himself for an AI interview experiment.

    Early adopters: From gurus to CEOs

    This once-futuristic concept is now a reality embraces by high-profile leaders:

    • Tony Robbins launched “Tony’s AI Twin,” an interactive coach built by Steno.ai using ElevanLabs voice cloning. It delivers advice drawn from his decades of work is accessible 24/7.
    • Deepak Chopra unveiled DigitalDeepak.ai, an AI trained on his teachings to offer guidance on spirituality and well-being.
    • Reid Hoffman created “Reid AI,” a custom GPT trained on 20 years of this thinking, and used a digital avatar to appear in interviews and explore the ethical limits of this tech.
    • Fan-made projects like “Ask Naval” offer an AI version of Naval Ravikant, trained unofficially on his tweets, interviews and writings.

    The allure: Outsourcing and scaling the self

    Why are leaders drawn to AI personas? The allure is clear. AI twins offer the promise of infinite reach, an ability to engage thousands simultaneously, attend multiple meetings or provide mentorship across time zones. They create an entirely new monetization model, where personal knowledge and brand become a scalable product. Robbins’ team, for instance, notes that his AI twin has opened a new revenue stream with no additional time investment. Productivity gains are significant, as digital twins take over routine tasks, freeing founders to focus on creative or high-value work. Additionally, trained AI twins can serve as cognitive memory tools, surfacing forgotten insights, maintaining brand consistency and supporting rapid decision-making.

    Zoom CEO Eric Yuan has even suggested that AI digital twins could eventually be so effective that they reduce the workweek to three days. For visionary leaders, AI personas are not just tools; they’re multipliers of influence, knowledge and time.

    Risks and ethical questions

    As a lawyer, I always ask: What are the risks, and what are the ethics behind the product? This frontier is not without peril:

    • Authenticity: Audiences may struggle to trust whether communication comes from the person or their AI. Transparency and fidelity are key.
    • Misinformation: AI personas must be tightly governed to avoid reputational or legal risk.
    • Privacy: Ownership of one’s digital likeness is a complex, emerging legal issue.
    • Human skill erosion: Over-reliance on AI might dull the very cognitive and interpersonal skills that define great leaders.

    Related: Why Every Entrepreneur Must Prioritize Ethical AI — Now

    The post-human edge

    Founders are no longer just building products; they’re becoming platforms. The real edge lies in knowing what to scale and what to keep human. An AI persona might extend your influence, but it’s your irreplaceable presence, empathy and judgment that remain your ultimate value.

    In a world where anyone can clone their voice and replicate their insights, the differentiator is not your scalability, but your discernment. The future belongs to those who know when to outsource — and when to show up.

    Founders and businesses are entering a post-human business era. Let’s build it wisely.

    In a quiet conference room, a startup founder’s digital doppelgänger delivers a pitch to investors, answering questions with the founder’s voice and expertise, even as the real founder is elsewhere.

    This scenario is no longer science fiction. A wave of AI personas, “digital twins” and self-replicating agents is emerging, allowing individuals to outsource aspects of themselves to AI. From celebrity coaches to tech icons, these AI-powered avatars promise to scale human presence and productivity in unprecedented ways. Yet they also raise profound questions about identity, authenticity and the very nature of work in a post-human era.

    The rise of personal AI personas and digital twins

    The rest of this article is locked.

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    Rejna Alaaldin

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  • Closer or Colder? How AI Shapes Your Customer Relationships | Entrepreneur

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    I’m not going to lie, the latest generation of AI, especially large language models and agentic AI, is nothing short of impressive. At Human Cloud, we used tools like Claude and Windsurf to accomplish in 5 minutes what had previously taken us 5 years.

    On the surface, it’s a story of overnight magic. But dig deeper and you’ll find that the real magic wasn’t the AI itself; it was the five years of groundwork that came before. We spent that time using spreadsheets, Canva graphics, CRM automations and hacky off-the-shelf tools to create the right sales and delivery motion, and validate our customers’ needs.

    Only then did the AI become a true accelerator, as we used Claude, Windsurf and AWS to create the Human Cloud Platform in less than 5 minutes.

    This brings up a crucial point. AI can easily be a distraction, prioritizing hype and buzz over real revenue and profitability. Why? Because the fundamental principle of business remains unchanged: every breakthrough starts with a deep understanding of what your customers need.

    Before you invest another dollar in AI, ask yourself one question: Is this technology making us closer to our customers, or pulling us further away?

    Here are five steps to ensure AI helps you get closer.

    1. Manually implement before automating

    “Do things that don’t scale” is a famous startup moniker brought up by Paul Graham, co-founder of Y Combinator, in his essay in 2013. As a 4x founder myself, this ethos has always run true.

    In the case of AI, in every scenario, ask yourself if there is a manual alternative. If there is, try that first, then automate based on customer demand.

    Related: LinkedIn’s Reid Hoffman: To Scale, Do Things That Don’t Scale

    2: Capture enough manual feedback

    Step 1 is only half the story. The other half is ensuring you have enough of the right type of feedback to automate what really works. My strongest recommendation is to capture feedback that’s closest to customers actually paying, engaging and sharing.

    I learned this the hard way in a former startup. We spent 3 months listening and iterating on prototypes based on feedback. We were maniacal in the level of detail we captured, from the user experience to the design. Then we launched, and less than 5% of these users actually paid. Instead, we shouldn’t have listened to what they said, but instead prioritized what they did.

    If you want a book to help you capture the right type of feedback, check out The Mom Test.

    Related: How the ‘Mom Test’ Can Help You Cut Through B.S. and Find Important Answers

    3: Make AI accessible for everyone, not just AI experts

    Rather than investing in an AI team or hiring AI experts, give everyone an opportunity to apply AI across their team and their work.

    Preston Mossman, Senior Director of AI Consulting for Galaxy Square, told me, “learning to use AI is a muscle you have to build. A lot of people self-select out because they can’t use AI today to help them, but the first step is to accelerate their comfort and understanding in a way that feels valuable to them.”

    When asking Preston about ways companies have helped their leaders get comfortable with it, he brought up investing in AI-related tools for interested individuals.

