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  • Podcast: Reimagining payment experiences with agentic AI

    AI, in some capacity, has been used within payments for 30 years. The latest evolution in AI is through the agentic lens — transforming transactions and experiences alike. 

    “We’re actually thinking about really reimagining not one payment, but an entire experience,” Zachary Aron, principal, Deloitte Consulting, tells FinAi News on this episode of “The Buzz” podcast. 

    For example, how can agents be used for travel, business spending or even date nights, he says, noting that you bought the airfare, but do you need to add a hotel or sightseeing package? Agentic AI can facilitate those payments. 

    Listen to “The Buzz” as Aron discusses the possibilities for agentic transactions this year. 

    Register here by Jan. 16 for early-bird pricing for the inaugural FinAi Banking Summit, taking place March 2-3 in Denver. View the full event agenda here. 

    The following is a transcript generated by AI technology that has been lightly edited but still contains errors.

    Whitney McDonald 08:06:01
    Happy New Year and welcome to The Buzz a fin AI news podcast. My name is Whitney McDonald, and I’m the editor of fin AI news. Fin AI news has rebranded from bank automation news, marking the next step in our mission to lead the conversation on innovation and Financial Services Technology. Joining me today, January 6, 2026 is Zachary Aaron, a principal at Deloitte Consulting. Zachary is here to discuss agentic AI’s role in shaping the future of payments. Thanks for joining us.

    Zachary Aron 08:06:27
    Zachary, sounds good. Whitney, thank you very much for having me. Zach Aaron, I am Deloitte global and US banking and capital markets payments leader. I have over 30 years of experience focused on payments overall. And I lead Deloitte practice on payments. We have over 2000 people globally that focus on payments, literally, 24 by seven for all of our clients, which includes everyone from corporates that are thinking about payment acceptance and how payments can help enable their business to the fintechs, to the traditional networks, the banks, and also the central banks and the regulatory areas. So we try to take really a complete view and look of payment around payments, so we can really help advise our clients on how they best can make payments fast, safe, secure, and enable people, individuals and companies, to really be able to best use their money the way that they have intended to do.

    Whitney McDonald 08:07:40
    As you said you’ve got about 30 years under your belt, so I’m excited to have this conversation, especially during a time with AI agentic payments. It’s obviously a lot of change. There’s been a huge evolution just this year. So why don’t we kind of start with the state of agentic AI right now? Where are we today with agentic payments?

    Speaker 1 08:08:02
    Sure, and I’d say maybe even the start. I think payments is one of those really fun areas where people don’t realize that AI has been involved in payments for literally over 30 years. And we, you know, when we look at, you know, payment processors and networks that were actually that have been using artificial intelligence to detect fraud in real time, to be able to look at patterns in real time, so that when a payment came through, they can immediately flag it as a safe or an unsafe payment. And so I’ve always felt that way about cloud. People have said cloud and payments have been around for literally 4040, almost 50 years. And so there’s a little bit of a misnomer in that this is a new concept for the payment space. And so AI has always been a part of it. What’s really happened to your to your point, Whitney, is we really see an evolution no different than, you know, the broader business area and broader technology around Hey, I has evolved from the, you know, the artificial intelligence to analytical. AI, conversational AI, such as your interaction with a chat bot, your ability to use voice to be able to make transactions like paying bills now, all the way to where we are on agentic AI, where we can start to create really true, if you will, agents to be able to accomplish tasks around payments. And so it’s definitely become prominent this year. I think this is the year, and I’ll say it’s an early year. I mean, we’re early in this story. This is the year where we’re starting to lay the foundation around agentic AI. We are starting to think about interesting use cases where this can be applied. We’re also starting to lay out standards. And so what we’re seeing as an example. Or you see the payment networks rolling out standards for how to enable agentic payments. You see some of the technology companies trying to also say, this is how you can execute an agentic transaction from the moment that you want to be able to pay. And so what we’re really seeing is a lot of entities coming in trying to lay the foundation. And I would say we’re sort of going to move to where, you know, how do we enable an agentic transaction probably happens next, and then from there, how we actually reimagine and enable real agentic experiences. And so again, I think we’re really early in this story around the agentic piece, but we’re also very well into the story around artificial intelligence overall and how it’s enabled payments.

    Whitney McDonald 08:10:52
    Yeah, I think that’s really important to note that, you know, AI isn’t necessarily a new player, it’s just we’re kind of getting into this evolution. Where the technology is going, what it’s enabling that is now, you know, new you’ve mentioned here some use cases that you’re starting to see emerge. You talked about the foundation. Obviously, we’re in the early innings of where agentic AI, you know, can go. You have to start somewhere. Let’s talk about what are some of those use cases that you are seeing, Where can this kind of be a reality?

