AI Isn’t Inherently Good or Bad. Leaders Must Decide to Use It Responsibly

AI has rapidly evolved from an emerging innovation to an everyday companion, becoming an integral part of how work gets done. It is already reducing friction in countless tasks, helping people work faster and access information that once required hours of searching. This acceleration boosts productivity, frees up valuable time, and reduces workers’ cognitive load. Thus, it allows them to spend less time on administrative tasks and more time focusing on high-value projects. 

However, AI use also carries risks. Without intention or oversight, it can spread misinformation and encourage intellectual complacency. The temptation to accept outputs at face value can sideline human judgment. Worse still, relying too heavily on AI can lead to what researchers call “cognitive offloading.” These are subtle, often unnoticed changes in our thinking patterns, where the ease of delegation to AI replaces active mental engagement. If left unchecked, this may reduce creativity, critical reasoning skills, and independent thought, and it’s happening faster than anyone could have imagined. 

What recent data reveals 

Recent research from OpenAI and Anthropic provides a more nuanced view of AI adoption than headlines might suggest. Despite the hype around AI transforming the workplace, the majority of ChatGPT use is personal, not professional. According to OpenAI’s study of more than 1.58 million ChatGPT conversations, 70 percent of interactions are non-work related. People are using AI for everything from daily tasks to practical advice. It has become a go-to resource for information unrelated to work. 

OpenAI categorizes AI interactions into three modes: asking—seeking information or advice, doing—producing tangible output like a summary, and expressing—personal reflection or leisure. The study found that workplace use of AI is more targeted, with professionals primarily turning to it for “doing” tasks such as drafting or editing content, coding, and handling administrative work.  

More than half of all work-related prompts focus on generating a specific output rather than seeking insights. Anthropic’s data supports this trend. More than three-quarters of enterprise use of Claude via API is automation-focused. This means organizations use AI to complete tasks from start to finish with minimal human involvement. 

These findings raise an important question for leaders as they plan their AI stacks. Will the tools enhance work or simply help check items off to-do lists faster?  

Doing is more than simply getting things done 

In a culture that prizes productivity, AI can feel like a cheat code. However, speed isn’t the only metric that matters. People seem to recognize this in their personal use of the tool. The study found that “asking” messages were twice as likely to be personal than professional in nature. When users are engaged and invested in the outcome, they see a difference between getting things done and truly doing the work. 

“Doing,” in this context, means staying engaged by thinking through problems and collaborating with others. It’s the kind of work that builds intuition and drives better long-term outcomes. By contrast, handing off tasks to AI without participating may save time now, but it may lead to stagnating skills and weakening strategic thinking muscles. 

Powerful though they may be, AI tools are best used as support rather than authorities. They can help people spot gaps in logic, sharpen perspectives, and interrogate their point of view. Leaders must be mindful of this when building AI roadmaps. If you want teams to build better products or serve customers more effectively, you can’t foster a culture where AI becomes a crutch or where AI investments are made simply to say they have been.  

Instead, you should model what it looks like to partner with AI. Use its output as a starting point for sharper thinking and solving specific problems. As AI becomes integrated into work environments, leaders are responsible to ensure that it enhances, rather than erodes, teams’ ability to reason and grow. That starts with thoughtful governance, outcomes-focused application, and the understanding that the goal should be better, more efficient work—not AI for its own sake. 

Striking the right balance  

Now is the time for leaders to take a clear-eyed look at how AI is truly being used and how to apply it responsibly. The technology—like all others—is not inherently good or bad. It’s a tool, and its impact depends on how we choose to use it. 

AI doesn’t need to be feared, nor should it be blindly celebrated. Like any transformative tool, it calls for balancing excitement, skepticism, experimentation, and caution. The more people rely on AI both personally and professionally, the more important it becomes that they can think critically about the things they see and do. 

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