    In his words, “if your mechanic told you about a $50 wrench that could get your job done just as well for half the cost, you would buy it for them or find a new mechanic (with the $50 wrench).”

    Leaders not using AI in 5 years will be like leaders not using a computer today.

    Related: Why Your AI Strategy Will Fail Without the Right Talent in Place

    4: Hire independent experts first

    Telling someone to use AI with no support is like telling someone to jump out of a plane without a parachute.

    Obviously, hiring AI experts as full-time employees would be expensive and out of reach for most of us. Likewise, AI trainings take time, might be expensive, and rarely has direct applicability from training to application.

    But a shortcut is hiring individuals who already use AI, as 65% of independent experts were already using AI as far back as 2024, and 95% of independent experts stated that AI makes them more competitive.

    This brings up step 4: to hire flexible talent first, with flexible talent defined as independent, freelance, and fractional experts.

    The data is clear that flexible talent upskills faster than full-time employees and is ahead of the curve in AI adoption and effectiveness. It’s not just AI, Deloitte research shows that the independent workforce upskills faster than their full-time peers.

    There are also four massive benefits of flexible talent compared to full-time. You can control cost. You have a quicker time to effectiveness. You learn by seeing their expertise. And the most important benefit is that this is the future workforce.

    To get started, look for a flexible talent platform that is specialized in your region, industry, and the application you need AI for. There are over 800 of these specialized solutions.

    Related: Solopreneurship and Freelancing Is Here to Stay — Are You Ready?

    5: Scale like the cloud

    We take for granted how transformational cloud computing has been for us entrepreneurs. Without getting too geeky, what it really did was enable us to scale in line with customer demand rather than taking big bets because of large fixed costs.

    Apply this same mindset to AI.

    Do you think your AI idea is the next big breakthrough that will transform your company, your industry, and the world? That’s great. Now go through steps 1-4 before you bet the farm.

    I’m not going to lie, the latest generation of AI, especially large language models and agentic AI, is nothing short of impressive. At Human Cloud, we used tools like Claude and Windsurf to accomplish in 5 minutes what had previously taken us 5 years.

    On the surface, it’s a story of overnight magic. But dig deeper and you’ll find that the real magic wasn’t the AI itself; it was the five years of groundwork that came before. We spent that time using spreadsheets, Canva graphics, CRM automations and hacky off-the-shelf tools to create the right sales and delivery motion, and validate our customers’ needs.

    Only then did the AI become a true accelerator, as we used Claude, Windsurf and AWS to create the Human Cloud Platform in less than 5 minutes.

    The rest of this article is locked.

    Join Entrepreneur+ today for access.

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    Matthew Mottola

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  • Roblox, Scale AI, Databricks Hiring ‘AI Native’ New Grads | Entrepreneur

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    Forget “digital native,” the term that refers to those who began interacting with digital technology at a young age. “AI native” is the new label getting entry-level college graduates six- or seven-figure salaries right out of school — and it’s all about capitalizing on young workers’ ability to use AI.

    According to a Tuesday report from The Wall Street Journal, though the unemployment rate for entry-level workers as a whole was 4.8% in June, higher than the 4% for all workers, companies are still hiring college graduates with AI experience.

    Data analytics firm Databricks, for example, is hiring three times as many recent college graduates this year than last year because of their ability to use AI. The company’s CEO, Ali Ghodsi, told The Journal that some junior staff members having a “big impact” are getting paid a million dollars — and they’re under 25 years old.

    Related: How Much Does Apple Pay Its Employees? Here Are the Exact Salaries of Staff Jobs, Including Developers, Engineers, and Consultants.

    “They’re going to be all AI-native,” Ghodsi told the outlet, referring to the college graduate hires. “We definitely have people, quite junior people, [who] have a big impact, and they’re getting paid a lot. Under 25, you can be making a million.”

    Databricks’ careers page shows that an entry-level AI research scientist working in New York City or San Francisco can make anywhere from $150,000 to $190,000 in base salary.

    Ghodsi isn’t the only tech leader using the term “AI-native.” Scale AI, an AI training service that received a $14.3 billion investment from Meta in June, pays employees right out of college salaries of $200,000 per year, according to The Journal.

    Scale AI’s Head of People, Ashli Shiftan, told the outlet that Scale AI was “eager to hire AI-native professionals, and many of those candidates are early in their careers.”

    Meanwhile, at Roblox, a virtual gaming platform, machine learning engineers with little to no experience can earn more than $200,000 annually, according to salary site Levels.fyi.

    Related: Here’s How Much a Typical Microsoft Employee Makes in a Year

    The market for those with AI experience is divided into two categories, Stanford University Professor of Computer Science Jure Leskovec told The Journal. The first refers to some doctoral students who complete Ph.D. studies in machine learning and AI and receive large offers from companies without any experience.

    The other category encompasses programmers who use AI to become more effective, increasing their value on the job market.

    “It’s almost like a next generation of a software engineer,” Leskovec told the outlet.

    Forget “digital native,” the term that refers to those who began interacting with digital technology at a young age. “AI native” is the new label getting entry-level college graduates six- or seven-figure salaries right out of school — and it’s all about capitalizing on young workers’ ability to use AI.

    According to a Tuesday report from The Wall Street Journal, though the unemployment rate for entry-level workers as a whole was 4.8% in June, higher than the 4% for all workers, companies are still hiring college graduates with AI experience.

    Data analytics firm Databricks, for example, is hiring three times as many recent college graduates this year than last year because of their ability to use AI. The company’s CEO, Ali Ghodsi, told The Journal that some junior staff members having a “big impact” are getting paid a million dollars — and they’re under 25 years old.

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  • Amazon Is Giving Whole Foods Staff New Job Offers | Entrepreneur

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    Amazon is completing its takeover of Whole Foods, eight years after buying the grocery brand for $13.7 billion.

    The Wall Street Journal reported on Wednesday that on Nov. 10, Amazon plans to give new job offers to U.S. Whole Foods corporate employees, complete with new titles, salaries, and benefits.