    Speaker 1 08:11:27
    Yeah, and I think what we’re, you know, what we’re seeing right now from players in the space is right now trying to do, what I would say is sort of like 1.0 type payments. In other words, I would like to buy something. How can the agent go out and buy on my behalf? As an example, we’re also seeing examples of, how can the agent help suggest a payment, and so that’s a little bit on the front end. We’re also starting to see how can an agent be there to help immediately detect perhaps a fraudulent payment and provide alerts. Similarly, how can an agent help provide support around payments, enabling disputes, as an example, if you need to contest the payment. And so we’re seeing a little bit of that, which I think is sort of, again, sort of foundational step. We look at a payment, we look at the flow, we look at the interaction. We go, where can an agent do this job better? What we are finding, though, is, you know, thinking further afield is, how do you really reimagine something? And so one of the things as an example that we’re looking at, and to use, sort of a possible example is say it’s, you know, it’s a Friday night, and you realize, like, oh, it’s date night for me and my spouse. And you know what, I just I have not given it enough thought, and I need to plan a really cool date night for my spouse. So I really want to go to movies, and I want to be able to go to dinner, and I want to be able to kind of, you know, maybe it’d be great to have, like, you know, get some flowers at the, you know, to start the date off, and and all those sort of things. And now, the way I would do that today is, right. I’m going to go on, I’m going to call up the restaurant, or I’m going to go on an app and see if they have space, or I’m going to try to look at a variety of restaurants, and I’m going to look at their different ratings that they have. Similarly, I got to go and I got to, you know, pull up and look at, you know, what movies are available and the like. And now I got to figure out how the timing of all of it works, right? So now I’ve got to do 6789, 10 things. I kind of throw up my hands, I close my eyes, I take a guess, maybe I did, well, maybe I didn’t, on my date night. Or I have to go, sorry, it’s not dinner and a movie, you know, how about we order pizza and, you know, you know, watch, watch something on the couch, which I probably failed on, on that, on that assignment. So yet I’m going to try to figure this out. But now maybe I’m going to go to say a search engine, or I’m going to use an app, and I’m actually going to say I need ideas for a date night that involve dinner in a movie, ideally Italian, ideally a rom com. I also want to make sure that there’s enough time from when the dinner ends to when the movie begins that I can also get the popcorn and the Raisinets, which, by the way, is a phenomenal combination put together, you know, a couple of sodas. And also, by the way, it’d be really cool if we could maybe stop at the ice cream parlor on the way back. And also, by the way, it’d be great if I could get, you know, a dozen roses. And now an agentic agent is going to say, let me do some work. You should actually go to this restaurant. They have a seat available at 6pm you can then have an hour and a half dinner, and you’ll be able to make the 8pm showing of the latest great rom com out there. And we’re going to get you seats, by the way, if you know you want the popcorn and raisin nets, we can get that pre ordered for you. You know, what do you want to drive or do you want to get a ride share? And I start adding that in. They’re like, How much money do you want to spend? And I’ll go, You know what? You know, I have the best spouse on Earth. Money’s no object. Get the best seats, right? All those sort of things.

    Unknown Speaker 08:15:38
    Get two boxes of raisin nets,

    Speaker 1 08:15:40
    exactly, right? We’re going to double up on the raisin nets. In fact, no budget, right there. You know what? There is absolutely no budget when it comes to good popcorn and raisin nets and gummy bears, to be honest. And it’s like, hey, you know, by the way, to maximize your time at the restaurant. Do you kind of know, is there a favorite dish that you have? Do you want to, you know, pre order a bottle of wine and have that ready? Or, you know what it’s gonna let’s have fun. Get the champagne. All right, we’ll even send that request for the champagne. So now what the agent has done is it suggested an experience. Now let’s move it to payments. I have potentially a payment for the car service, for the restaurant, for the movie theater, for the tickets and the concession I still have to, you know, and maybe even you know, the ice cream place at the end, imagine now this experience says, Do you want to pay for this stuff now? And that way, also you’re not fumbling around. You’re also maybe not even thinking about, Oh, well, Shoot, maybe money wasn’t no object, or whatever the case may be, as things went around, you’re like, you know what? That would be great. And I can show up. We’ll be at home. The car service comes. I just get out of the car. I walk into the restaurant. The wine’s already there. We’ve eaten, right? I maybe, you know, go back on my app and said, Yeah, I had the lasagna, and, you know, my spouse had the scampi. Great, done. I walk in the popcorn and raisin nets are right there. And there the tickets were printed out. I go get the double box of the rate of the raisin nets and the popcorn, little extra butter too. And then, you know, the seats are there, the car is there. Right when the movie ends, it takes us to the ice cream we got in before it was over. They already had the rocky road ready to go, and then takes us home. And I maybe never reached for my wallet and it said everything was paid for. Or even at the end, it said, here’s the total for everything. Are you good? And you’re like, yeah, by the way, I like to tip these people some stuff. You do it, you’re done. And when we think about that agentic AI experience, we have made payments invisible and easy, and we’ve taken that challenge out. It’s going to split the payments out to the movie theater, to the restaurant, the ice cream people, the car people. And I’ve basically been able to have an easier experience, easier to find, easier to pay, and I’ve really been able to enjoy my date. And so when we think about the agentic AI experience that’s coming up. We’re actually thinking about really reimagining not one payment, but an entire experience. So you think about that. You can now think about all sorts of things, travel as an example. You think about businesses. And you think about just even how businesses have to procure supplies and all the different things. And now you could have an agent that just says, Hey, we’re nearing the end of the month. You’ve got to, you know, this is normally the time you want to replenish. I looked at your cash flow. This is what that looks like. How about, you know, we pay these invoices this way. Place these orders. This is where you’re going to get the better vendor discount on supplies. You know, if you wait another week, you can get this deal. And all of a sudden, we’re stringing together multiple transactions into one thing. We’ve created time savings. We’ve created safety as well, and we’ve created the ability to customize the way those payments work and those transactions work for the way that that individual or that business really wants to operate.