    The affected employees work in positions ranging from merchandising to marketing, and will be offered a month to review the new compensation packages, according to the report.

    Under the new job offers, corporate Whole Foods employees will gain Amazon discounts and healthcare benefits, but lose perks, including four weeks of remote work a year. Amazon implemented a return-to-office mandate requiring five days a week in the office beginning in January.

    Related: Some Whole Foods Locations Are Experiencing Empty Shelves After a Main Distributor Was Hacked

    Additionally, Whole Foods corporate workers will receive Amazon stock instead of an annual bonus, starting next year. Corporate employees will keep a 20% discount at Whole Foods stores for a year, but lose the perk in 2027.

    Amazon bought Whole Foods in 2017 and offers a discount to shoppers with Amazon Prime subscriptions. It has also implemented its technology to make stores available for Amazon package pickups and returns.

    Since the acquisition, Whole Foods has increased sales by more than 40% and expanded its footprint from 467 stores in 2017 to 535 stores in October 2024, per The Business Journals.

    Amazon previously allowed Whole Foods staff to keep their job titles and their benefits. Whole Foods even had its own dedicated CEO, Jason Buechel, until January, when Amazon expanded his responsibilities to include Amazon Fresh grocery stores and Amazon Go convenience stores. Buechel is now Amazon’s vice president of worldwide grocery.

    Related: ‘I Hate Bureaucracy’: Leaked Internal Amazon Document Reveals How the Tech Giant Is Cutting Down on Middle Management

    In a leaked meeting in June for Amazon’s grocery team, Buechel said that internal bureaucracy slows down Amazon’s grocery business and holds the team back. He mentioned that it was “taking too long” for spending approvals and other decisions to occur.

    “Ultimately, we’re wasting time,” Buechel said at the meeting. “It’s taking too long for decisions and approvals to take place, and it’s actually holding back some of our initiatives.”

    Whole Foods falls under Amazon’s physical stores segment, which also includes Amazon Fresh and Amazon Go stores. During the second quarter of 2025, Amazon’s physical stores generated $5.6 billion in sales, a 7% increase from the same time last year.

    Amazon is completing its takeover of Whole Foods, eight years after buying the grocery brand for $13.7 billion.

    The Wall Street Journal reported on Wednesday that on Nov. 10, Amazon plans to give new job offers to U.S. Whole Foods corporate employees, complete with new titles, salaries, and benefits.

    The affected employees work in positions ranging from merchandising to marketing, and will be offered a month to review the new compensation packages, according to the report.

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  • How to Unlock Profitable SEO as AI Search Engines Take Over | Entrepreneur

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    Opinions expressed by Entrepreneur contributors are their own.

    As AI technology continues to grow in capability and popularity, the online search landscape and search optimization are rapidly changing. AI search engines, including Perplexity, Google’s AI mode, ChatGPT Search, Gemini, Arc Search and others, are competing for their share of searches and are quickly catching up to traditional search engines.

    In fact, one study projected that AI search engines may have more users than traditional search engines by 2028. These constantly changing search dynamics have many businesses wondering whether their current SEO strategy is sufficient or whether they need to adapt to stay relevant. While many SEO strategies can help businesses rank in both traditional and AI search engines, there are some key techniques businesses can implement to ensure that the evolution of AI search engines does not leave them behind.

    Related: Want to Be Discovered in AI Search? These Are the Sources That Matter

    The increasing popularity of AI search engines

    AI search engines are generative AI platforms that create answers to queries entered by users. Rather than simply presenting results, like traditional search engines, AI search engines summarize and present information pulled from multiple sources. AI search engines are quickly becoming the first choice for many users.

    Rather than using a traditional search engine, people prefer to use AI search engines for more specific, conversational queries. AI search engines consolidate and summarize information, which appeals to many users, particularly when they have a longer, more specific search query or are researching a new topic. Users can also utilize AI search engines to compare products or generate a list of multiple service providers without needing to visit various websites.

    4 strategies for ranking in AI search engines

    AI Search engines cite the websites they pull information from. Having your website cited as a source is an effective way to generate organic traffic and increase leads. Fortunately, many of the SEO strategies that are effective for ranking in traditional SERPs remain effective for ranking in AI search engines. Additionally, search engines pay attention to ranking positions when they select websites to pull information from and cite. However, for businesses looking to stay ahead of their competition, here are a few strategies that we implement at Outpace SEO to make sure our clients rank in AI search engines as well as traditional SERPs.

    1. Audit your strategy

    AI search engines prioritize credibility and relevancy. Before you begin, audit your current SEO strategy and identify its strengths and weaknesses. Who is your target audience, and are they likely to use AI search engines? Are you hoping to rank nationally or locally? Answering these questions can help you adapt your strategy for continued success.

    2. Ensure visibility

    It’s essential to make sure that AI search engines can index your website and easily understand the context and relevance of your content. In-depth technical SEO is crucial to ensure that your website is visible to the relevant search engines. Some search engines have specific primary crawlers that need to be enabled in your robots.txt file. Make sure that your pages are indexed by Bing, not just Google. Your site should have a simple and easy-to-understand site architecture that allows AI engines to navigate it effectively. Other technical strategies include optimizing alt text, URLs, meta titles, page speed and internal linking to enhance your website’s visibility.

    Related: How AI Is Transforming the SEO Landscape — and Why You Need to Adapt

    3. Create concise, organized content

    AI search engines summarize information in conversational language. This means that they can more easily extract information from websites that provide clear and concise content. Answering questions clearly in a sentence or two increases the chance that AI search engines will cite your website in answers to search queries. Creating content that is clearly organized with header tags is an effective way to make sure that users and search engines can easily skim your content and identify its relevance. Using high-volume, long-tail keywords as titles and headers also increases the chance that AI search engines will use your content when they generate answers to popular questions. How you write your content can significantly increase your chances of ranking both in traditional search engines and AI search engines.