    Whitney McDonald 08:19:33
    Now, to go back just a little bit here, because obviously, like the the sound of all of that is, you know, it’s promising and it’s exciting, and you don’t want to have to worry about, you know? Okay, now we’ll go through the payments process at all of these different, you know, when you’re talking about the date, all of these different places, the restaurant, the theater, wherever you are, let’s kind of talk about the reality of getting there. You talked a little bit about the foundation and how we’re kind of laying the foundation in 2025 let’s talk about the things that need to go into that foundation to ensure that you know, if you’re enabling this type of experience, that you do have accountability, liability, trust, that you have all of those pieces in place in order to enable you know, The magical date experience, what what needs to be? What do you need to think about? What do you talk to your clients about?

    Speaker 1 08:20:27
    Yeah, the great, great question, Whitney and you actually, I mean, I think you actually really know that, like this is the number. Like the number, everyone goes, Okay, love the idea. How do we make it happen? Because one of the things that we now need to be able to do is, when you are bringing in, if you will, the agent that is fundamentally making these suggestions and enabling these transactions, you need to do a couple of things. One is be able to and they to have that person have control over that agent. I need. Be able to have the choices around everything from my budget to the vendors or the merchants that I want to be able to do, to be able to spend, to frequent. Pardon me, you know, I can see I want to be able to have preferences what I like and don’t like, I want to be able to authorize, maybe up to a certain limit, or the ability to say I want to change that in the middle of the flow. So I need to be able to give a level of personal control. That’s one piece. The second piece is within the infrastructural aspect, because now what you need to be able to have is participate. You know, ultimately, at the end of the day, you’re enabling payment transactions, which means you’re asking banks to essentially say valid person sending the transaction, someone saying, I could this is a valid receipt of a transaction. And now this is a valid agent, and this is an agent that should have been doing what it was doing, that was doing it in accordance to how I wanted that, that transaction to occur. And so you need to be able to create that ability to say, I have a valid agent, and it’s a valid transaction. The third thing that you need to be able to do is, in order is to be have all that is, you need to look at your operational aspects around how you support those transactions, so that when they do happen, if I come back later and say, Uh oh, that no, no, no, I got overcharged. I didn’t have five boxes of Raisinets. I had two right? How do I make that change? And people are able to look at that and say, Yes, that was the movie theater concession transaction. These other transactions were good in that chain. This is the one that they’re disputing. And how do I appropriately handle that? And similarly, I want to be able to see each and every one of those transactions if I look at it on my app or my statement, whatever the case may be. And so it actually involves securing the entire chain, from all the way to the front end, all the way through to how you authorize, settle and support and service that transaction, as well as adding in that additional level to ensure we have true agent to agent validation as well.

    Whitney McDonald 08:23:35
    Yeah, it kind of changes the authentication process. Who are you authenticating? Obviously, we’re all familiar with, you know, the biometrics or two factor authentication. Now you’re, you’re validating or authenticating agents that they should be making these decisions or, you know, approving these transactions. And obviously, with the guidelines or the guardrails that you mentioned to up to a certain amount, things like that are definitely important. But, yeah, those are all questions that that definitely come up when it when it comes to, you know, liability, you know, who’s responsible for these transactions?

    Speaker 1 08:24:13
    Well, you know you’re absolutely right. And, I mean, we did, we did some research, and exactly to your point, number, top two concerns. So, so the good news, if you will, is when we talk about these things, and we, you know, we surveyed consumers on the on, you know, on their preferences. We also surveyed businesses, and you have a majority, greater than 50% on both consumers and businesses that says, I want to try this. That being said, the flip side of that equation is when you list that, where are going to be the concerns around how you would use this to drive a good amount of the way that you make your your paying decisions. 58% said, Look, security, data, privacy hacking, number one concern. 57% almost the exact same amount, also said incorrect decisions that were being made. And so the other aspect to what you’ve said, and this is why we’re sort of doing this in this step function way, is as much as we want to roll out the great date, you know, Agent right now is you have to ensure trust, and that’s the number one thing, and that means prove that you can do a transaction in a trustworthy way, prove that you’re going to keep people’s data secure, prove that you’re not going to the agent Isn’t now going to run amok on what I’m doing or or, I think the other thing that we’re hearing is start to overly suggest things, and it turns from an agent that’s acting on my behalf to an agent that’s acting on someone else’s behalf and all like, and it’s now basically spamming me with, Hey, do you want to go on an. Their date over and over and over again, and you know? And that’s not what I want. And so the thing we talk to our clients about is create that level of security, focus on doing the basics right, but also design it so that it is acting in the best interest of the end user, and if you’re not, if you’re not doing it that way, then your level of adoption and your margin for error becomes extremely low.

    Whitney McDonald 08:26:34
    Now let’s kind of talk about 2026 here. We talked about 2025 what, where we kind of stood, what was, what conversations were had between, you know, you and clients. Now, 2026 what could be tangible experiences? Do you think we’re going to get to the, you know, the great date? Or do you, do you think it’ll still continue to kind of be like a pump, the brake, slow roll, maybe a hybrid of that. What’s your expectation for the year? Likely a hybrid

    Speaker 1 08:27:08
    and, and, and, I think the you know, I think we’re going to see some, some really interesting things be, be, be offered out there. It may not be the great date, but it may be certain things that perhaps are linked purchases around a common topic, such as, you know, as an example, travel might very well be an interesting one, where you kind of, you know, you think about things that are commonly linked. You bought the airfare. Do you need a hotel? You bought a trip? Do you want to add a sightseeing package? Things of that nature? I think we’re going to look at what I would say is more tightly connected, coupled transactions that are going to be there, are going to be brought out there. There’s still a lot of work. And I think we’re going to see that kind of hybrid attempts kind of come as people will really want to test right the efficacy and the safety of the agents. I also think, you know, we talk a lot about the things that we can experience every single day. I would be remiss. I think we’re going to see a lot of movement on the infrastructure side with agents. I think we’re going to see that on servicing. And I think we’re definitely going to see that on fraud. And I think we’re going to see a lot of, how do we ensure that, you know, agent to agent transactions are going to be safe and secure. And so I think we’re going to see a little, a lot of that, you know, if you will, the stuff you don’t see the middle, back office side of payments happen on the agentic side. And I think you’re going to see a couple of these hybrid rollouts, and then maybe we’ll get to the great date agent as well.