    4. Build online authority

    Both traditional search engines and AI search engines are more likely to rank your website if it has a strong online presence. AI search engines pay particular attention to websites with regularly updated content and a strong off-page authority. The type of brand mentions and backlinks you acquire is also significant; backlinks from websites in your industry with strong domain authority will do more to boost your website’s profile than links that are irrelevant or appear untrustworthy. By consistently creating on-site and off-site content, you can establish authority and credibility within your industry, resulting in increased rankings, leads and traffic.

    Final thoughts

    As more people use AI search engines, it may not be enough for businesses to simply rank on SERPs. If your target audience is likely to use an AI search engine to find businesses, information and products, then it’s essential to adapt your SEO strategies to rank in AI search engines as well as traditional search engine results pages. By creating content strategically, implementing technical optimizations on your website and developing your online authority, you can provide your business with a competitive edge and keep up with rapidly advancing AI technology.

    As AI technology continues to grow in capability and popularity, the online search landscape and search optimization are rapidly changing. AI search engines, including Perplexity, Google’s AI mode, ChatGPT Search, Gemini, Arc Search and others, are competing for their share of searches and are quickly catching up to traditional search engines.

    In fact, one study projected that AI search engines may have more users than traditional search engines by 2028. These constantly changing search dynamics have many businesses wondering whether their current SEO strategy is sufficient or whether they need to adapt to stay relevant. While many SEO strategies can help businesses rank in both traditional and AI search engines, there are some key techniques businesses can implement to ensure that the evolution of AI search engines does not leave them behind.

    Related: Want to Be Discovered in AI Search? These Are the Sources That Matter

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  • His Side Hustle Earns 6 Figures a Year: 1-2 Hours of Work a Day | Entrepreneur

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    This Side Hustle Spotlight Q&A features Dennis Tinerino, 39, of Los Angeles, California. Tinerino worked in online sales when he first learned about domain names and launching websites, which helped him discover domain investing as a side hustle. Here’s how he turned the gig into a lucrative business that brings in six figures a year — with about an hour or two of work per day. Responses have been edited for length and clarity.

    Image Credit: Courtesy of Domain Smoke. Dennis Tinerino.

    When did you start your side hustle, and where did you find the inspiration for it?
    I started my side hustle in 2014 after discovering that domain names are like real estate, only online. Realizing the right ones could keep growing in value was all the inspiration I needed to dive in. My interest first sparked when I was launching a new website and came across a domain name for sale. I had no idea what the cost might be, so I filled out the form on the seller’s website. A domain broker from Afternic replied, explaining that the name was for sale and would require a six-figure minimum offer. Unfortunately, this domain was out of my budget for this project, but thankfully, they were very helpful and explained why it was valued at that price, even suggesting other names that were closer to my budget at the time. That conversation grabbed my attention and pushed me to do a deep dive into the world of domains.

    Related: These 31-Year-Old Best Friends Started a Side Hustle to Solve a Workout Struggle — And It’s On Track to Hit $10 Million Annual Revenue This Year

    What were some of the first steps you took to get your side hustle off the ground? How much money/investment did it take to launch?
    When I started, I did not know anyone personally who was doing this, so I had to teach myself. I dove into blogs, read FAQ sections on marketplaces and learned everything I could about how domains are bought and sold. Like most new investors, my first stop was GoDaddy, where I began registering domains that sounded cool or interesting. Luckily, I kept my spending in check and only bought four domains for a total of $36. One of them, LawyerBoss.com, ended up selling for $700 on Afternic less than two months after I bought it for about $8. That sale was a turning point. It was exciting to see that I could learn the process, list a name and have someone actually buy it for their business. From that moment on, I was hooked and started looking for more ways to find new domains to invest in.

    If you could go back in your business journey and change one process or approach, what would it be, and how do you wish you’d done it differently?
    If I could hop in a time machine, I’d go straight back and immediately sign up for the Domain Academy course on day one. It covers everything about domains, with resources from A to Z, and there’s nothing else like it. I could have skipped months of trial and error, saved a few gray hairs and gotten in the game faster with a deeper understanding of domains and the industry as a whole. There are countless strategies in domain investing, but before you dive in, you need to understand how domains work, what end users are looking for and the different ways to approach them. Trust me, learning this early is a lot cheaper than buying cool names and hoping for the best.

    Related: I Interviewed 5 Entrepreneurs Generating Up to $20 Million in Revenue a Year — And They All Have the Same Regret About Starting Their Business

    When it comes to this specific business, what is something you’ve found particularly challenging and/or surprising that people who get into this type of work should be prepared for, but likely aren’t?
    The hardest part for newcomers is getting the right education. Too many jump in blind, skip the basics and end up spinning their wheels. It’s like trying to fix a car without ever popping the hood. Making uninformed investments is a quick way to waste time, burn cash and get frustrated fast. Another big surprise is how much upkeep a domain portfolio requires. This is not a buy it and forget it business. You have to watch your names, keep up with renewals, follow the market and be honest when it is time to let go of names that are no longer relevant or valuable.

    Can you recall a specific instance when something went very wrong? How did you fix it?
    In my early days, I started doing outbound marketing to create interest and generate sales for my domains. I was not thinking about trademarks at the time and reached out to companies that owned marks similar to my names. That mistake earned me a stack of legal threats and cease and desist letters. Thankfully, I was able to resolve each situation on good terms by finding common ground with the parties involved. It was a valuable lesson to always check for trademarks before investing or reaching out to buyers, and I am glad I learned it early. Avoiding legal battles is high on my priority list.

    How long did it take you to see consistent monthly revenue? How much did the side hustle earn?
    It wasn’t until my second to third year of domain investing that I began to see consistent monthly revenue come in. What I noticed is that after my first year, when I started to educate myself more, build up my domain portfolio with better quality domains and then began outbound marketing, my sales accelerated, and steady monthly revenue came in. In the first year, I earned a few thousand with my first initial sales. In the second year, it was in the lower five figures, and it kept ramping up from there as I invested more time and resources.