    Whitney McDonald 08:28:51
    You’ve been listening to the buzz a fin AI news podcast. Please follow us on x and LinkedIn, and as a reminder, you can read this podcast on your platform of choice. Please be sure to visit us at finaI news.com. For more finaI News, thanks for listening. You.

    Transcribed by https://otter.ai

    Whitney McDonald

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  • Deloitte: Banks need overarching vision for AI adoption

    Banks in the United States are continuing their investment in AI, which will have both short- and long-term effects on their efficiency ratios.  Publicly held banks are expected to experience a slight increase in their average efficiency ratio — from 56.3% in 2025 to 56.9% in 2026 and 57.1% in 2027, according to Deloitte’s 2026 […]

    Vaidik Trivedi

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  • Small Businesses Aren’t Seeing the Same AI Gains as Big Corporations. Here’s Why

    Companies of all sizes and sectors are moving swiftly to boost productivity by integrating artificial intelligence applications to automate tasks previously performed by employees. But recent reports clash significantly in calculating AI’s effects on humans, while also diverging on whether larger corporations seem to benefit from AI more than smaller businesses.

    In the end, the difference in those analyses appears to be opinions about how fast and far AI should go in replacing humans in a given workplace, and how beneficial machines taking over from employees is to the results sought in using the tech.

    The first of those inquiries came from Wells Fargo chief equity strategist Ohsung Kwon, who compared changes in revenue generated per each worker on the staffs of big S&P 500 firms. He then made the same calculation for companies on the small-cap Russell 2000 index.

    Using the 2022 release of OpenAI’s ChatGPT AI bot as the starting point, Kwon’s team determined that the increased scaling abilities of larger corporations allowed them to benefit from the tech’s automating capabilities to boost the output—and with it, revenue—of workers they employed. During the same period, by contrast, it found productivity in the modest-size businesses fell.

    ″While productivity for the S&P 500 has soared 5.5 [percent] since ChatGPT, it’s down 12.3 [percent] for the Russell 2000,” Kwon wrote in a recent note to clients that was featured in a CNBC report on the differing results of AI adoption in business. “We see other examples of diverging trends in consumer, industrial, and financial markets.”

    But much like today’s big news that Amazon is laying off 14,000 corporate employees as it expands its use of AI across the business, Kwon’s measurement of productivity gains appears to depend mainly on human workers losing their jobs to the tech. Even if overall output remains the same or even dips following tech-driven head count reductions, the lower number of total workers—and payroll savings added back into the bottom line—mechanically boosts per employee claims of revenue generated.

    In addition to Amazon, the CNBC report lists big companies—including Meta, UPS, Starbucks, Oracle, Microsoft, and Google—that have announced big staff cuts this year. Those were undertaken to streamline their structures, but primarily to make way for use of AI to automate many of the tasks eliminated that employees previously performed.

    That willingness of big companies to sacrifice employees, cut labor costs, and boost revenue by scaling their use of AI appears to explain why they’ve benefited more from the tech than small-business owners under Kwon’s analysis. After all, even entrepreneurs responsive to investor demands for increasing returns tend to be more hesitant about laying off people they’re often working in close contact with than corporate managers.

    Any aversion to company founders cutting staff as an integral part of AI adoption may well also explain another of Kwon’s findings. While the S&P 500 rose 74 percent since use of AI took off in 2022, the Russell 2000 increased by just 39 percent—probably reflecting investor views about where the biggest, fastest potential boosts to share prices are.

    Still, none of that means smaller companies are holding back on introducing the tech to their workplaces or missing out on the productivity gains it can offer.

    A recent survey of small-business owners in the U.S., Australia, Canada, and the U.K. by Intuit QuickBooks Small Business Insights found nearly 70 percent of respondents used AI on a daily basis, with 75 percent reporting increased productivity as a result. Around 15 percent of participants said adoption of the tech had allowed them to create jobs, with only 5 percent saying they’d cut head counts instead.

    Results of a recent study by business consultancy Deloitte also measured successful adoption of AI in ways other than merely reducing head counts and costs. Its Humans x Machines report argues that both big corporations and small businesses that focus primarily on the tech rather than the employees who use it end up with disappointing results.

    Its survey found that nearly 60 percent of responding companies that deployed AI first and asked workplace questions about its use and effectiveness later are 1.6 times more likely to report lower return on their investment than other businesses.

    Companies with the best outcomes, the report said, are organizations that allowed human relations and other managers to work with staff to identify the most useful kinds of AI applications, train workers to adopt them, and then encourage continued deployment of those tools across the business. The report concluded that the tech will never meet its effectiveness potential unless business leaders prepare employees to enable that beforehand.

    “[M]ost organizations are investing heavily in AI, but not enough in the work design needed to unlock its value,” said Deloitte U.S. human capital head of research and chief futurist David Mallon in comments about the study. “This shouldn’t be an ‘either/or’ approach—it should be a ‘both/and’ strategy to maximize value. Organizations that take a technology-first approach struggle to scale, while those that intentionally design roles, workflows, and decision-making to integrate humans and machines are more likely to exceed their ROI expectations.”

    Bruce Crumley

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  • Ready or not, enterprises are betting on AI | TechCrunch

    This has been a big week for AI companies signing enterprise deals, with Zendesk unveiling new AI agents that are supposed to be able to resolve 80% of customer service issues, Anthropic and IBM announcing a strategic partnership, and Deloitte also announcing a deal with Anthropic. Plus, Google announced a new AI-for-business platform.

    That doesn’t mean it’s going to be smooth sailing for big organizations using AI. In fact, the timing of the Deloitte announcement was a bit awkward, coming on the same day the Australia Department of Employment and Workplace Relations said the professional services and consulting firm would have to pay a refund for delivering a report to the department with what appeared to be a number of AI-generated hallucinations.

    On the latest episode of the Equity podcast, Kirsten Korosec, Sean O’Kane, and I discussed the latest AI headlines, contrasting it with last week’s news about the new Sora app. While AI companies may eventually make real money from consumer social networking apps, enterprise deals offer a more immediate path to significant revenue.

    You can read a preview of our conversation, edited for length and clarity, below.

    Anthony: I think this actually ties back to our discussion last week about some of these GenAI social networks. We were framing that as potentially a way that these AI companies could eventually make money, which I definitely think is the case, but there’s a long road to get there. And the enterprise, sometimes people don’t find it quite as interesting or sexy as consumer, [but] it’s actually where the real money is. 

    Maybe Sora is how OpenAI will make money five years from now, but this is how these companies are going to make money now.

    And the Deloitte [news] was especially striking. Sometimes you can feel like a little bit of a broken record to just point out how these models [aren’t always] totally ready for prime time, but I find it encouraging that the Australian government actually pushed back and said, no, you cannot do this.

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    It’s not necessarily that no one should ever use AI in the creation of these kinds of reports, although I think you could make that argument. But if you’re going to do it, you actually have to be responsible for the outputs. You have to actually go through and make sure that the information being cited is real. You can’t feed it into a model and just [say] “All right, my job is done, that’ll be however many billable hours.” I think anyone who does that should be embarrassed and fined.

    Kirsten: Absolutely. Sean, Zendesk also had an announcement this week, and they’re really creating these tools that are going to handle pretty much all of customer service, basically removing the human from that process. In your everyday [life], how you go about the world or how automakers deal with service, for instance, are you starting to see that kind of [automation] creep in?

    Sean: Yeah, I’ve actually written about it a few times. There are a bunch of different startups that are developing full customer service suites, voice agents, LLMs for emails and texts [from] dealerships and service centers. I actually think that’s a worthy idea, because the problem there isn’t: We don’t have enough people for the jobs to do this stuff and it’s going to take their jobs away. It’s that you can never get somebody on the phone or you get bounced around. 

    Especially going for service, you get bounced to the service department. Everybody’s busy. So if you can capture it accurately and make it easier for people to get a response, the question there for me is how much will those businesses adopt it and stick with it. There’s been all sorts of technologies over the years, like web forms and things like that, where these dealerships have done it, but then they forget about it. And then it just sits on their website and you think that it’s going to work, and then it doesn’t work, because they just want you to call them. 

    So I have some optimism and some hope that stuff like this is actually gonna be people’s first touch point with [a business]. And it looks like we’re about to find out.

    Equity is TechCrunch’s flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday.

    Subscribe to us on Apple Podcasts, Overcast, Spotify, and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

    Anthony Ha

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  • Why Deloitte is betting big on AI despite a $10M refund | TechCrunch

    AI companies are making their much-anticipated enterprise plays, but the results are wildly inconsistent. Just this week, Deloitte announced it’s rolling out Anthropic’s Claude to all 500,000 employees. On the very same day, the Australian government forced Deloitte to refund a contract because their AI-generated report was riddled with fake citations. It’s a perfect snapshot of where we are: companies racing to adopt AI tools before they’ve figured out how to use them responsibly. 

    On this episode of Equity, Kirsten Korosec, Anthony Ha, and Sean O’Kane dig into the messy reality of AI in the workplace, plus funding news and regulatory drama across tech and transportation. 

    Listen to the full episode to hear more news from the week, including: 

    • Zendesk’s claim that its new AI agents can handle 80% of customer service tickets autonomously, and what happens in the other 20% 

    Equity is TechCrunch’s flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday.  

    Subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

    Theresa Loconsolo

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  • Deloitte was caught using AI in $290,000 report to help the Australian government crack down on welfare after a researcher flagged hallucinations | Fortune

    Deloitte’s member firm in Australia will pay the government a partial refund for a $290,000 report that contained alleged AI-generated errors, including references to non-existent academic research papers and a fabricated quote from a federal court judgment. 

    The report was originally published on the Australian government’s Department of Employment and Workplace Relations website in July. A revised version was quietly published on Friday after Sydney University researcher of health and welfare law Chris Rudge said he alerted media outlets that the report was “full of fabricated references.”

    Deloitte reviewed the 237-page report and “confirmed some footnotes and references were incorrect,” the department said in a statement Tuesday.