    Related: This Couple’s ‘Scrappy’ Side Hustle Sold Out in 1 Weekend — It Hit $1 Million in 3 Years and Now Makes Millions Annually: ‘Lean But Powerful’

    What does growth and revenue look like now?
    Back in 2014, the portfolio was just a handful of domains. Today, it has grown to roughly 8,000 to 10,000 names. There were stretches where I was buying one name a day, and some days I went on a spree and grabbed 20, using profits to keep scaling and building the portfolio. Each year, I have consistently added another 500 to 1,000 names, experimenting with different top-level domains (TLDs) and country code top-level domains (ccTLDs) when I spot a trend. The real growth has come from .com domains, which remain the most in-demand with end users. What started as a few thousand dollars a year has grown into a business generating steady six-figure revenue for the past five years. That growth comes from years of research, relentless market tracking, careful portfolio maintenance and making the right moves at the right time, even when they were tough.

    How much time do you spend working on your business on a daily, weekly or monthly basis?
    On a typical day, I spend one to two hours building and managing my portfolio. Over a week, that adds up to 15 to 20 hours, and by the end of the month, it’s usually 60 to 80 hours.

    How do you structure that time? What does a typical day or week of work look like for you?
    My time is split between portfolio management, searching for fresh inventory, outbound marketing and closing deals. Each week, I set aside blocks of time to review my portfolio, adjust prices and prepare names for marketing. Once you get past a few hundred domains, daily portfolio management becomes essential. It is easy to let small tasks slip through the cracks, and that is when mistakes happen. What has saved me the most time is staying organized. It sounds easier than it is, but creating workflows, keeping detailed spreadsheets and using the right tools will save you from falling behind on your daily tasks.

    Related: These Friends Started a Side Hustle in Their Kitchens. Sales Spiked to $130,000 in 3 Days — Then 7 Figures: ‘Revenue Has Grown Consistently.’

    What do you enjoy most about running this business?
    Domain investing can get a little lonely sometimes because you have to put in the hours to stay sharp and up to date. But the thing I have enjoyed the most is the investor community. We are very active on X, and I have met incredible people from all over the world who have helped me grow as an investor, taught me a ton and become lifelong friends.

    The freedom that comes with this business is unlike anything else. You can run it from anywhere in the world with minimal tech skills. You set the rules, choose your hours, decide your prices, pick where to sell your names and choose which names you want to buy.

    Over the years, as an investor, I found myself looking at tens of thousands of domains coming to auction or expiring every day. As great as many of those names were, I knew I could not buy them all, but I also did not want to see those opportunities go unnoticed by other investors. That got me thinking about how I could share this research and these findings with others. That is when I launched Domain Smoke, a daily newsletter sharing industry news, investment opportunities and the best domains hitting auction each day. Since its launch in 2019, it has grown to thousands of readers worldwide who read it every day.

    Based on your journey so far, what’s your best advice for someone who wants to get started with this kind of business?
    When I got started, there were a few things I would change if I could, and I hope my experience can help you find success in your own journey as a domain investor. If you are new to domain investing, here are three tips that can help you start on the right foot:

    1. Be patient with hand registrations
      This one is not easy, but you will thank me later. Try to hold back from registering new domains by hand until you have a proper understanding of domain investing. The easiest mistake beginners make is buying names that are not likely to sell. Many of them also have little or no appeal to end users. That costs both time and money you will not get back. Once you get past the learning phase, you will have plenty of time to acquire domains that actually fit your strategy. When you know what to invest in, you will be glad you waited.
    2. Invest in yourself early
      They say the more you learn, the more you earn, and that is definitely true with domains. Avoid rookie mistakes by investing in your education. One of the best places to start is the Domain Academy course from GoDaddy, which teaches the ins and outs of the business. Just like any other form of investing, there are many ways to make money, but the best way to improve your chances of success early on is to educate yourself.
    3. Keep learning and follow the data
      It is easy to get started, build up a bit of knowledge and then think you know it all. But markets evolve, trends shift, and change is constant. Stay up to date with domain blogs, industry news, eBooks, Domain Sherpa shows and forums like NamePros, which is full of free knowledge for beginners. Most importantly, follow the data. Study sales and trends using resources like NameBio, dotDB and DNJournal. These will help you understand what is actually selling, what is trending and why. That insight gives you a competitive edge and keeps you aligned with the market.

    Related: I’ve Interviewed Over 100 Entrepreneurs Who Started Businesses Worth $1 Million to $1 Billion or More. Here’s Some of Their Best Advice.

    Start small, stay consistent and give yourself time to learn. Every successful investor was once a beginner. The more you study and track sales data, the sharper your skills will become. And remember, the community side of this business matters too. The investors and connections you build can be just as valuable as the domains you own.

    Want to read more stories like this? Subscribe to Money Makers, our free newsletter packed with creative side hustle ideas and successful strategies. Sign up here.

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    Amanda Breen

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  • These Fields Are Losing the Most Entry-Level Jobs to AI: Study | Entrepreneur

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    AI is cutting into entry-level jobs, according to a new Stanford University study, released on Tuesday.

    Stanford researchers analyzed ADP payroll data, which included monthly payroll information for millions of workers at thousands of companies, to find how AI impacts employment for people ages 22 to 25 compared to other age groups.

    The study found that the professions most exposed to automation with AI were operations managers, accountants, auditors, general managers, software developers, customer service representatives, receptionists, and information clerks. In those AI-impacted jobs, which lost the most entry-level positions to the technology, employment for young workers has declined by 13% over the past three years.

    Related: These 3 Professions Are Most Likely to Vanish in the Next 20 Years Due to AI, According to a New Report

    “There’s definitely evidence that AI is beginning to have a big effect,” Erik Brynjolfsson, Stanford professor, economist, and first author on the study, told Axios. He called the trend of reduced entry-level hiring “the fastest, broadest change” that he had ever seen in the workplace, second only to the shift to remote work during the pandemic.

    Meanwhile, the study determined that since late 2022, when ChatGPT was released, employment for more experienced workers has remained steady or even improved in AI-impacted fields.

    In software engineering and customer service, for example, the study found that “employment for the youngest workers declines considerably after 2022, while employment for other age groups continues to grow.”

    Brynjolfsson explained that more experienced workers gain an advantage from on-the-job experience, which AI does not possess and has not yet been able to learn. However, he warned that industries might have difficulty finding the next generation of experienced hires if entry-level workers do not have opportunities to get started.

    Related: Here’s Why Companies Shouldn’t Replace Entry-Level Workers With AI, According to the CEO of Amazon Web Services

    When it comes to employers, Brynjolfsson noted that the way companies view AI affects whether they have open jobs available. Firms that want to use AI to augment their workforce are hiring more human workers, as those who see AI as a replacement for human labor are hiring fewer employees, he stated.

    The study supports another one released earlier this year by SignalFire, a venture capital firm that tracks the job changes of over 650 million people on LinkedIn. In a May report, SignalFire found that big tech companies have reduced entry-level hiring by 25% from 2023 to 2024 while simultaneously increasing hiring of experienced professionals.

    SignalFire’s Head of Research, Asher Bantock, told TechCrunch that there was “convincing evidence” that AI was to blame for the reduction in entry-level hiring, because AI can handle routine tasks well. AI can code, conduct research, and even generate web applications, reducing the need for junior employees to handle those tasks.

    Related: ‘Fully Replacing People’: A Tech Investor Says These Two Professions Should Be the Most Wary of AI Taking Their Jobs

    AI leaders have been warning about the technology’s impact on hiring for months. In June, Nobel Prize winner Geoffrey Hinton, who is often called the “Godfather of AI” due to his pioneering work on AI, predicted that AI “is just going to replace everybody” in white-collar jobs. He said paralegals and call center representatives were most at risk in the immediate present of losing their jobs to AI.

    Meanwhile, Anthropic CEO Dario Amodei stated in May that AI could take over half of all entry-level, white-collar jobs within the next one to five years. The move could cause mass joblessness, resulting in unemployment rising to up to 20%, he predicted.

    AI is cutting into entry-level jobs, according to a new Stanford University study, released on Tuesday.

    Stanford researchers analyzed ADP payroll data, which included monthly payroll information for millions of workers at thousands of companies, to find how AI impacts employment for people ages 22 to 25 compared to other age groups.

    The study found that the professions most exposed to automation with AI were operations managers, accountants, auditors, general managers, software developers, customer service representatives, receptionists, and information clerks. In those AI-impacted jobs, which lost the most entry-level positions to the technology, employment for young workers has declined by 13% over the past three years.

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  • Her Business Helps Women Earn in a $6.3B Industry: ‘Rewarding’ | Entrepreneur

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    Moniqueca Sims, owner of SSG Appliance Academy, got her first glimpse into the appliance repair industry while dating a man who worked in the space. “He worked all the time, seven days a week,” Sims recalls, “so I used to go out with him just to spend time with him. I saw how easy it was for him to repair those appliances, and he was repairing them quickly.”

    Image Credit: Courtesy of SSG Appliance Academy. Moniqueca Sims.

    Sims believes in “working smarter, not harder” and had the idea to hire technicians to help the man she was dating with repair calls. She did, but when he didn’t slow down, she ended up with her own appliance repair company.

    However, in running that business, Sims lost a significant amount of money purchasing parts. Many people she hired didn’t actually know how to repair appliances — and would just switch out part after part in search of a fit.

    Related: After Experiencing the ‘Lack of Diversity’ in Tech, This Software Engineer Started a Business That’s Changing Lives: ‘People Are Waking Up’

    So Sims took matters into her own hands again. She enrolled in an online course to learn about appliance repair and started handling jobs herself, even taking her kids along sometimes.

    “When you fix something, it boosts you up, every time you do it.”

    Still, Sims knew there had to be a better way to train and hire technicians for business growth, so once more she set out to make it happen: She founded SSG Appliance Academy, which provides hands-on training courses on the fundamentals to have a career in the appliance repair industry, in Atlanta in 2019.

    “ I saw how appliance repair was the gift that keeps on giving,” Sims says. “When you go out, when you fix something, it boosts you up, every time you do it. It’s not a grunt job. It’s a feel-good job.”

    When Sims went out on jobs with her daughter, she found that many of the clients were stay-at-home moms who breathed a sigh of relief when they realized they wouldn’t be alone with a male worker. Knowing that, and seeing firsthand what a confidence booster appliance repair could be, Sims committed to bringing more women into the industry.

    The total appliance repair industry revenue reached an estimated $6.3 billion in 2023, yet women make up less than 3% of home appliance repairers, according to data from ConsumerAffairs.

    Related: Raised By an Immigrant Single Mom, She Experienced ‘Culture Shock’ Working at Goldman Sachs. Here’s What She Wants You to Know About ‘Black Capitalism.’

    Sims decided to partner with shelters to grow SSG Appliance Academy and offer a viable career path to the women there. Although there was a lot of interest, the shelters didn’t have the funding to back it. So Sims got approved for grants through the Workforce Innovation and Opportunity Act (WIOA).

    The funding helps low-income, under- or unemployed women and men complete SSG Appliance Academy’s program and “turn their life around,” Sims says.

    SSG Appliance Academy’s classes typically enroll eight to 10 students. The most recent course had three women in it. In the past, Sims often had to attend events and convince women to come to the class; now, word-of-mouth is helping them find it themselves, she says.

    “ You constantly have to prove yourself [as a woman] in this industry.”

    Sims looks forward to seeing even more women take advantage of SSG Appliance Academy, despite the challenges that can come with being a woman in the space.

    “ You constantly have to prove yourself [as a woman] in this industry, and not just to the customers,” Sims says. “You have to prove yourself to everybody that works in the industry.”

    Sims is also excited to see more people across the board jump into the appliance repair industry, noting that learning a trade can help people make more money than they might through earning a four-year college degree.

    “Appliance repair can really help change people’s lives,” the founder says.

    Related: This Black Founder Stayed True to His Triple ‘Win’ Strategy to Build a $1 Billion Business

    “You want to learn your craft from the inside out.”

    To other women interested in starting their own careers or businesses in the appliance repair industry, Sims has some straightforward but essential advice: Enroll in a program that can help you learn all you need to know about the trade.