    Deloitte did not immediately respond to Fortune’s request for comment.

    The revised version of the report includes a disclosure that a generative AI language system, Azure OpenAI, was used in its creation. It also removes the fabricated quotes attributed to a federal court judge and references to nonexistent reports attributed to law and software engineering experts. Deloitte noted in a “Report Update” section that the updated version, dated September 26, replaced the report published in July. 

    “The updates made in no way impact or affect the substantive content, findings and recommendations in the report,” Deloitte wrote.

    In late August the Australian Financial Review first reported that the document contained multiple errors, citing Rudge as the researcher who identified the apparent AI-generated inaccuracies. 

    Rudge discovered the report’s mistakes when he read a portion incorrectly stating Lisa Burton Crawford, a Sydney University professor of public and constitutional law, had authored a non-existent book with a title outside her field of expertise.

    “I instantaneously knew it was either hallucinated by AI or the world’s best kept secret because I’d never heard of the book and it sounded preposterous,” Rudge told The Associated Press on Tuesday. 

    The Big Four consulting firms and global management firms such as McKinsey have invested hundreds of millions of dollars into AI initiatives to develop proprietary models and increase efficiency. In September, Deloitte said it would invest $3 billion in generative AI development through fiscal year 2030. 

    Anthropic also announced a Deloitte partnership on Monday that includes making Claude available to more than 470,000 Deloitte professionals.

    In June, the UK Financial Reporting Council, an accountancy regulator, warned that the Big Four firms were failing to monitor how AI and automated technologies affected the quality of their audits. 

    Though the firm will refund its last payment installment to the Australian government, Senator Barbara Pocock, the Australian Greens party’s spokesperson on the public sector, said Deloitte should refund the entire $290,000.

    Deloitte “misused AI and used it very inappropriately: misquoted a judge, used references that are non-existent,” Pocock told Australian Broadcasting Corp. “I mean, the kinds of things that a first-year university student would be in deep trouble for.”“The matter has been resolved directly with the client,” a spokesperson from Deloitte Australia told TheAssociated Press.

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    Nino Paoli

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  • How Economic Uncertainty is Sapping Executives’ Confidence

    Critics of President Donald Trump’s trade war, mass deportations, and other contested policies have repeatedly warned the measures risked provoking renewed inflation, economic contraction, and mass job losses. While most of those dire predictions have —thankfully — not yet come to pass, U.S. executives are increasingly anxious about their companies and professional futures amid continued uncertainty all the same.

    Three different studies reflect growing concern among top managers about their personal and professional stakes in today’s uncertain business and economic environment. The broadest of those studies in scope was consultancy Deloitte’s latest quarterly poll of chief financial officers (CFO). While it found that the general confidence level of respondents rose slightly in September compared to earlier this year, it noted its 5.7-point reading “remains in medium territory… (and) is well below the 6.4 mark registered at the beginning of the year.” Other results included only 65 percent of participants saying the current economic situation is not safe to take risks in, and just 15 percent described the economy itself as “good.” 

    Among the top threats to business cited by participating executives were inflation, high interest rates, faltering economic growth, and supply chain disruptions from tariffs. But even if those didn’t prevent the confidence index of CFOs creeping up a little in Deloitte’s survey, even that mediocre outlook appeared strong compared to those captured by consultancy Korn Ferry in its recent poll of CEOs and board members.

    Its polling found 63 percent of top company officials said risks to their businesses had increased more rapidly over the past year. Meanwhile, just 11 percent of respondents said they felt fully confident about their organization’s ability to successfully navigate those multiplying challenges. The leading worries voiced by participants were minimal early returns on artificial intelligence investments, a shortage of qualified candidates to fill job openings, and internal resistance by existing staff to policy or cultural change.

    Another concern, focused on an aspect of the increased economic volatility observed since Trump came to office, was executives’ recognition that those risks are spread unevenly across various business sectors. Around 86 percent of leaders of consumer businesses said that growing unpredictability was a major concern, topping all other categories. Second most exposed to the rising uncertainty were industrial companies, with 83 percent calling it a big problem.

    “Many leaders are challenged to navigate so many forces simultaneously,” said Tierney Remick, head of Korn Ferry Services. “We’re seeing uneasiness — especially among long-tenured CEOs who have weathered decades of change but now face a convergence of risks unlike anything before.”

    A third survey, by workforce management platform Kahoot!, found uncertainty rising on a more personal level among the 221 human relations and training professionals polled. It found most responding managers feeling the same disengagement also reported by growing numbers of employees across U.S. workplaces over the past year.

    Nearly 80 percent of participating C-suite executives said that while their teams appear to view them as “fully engaged” in their work, only 47 percent said they actually were all-in and energized on the job. Over a third of respondents reported feeling burned out daily or several times during the week, with 22 percent saying they’ve often or always felt disconnected from teams they work with over the past six months.

    That psychological and emotional disconnect has consequences on two important levels.

    First, it led 46 percent of participating managers to say they’d be willing to give up their executive titles if that would allow them to feel engaged again. Another 26 percent confided that they’d considered quitting in the past year in order to stop feeling so adrift on the job.

    Meanwhile, with recent Gallup data showing only 31 percent of all employees saying they felt engaged at work, the risk of already slackening workplace energy and enthusiasm waning even more increases further as more managers overseeing staff similarly withdraw.

    But Kahoot! CEO Eilert Hanoa noted that as troubling as that development among top managers is, there are ways for companies to remedy the problem.

    “If leaders are ready to trade away their title for the chance to feel engaged, it signals something profound,” said Hanoa in comments about the findings. “Leaders are telling us loud and clear that recognition, training and connection matter more than status. Engagement cannot be a side project. If engagement fails at the top, it fails everywhere. The companies that respond will not only retain their leaders but unlock the energy of entire teams.”

    How do businesses effectively react? By showing executives the same attention, consideration, and support that lower-level employees say they need.

    When asked what would boost their engagement most, 69 percent of executives answering the survey cited more recognition and incentives from their companies, followed by 57 percent who said greater connection between teams would help. Nearly 45 percent said simply introducing more competition or gamification exercises at work would be beneficial — with 58 percent predicting that initiative alone would would result in increased energy, creativity, and fun on the job.

    Over half of respondents also getting more training to build their skills would strengthen their engagement. That’s a desire that a nearly 80 percent of lower-level employees have increasingly expressed, especially Gen Zers who place a premium on professional and personal growth.

    Meaning, there are many relatively easy ways employers can start addressing and reversing declining workforce engagement — awaiting the return of improved macroeconomic conditions capable of curing the broader doubts many companies now face at all levels of staff hierarchy amid today’s uncertainty.

    Bruce Crumley

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  • Aha moments, the ‘first ten hours’, and other pro tips from business leaders building AI-ready workforces | Fortune

    As businesses face pressure to bring new AI tools on board, they have the dual challenge of effectively incorporating the technology into their operations and of helping their workforce make the best use of the technology. 

    Longstanding methods for assessing the skills and performance of an employee, as well as hiring practices, are being upended and re-imagined, according to business leaders who spoke at the Fortune Brainstorm Tech conference on Tuesday in Park City, Utah. 

    Technical skills, contrary to what you might think, are not paramount in the age of AI. In fact, for many employers, technical skills are becoming less important.

    “For the first time this summer on our platform we saw a shift,” said Hayden Brown, CEO of Upwork, an online jobs marketplace for freelancers. In the past, when Upwork asked employers on its platform about the most important skills they were hiring for, the answer invariably involved deep expertise in certain technical areas, Brown said. “For the first time this summer, it’s now soft skills. It’s human skills; it’s things like problem solving, judgement, creativity, taste.” 

    Jim Rowan, the head of AI at consulting firm Deloitte, which sponsored the Brainstorm discussion, said an employee’s “fluency” should not be an end goal in itself. More important is intellectual curiosity around new tools and technology.

    And that’s something that needs to start at the top.

    “We’ve done a lot of work with executive teams to make sure the top levels of the organization and the boards are actually familiar with AI,” said Rowan. “That helps because then they can communicate better with their teams and see what they’re doing.” 

    For Toni Vanwinkle, VP of Digital Employee Experience at Adobe, it’s critical for employees at all levels of an organization to have an “aha moment” with AI technology. And the best way to bring that about is for each employee to get their “first ten hours” in. 

    “Go play with it,” Vanwinkle says. “Sort your email box, take the notes in your meeting, create a marketing campaign, whatever it is that you do.” Through that initial process of personal exploration, you start to understand the potential of the technology, she says.

    The next step, Vanwinkle says, is collaboration, discussions, and experimentation among colleagues within the same departments or functionalities.

    “This whole spirit of experiment, learn fast. That twitch muscle can turn into something of value when people talk openly,” Vanwinkle says.

    The importance of embracing experimentation, and fostering it as a value within the organization, was echoed by Indeed chief information officer Anthony Moisant.

    “I think about the pilots we run, most of them fail. And I’m not embarrassed at all to say that,” Moisant says. It all comes down to what a particular organization is optimizing for, and in the case of Indeed, Moisant says, “what we go for is fast twitch muscle. Can we move faster?”

    By encouraging more low stakes experiments with AI, companies can gain valuable insights and experience that employees can leverage quickly when it counts. “The only way to move faster is to take a few bets early on, without real long term strategic ROI,” says Moisant.

    Workday Vice President of AI Kathy Pham emphasizes that with new tools like AI, getting a full picture of an employee’s value and performance may take a bit longer than some people are used to. “Part of the measurement is better understanding what the return is and over what period of time,” she said.

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    Alexei Oreskovic

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  • Elon Musk’s xAI Faces High Exec Turnover as CFO and Key Leaders Step Down

    Elon Musk’s A.I. firm is best known for its Grok chatbot. Photo by Jared Siskin/Patrick McMullan via Getty Images

    Mike Liberatore, chief financial officer of Elon Musk’s xAI, has left the company after just three months, the Wall Street Journal first reported. His exit adds to a wave of high-profile turnover at the startup. Launched by Musk in 2023, xAI is best known for its Grok chatbot. The company’s technology has quickly caught up to competitors, but Grok has also made headlines for controversial outputs and now for a string of executive departures.

    Liberatore joined xAI in April after eight years at Airbnb, where he was vice president of finance and corporate development. He also previously worked at PayPal and eBay. At xAI, he was reportedly involved in fundraising and oversaw data center expansion efforts in Memphis, Tenn. Liberatore left in July, according to the Journal.

    Around the same time, Raghu Rao, xAI’s former commercial lead, also departed. Rao had joined in April following roles at Zoom, Ernst & Young and Deloitte.