    “You want to learn your craft from the inside out,” Sims says. “A lot of technicians in the field now learn on the job, so they become part-changers because they don’t learn how to diagnose and troubleshoot the appliances properly. So my advice would definitely be to take a class. It doesn’t have to be my school — any school.”

    Related: I Interviewed 5 Entrepreneurs Generating Up to $20 Million in Revenue a Year — And They All Have the Same Regret About Starting Their Business

    Sims notes that there will be plenty of obstacles along the way, but she encourages anyone interested in learning appliance repair to stay the course — because “it’s a very rewarding career and business.”

    This article is part of our ongoing Women Entrepreneur® series highlighting the stories, challenges and triumphs of running a business as a woman.

    Moniqueca Sims, owner of SSG Appliance Academy, got her first glimpse into the appliance repair industry while dating a man who worked in the space. “He worked all the time, seven days a week,” Sims recalls, “so I used to go out with him just to spend time with him. I saw how easy it was for him to repair those appliances, and he was repairing them quickly.”

    Image Credit: Courtesy of SSG Appliance Academy. Moniqueca Sims.

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  • Is There a Hidden Agenda Behind These New Crypto Laws? | Entrepreneur

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    Opinions expressed by Entrepreneur contributors are their own.

    Recent crypto laws have sparked debate about their true political motivations. The GENIUS Act, signed on July 18, 2025, represents the cornerstone of the administration’s cryptocurrency strategy.

    Officially, the initiative aims to remove excessive administrative barriers and legalize stablecoins – crypto assets backed by real American assets: dollars, treasury bonds or gold.

    According to legislators, these coins should simplify transactions and position the United States as a global leader in digital finance. The administration has framed this legislation as part of a comprehensive strategy to enhance financial innovation while maintaining America’s economic leadership.

    Understanding cryptocurrency laws in the U.S. requires looking beyond official narratives. The stablecoin market, currently valued at over $260 billion, is projected to reach $2 trillion by 2028 under this new regulatory framework. This explosive growth will fundamentally alter the financial landscape in ways that may not align with stated objectives.

    Related: The Hidden Problems That Could Threaten Crypto’s Future

    Who regulates crypto in the U.S.?

    The question of who regulates cryptocurrency in the U.S. is becoming complex under the new legislation. The hidden agenda behind these laws appears to be weakening the Federal Reserve System’s control. As a reminder, the Fed, established in 1913, consists of twelve regional reserve banks and is considered a private structure independent of executive power.

    The prerogative of issuing “national money” is firmly secured by the Fed, and attempts to interfere with its powers have invariably met with strong opposition. Understanding who regulates cryptocurrency in the U.S. reveals the political power struggle behind recent laws.

    The new stablecoin law represents a half-measure, as it cannot solve the task of creating an alternative digital central bank. Instead, it allows private players to issue their own “money” backed by government securities, effectively fragmenting the Fed’s monopoly on emission.

    Read More: People Really Only Care About These 3 Things at Work — Do You Offer Them?

    Stablecoin influence as a tool for political influence

    New stablecoin regulation allows private entities to issue currency-like assets backed by government securities. This represents a significant departure from traditional monetary policy, where currency issuance is tightly controlled by central banking authorities.

    The approach to stablecoin regulation may fragment the Federal Reserve’s monopoly on currency issuance. By allowing private entities to create dollar-backed digital assets, the legislation effectively creates a parallel monetary system that operates under different rules and oversight.

    Critics argue that current stablecoin regulation could create a shadow emission system outside traditional controls. This system could potentially undermine the Fed’s ability to implement monetary policy effectively and respond to economic crises.

    Related: Why Institutional Investors Are Embracing Crypto–TradFi Partnerships

    The political agenda driving recent legislation

    The cryptocurrency political agenda behind recent legislation extends beyond promoting innovation. As a result, the U.S. economic system risks losing part of its budget revenues and deviating from its usual course. Businesses, having received the right to issue and use stablecoins, may begin to evade tax control and the stablecoins themselves, under unfavorable regulation, will depreciate and lose trust.

    To understand the politics around crypto, you have to look at the power struggles between government institutions. Hidden money printing creates slower growth and shaky forecasts, which is risky in an election year when political pressure is already high.

    Some in the crypto space even push for reducing the Federal Reserve’s control over monetary policy — a major change to the financial system that has shaped the U.S. for more than 100 years.

    The potential consequences of these hidden agenda crypto laws include:

    • Budget Revenue Loss: Reduced tax collection from cryptocurrency transactions compared to traditional financial operations.
    • Monetary Policy Fragmentation: Multiple entities issuing dollar-backed assets could complicate coordinated monetary policy.
    • Financial Stability Risks: A parallel financial system with different rules could introduce new systemic risks.
    • Political Power Shifts: Reduction in Federal Reserve independence and increased executive branch influence over monetary policy.
    • Economic Uncertainty: Potential for market volatility and reduced predictability during political transitions.

    Analysts are questioning whether Trump’s crypto ventures are designed to weaken Federal Reserve control. The legislation creates a framework where private entities can issue dollar-backed assets with potentially less oversight than traditional banking institutions.

    The Trump administration has framed its cryptocurrency laws as forward-looking reforms designed to position the U.S. as a leader in digital finance. But beneath that narrative lies a more complex political agenda. The legislation could reduce the Federal Reserve’s influence over monetary policy, introduce alternative currency-like instruments with favorable tax treatment and shift power among key financial institutions.

    Related: This Trillion-Dollar Industry Is Where You Need to Look For Your Next Investment — Here’s Why

    The full impact will only become clear over time. What is certain is that the effects will extend well beyond cryptocurrency markets, with the potential to reshape core elements of America’s financial and political order. The central question is whether these changes will bolster or weaken U.S. economic stability and global leadership. Understanding the implications requires looking past official narratives to the shifting power dynamics they conceal — only then can we judge whether the reforms serve the public good or narrower political aims.

    Recent crypto laws have sparked debate about their true political motivations. The GENIUS Act, signed on July 18, 2025, represents the cornerstone of the administration’s cryptocurrency strategy.

    Officially, the initiative aims to remove excessive administrative barriers and legalize stablecoins – crypto assets backed by real American assets: dollars, treasury bonds or gold.

    According to legislators, these coins should simplify transactions and position the United States as a global leader in digital finance. The administration has framed this legislation as part of a comprehensive strategy to enhance financial innovation while maintaining America’s economic leadership.

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    Vladimir Gorbunov

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  • Trump says he ‘paid zero’ for $11 billion federal stake in Intel. Here’s the downside.

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    President Donald Trump negotiated a deal last week for the U.S. government to take a substantial ownership stake in an American company. Despite his assurances, Trump’s socialistic transaction is a terrible deal not only for the parties involved, but for the entire U.S. economy.

    “It is my Great Honor to report that the United States of America now fully owns and controls 10% of INTEL, a Great American Company that has an even more incredible future,” Trump posted Friday on Truth Social. “The United States paid nothing for these Shares, and the Shares are now valued at approximately $11 Billion Dollars. This is a great Deal for America and, also, a great Deal for INTEL. Building leading edge Semiconductors and Chips, which is what INTEL does, is fundamental to the future of our Nation.”

    “I PAID ZERO FOR INTEL, IT IS WORTH APPROXIMATELY 11 BILLION DOLLARS,” Trump added on Monday. “All goes to the USA. Why are ‘stupid’ people unhappy with that?”

    As of this writing, Intel’s market cap is around $110 billion, so a 10 percent stake would indeed be worth $11 billion. But despite what Trump says, this was not a freebie.

    “Under terms of the agreement, the United States government will make an $8.9 billion investment in Intel common stock,” the company announced. “The government’s equity stake will be funded by the remaining $5.7 billion in grants previously awarded, but not yet paid, to Intel under the U.S. CHIPS and Science Act and $3.2 billion awarded to the company as part of the Secure Enclave program….The $8.9 billion investment is in addition to the $2.2 billion in CHIPS grants Intel has received to date, making for a total investment of $11.1 billion.”

    Intel added that “under the terms of today’s announcement, the government agrees to purchase 433.3 million primary shares of Intel common stock at a price of $20.47 per share, equivalent to a 9.9 percent stake in the company.” According to the Financial Times, that was “below Friday’s closing price of $24.80, but about the level where they traded early in August. Intel’s board had approved the deal, which does not need shareholder approval.”

    The Financial Times added that under the agreement, “the US will also receive a five-year warrant, which allows it to purchase an additional 5 per cent of the group at $20 a share,” but only “if Intel jettisons majority ownership of its foundry business, which makes chips for other companies.” Trump may be expanding state ownership of private industry, but at least he seems to have no interest in seizing the means of production.

    The CHIPS Act grants were approved under Trump’s predecessor, President Joe Biden. Before leaving office, Biden’s administration rushed to finalize many such grants, even as Intel was the worst-performing tech stock in 2024; the government actually agreed to less than initially allocated when the company failed to hit certain milestones.

    Instead of rescinding those grants, as Trump reportedly threatened to do, he instead demanded a tenth of the business, as a result making the U.S. government Intel’s largest shareholder.

    Every part of this transaction flies in the face of any sincere interpretation of free markets, including the Biden administration’s original sin to approve billions of dollars for a struggling company. It is perhaps telling that as Reason‘s Eric Boehm noted last week, the idea that the U.S. government should take a piece of Intel in exchange for CHIPS Act funding was first floated by Sen. Bernie Sanders (I–Vt.). Trump and his allies are now issuing talking points that could have come from the socialist senator himself.

    If the U.S. government insists upon dishing out taxpayer money to private companies, is there any reason it shouldn’t, as U.S. Secretary of Commerce Howard Lutnick put it to CNBC, get “a piece of the action”?

    There are many reasons, in fact. “The most immediate risk is that Intel’s decisions will increasingly be driven by political rather than commercial considerations,” Scott Lincicome of the Cato Institute wrote Sunday in The Washington Post. “With the U.S. government as its largest shareholder, Intel will face constant pressure to align corporate decisions with the goals of whatever political party is in power.”

    Not only that, Lincicome writes, but “Intel’s U.S.-based competitors…might find themselves at a disadvantage when vying for government contracts or subsidies, winning trade or tax relief, or complying with federal regulations. Private capital might in turn flow to Intel (and away from innovation leaders in the semiconductor ecosystem) not for economic reasons but because Uncle Sam now has a thumb on the scale.”

    Such market distortions may seem abstract, but they can have devastating consequences for the American industrial economy. “Will investors and entrepreneurs stay away from critical industries that might also see the U.S. government eager to get more involved?” Lincicome wonders. “Will future presidents, Republican or Democrat, use this noncrisis precedent to carry out their own adventures into corporate ownership with their own economic and social priorities attached?”

    Indeed, White House National Economic Council director Kevin Hassett told CNBC on Monday that he’s “sure at some point there’ll be more transactions, if not in this industry, [then] in other industries.”

    Trump has made several such deals just since reentering office in January. He leaned on Intel competitors Nvidia and AMD to give 15 percent of proceeds from Chinese sales to the government; he demanded veto power over U.S. Steel as part of its sale to the Japanese company Nippon Steel; and MP Minerals, which operates a rare earth mineral mine in the U.S., got a $400 billion government investment that made the Department of Defense its largest shareholder.

    In his Monday morning Truth Social post defending the Intel agreement, Trump said, “I will make deals like that for our Country all day long.”

    But as Lincicome notes, Republicans likely won’t be in power forever; in time, a Democratic president would have the same influence on Intel—and beyond.

    “This is a product of both parties forgetting a cardinal rule of politics: don’t give yourself powers you don’t want your opponents to have,” writes Ryan Young, an economist at the Competitive Enterprise Institute. “The Democrats who passed the CHIPS Act likely did not foresee Republicans using it to essentially nationalize Intel. Similarly, Republicans cheering government takeovers of chipmakers will somehow be surprised if Democrats invoke similar powers in the health insurance, energy, and other industries when they are in power again.”

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    Joe Lancaster

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