    Another loss came this summer when Robert Keele, a member of xAI’s legal team, stepped away from his role as general counsel. “Working with Elon on this tech, at this time, was the adventure of a lifetime,” Keele wrote in an Aug. 5 X post. He said he was leaving to spend more time with his family. His farewell included a Grok-generated video of a man in a suit shoveling coal, which Keele said was the chatbot’s response to the prompt: “What’s it like to lead legal at xAI?”

    Musk built xAI in just a few years with a founding team largely drawn from OpenAI and Google. Of the dozen co-founders, at least three have since left. Kyle Kosic is now at OpenAI, while Christian Szegedy became chief scientist at Morph Labs. Both departed last year.

    The most recent co-founder to exit was Igor Babushkin, who led engineering teams at the firm before leaving in August to launch his own venture capital firm focused on A.I. startups and agentic systems. “We wouldn’t be here without you,” said Musk in an Aug. 13 post responding to Babushkin’s announcement.

    Not every departure has been as cordial. Last month, xAI filed a lawsuit against Xuechen Li, a former member of xAI’s technical team, accusing him of stealing trade secrets to take to a new role at OpenAI. Li, who joined xAI in February 2024 and helped develop Grok, allegedly uploaded confidential data before accepting an offer from OpenAI in August. On Sept. 3, xAI won a court order temporarily blocking Li from starting the new job.

    Elon Musk’s xAI Faces High Exec Turnover as CFO and Key Leaders Step Down

    Alexandra Tremayne-Pengelly

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  • Americans pinched as electricity costs hit all-time highs

    Americans pinched as electricity costs hit all-time highs

    Electricity rates in the U.S. soared to all-time highs in September, with Americans facing the sting of higher energy bills.

    The Bureau of Labor Statistics reported a spike to $0.171 per kilowatt-hour in September, presenting a harsh reality against the backdrop of a seemingly robust economy. While costs moderated to $0.169 per kilowatt-hour in October, industry experts point to a web of causes including geopolitical tensions, global pandemics, and green energy transitions which indicate that the days of stable, low-cost electricity might be fading and a new reality may be emerging.

    As households gear up for winter, there’s cautious optimism for a slight respite in electricity costs. A recent downtick in natural gas prices—a key determinant of electricity rates—hints at a potential but modest decrease in upcoming electric bills.

    Newsweek’s previous analysis of Energy Information Administration (EIA) data indicates that while a 2 percent reduction in residential electricity rates is projected, stemming from a 14 percent year-over-year drop in wholesale natural gas prices, consumers should still brace for relatively high energy expenses.

    That’s because the complexity of the energy market means that lower fuel costs don’t always equate to lower electricity rates for consumers, according to experts. Deloitte’s 2024 power and utility industry outlook analysis paints a picture of an industry grappling with the costs of modernizing the grid and transitioning to green energy, pointing to a 1.9 percent overall increase in retail electricity prices by the end of the year.

    The Federal Reserve’s warning of a ‘higher for longer’ interest rate environment aimed at curbing inflation resonates within the energy sector. Capital expenditures have surged to a record-breaking nearly $171 billion in 2023 for the most significant electric and gas utilities, according to Deloitte, indicating a trend that may not reverse soon.

    As interest rates climb, the cost of borrowing increases, which can ripple through the economy, affecting utilities and, by extension, electricity rates.

    These higher borrowing costs come at a time when utilities are investing heavily to modernize and transition towards more sustainable energy sources, meaning a return to prices that electricity enjoyed over the 2010s may not happen anytime soon because “much of the increase over time is due to inflation and has often lagged inflation,” Jim Thomson, U.S. Power, Utilities & Renewables leader at Deloitte Consulting, explained to Newsweek.

    That lag indicates that while consumers may be feeling the immediate sting of higher prices, the energy sector and the utility companies that monetize it might be contending with the rising costs for a longer period. Thomson said that in the short term, “utilities will likely continue to face high costs as they modernize and decarbonize the electric grid.”

    Why Did Costs Increase in the First Place?

    The decade-long stability of electricity prices that consumers enjoyed for years was upended in 2022 when a confluence of factors caused the price spike. A surge in natural gas prices, fueled by lower production and amplified by geopolitical tensions stemming from the Russian invasion of Ukraine, played a key role, Thomson told Newsweek. Additionally, Thomson said the energy sector was not insulated from the pandemic’s inflationary effects and supply chain disruptions, which drove up costs.

    Will I Have High Electric Bills Forever?

    There is light at the end of the tunnel. “Some of these factors are subsiding,” Thomson explained, “and since regulated utilities are required to pass cost decreases through to customers as well as cost increases, some customers could see lower bills in the coming year.”

    The U.S. Power Utilities & Renewables leader told Newsweek that as the industry increasingly turns to renewable sources like wind and solar, which are not fuel-reliant, the potential for moderating costs emerges. “Over time, as the share of electricity generated by renewables such as wind and solar continues to grow, it could tend to moderate costs since those energy sources do not use fuel, and those savings would be passed on to customers,” he noted.

    He remains optimistic about the long-term impact of renewable energy, adding, “As the energy transition progresses, households that electrify their energy use by replacing fossil-fueled cars, heating systems, and other appliances with EVs, heat pumps and electric appliances could potentially see as much as a 40 percent decrease in household energy bills by 2045.”

    A young lady sits at her kitchen table at home checking over the household bills. Experts say that high energy costs may be the new norm as the industry grapples with the costs of modernizing the grid.
    In Pictures Ltd./Corbis via Getty Images