1 hour ago
2
Companies in 2026 are expected to spend over $2.5 trillion on AI, a 47% increase on 2025. This is a spending spree never seen before in the history of organizational investments, and it’s driven in part by companies giving all employees access to GenAI tools such as Co-Pilot, Gemini, or Claude.
Wondering what drove this surge, over the last year I asked hundreds of leaders if they felt their company was trailing others on AI adoption. Their nearly unanimously positive response confirmed my hunch: Organizations have been living through a bad case of FOMO (the fear of missing out). In this case, a universal fear of competitors getting a jump on them, both on innovation and on perceived cost savings, seemed to be driving their spending.
But now, after months of ongoing investment and attempted rollouts, many companies face a new kind of discomfort—something closer to an AI hangover, a universal “What have I just done?” moment.
The hangover has three main symptoms. First, surprise at the intensity of pushback against AI. Second, anxiety about how little business impact they can see. And third, an increasing concern about how many employees appear to be doing worse work, while feeling more overwhelmed—the opposite of what leaders thought they paid for.
The most common go-to solution for this hangover? Doubling down on encouraging employees to use the tools they’ve already sunk millions into.
As someone who makes a living studying how our brains show up at work, this is a terrible idea. Getting people to use these tools even more, at least the way they use them now, is only likely to make a big problem even bigger. That’s because companies have the wrong mental model for this moment. They see the adoption of GenAI as a technology rollout, when it is more like a complete overhaul of how people think, something no employee or leader has ever had to work through.
Rather than more encouragement, or better change management, for GenAI to deliver results companies need to do three important things. Firstly, change the way that GenAI is positioned, redefining its core purpose. Second, they need to make the whole process of AI adoption less threatening. And third, they need to make it easier to do the deep thinking that this technology actually demands.
How AI sets a thinking trap
GenAI has been pitched as a tool to save you having to think. Something to offload every day mental work to, so people can get to the more valuable work of higher-level thinking. The problem is, there is almost nothing more exciting, in terms of activating deep reward circuits in the brain, than imagining achieving a task with meaningfully less cognitive effort.
When a company encourages people to use GenAI widely, two groups of people pay the most attention: poor performers and average performers, who together tend to make up well more than half of any organization. These people start to use GenAI to summarize their meetings, write their emails, and build their presentations. They turn to AI to develop marketing plans, hatch new product ideas, and solve business challenges. Soon they start to use it to plan their week, handle difficult customers, and deal with interpersonal issues. Their raw output goes up, so they think the quality of their work does, too.
These people have no idea they are doing anything wrong. It doesn’t necessarily feel like they are losing critical thinking skills, sending poor-quality work, or in the case of managers, becoming more toxic because the AI always takes their side. They are just doing what their company asked them to do.
Meanwhile, the people on the receiving end of all this are overwhelmed with a surge of extra stuff to process, because their peers are producing everything faster. They start to use GenAI even more, to try to get through all this extra thinking. Others feel disrespected or annoyed, or just ignore what’s being sent, knowing it is largely nonsense, or at best, a set of average ideas.
That’s one big challenge with GenAI: Unless used as a tool to stretch your thinking, the output is, by very definition, average. People are anchoring on the hallucination problem. The real issue is most outputs of GenAI should never be used “as-is.” But that’s not how it is being pitched inside our companies.
Shift the narrative
Instead of GenAI being a tool to think for you, it needs to be positioned as a tool to improve your thinking, to help you think more widely, more deeply, more creatively or more thoroughly. Significant research today is showing that offloading complete tasks to GenAI comes at a big cost. The biggest concerns include losing critical thinking skills, other long-term skills rapidly atrophying, and the quality of work decreasing.
Another reason we need to change the narrative? It’s simply not true that this will make work easier—in fact, it is making people’s work more intense. Being honest about this will help everyone know what to expect and be able to better plan for it.
Some researchers are calling this kind of solution ‘human in the loop’. We think it should be more “human in the lead”. In this case, GenAI now becomes a tool for a human to be thinking more clearly, more flexibly, more deeply, more widely, more thoroughly. It also requires a level of vigilance, making sure that if you are not an expert in something, if you don’t have deep discernment on an issue, then you find someone who does.
Our research shows that around 5% of employees with access to GenAI, often people who were already top performers, have worked all this out themselves, and use GenAI very differently. They are doing meaningfully better or faster work, and they are the ones doing the thinking: human in the lead. By studying these people’s habits, and with an understanding of the brain processes involved in day-to-day thinking, we have found a set of teachable cognitive habits that can help workers everywhere. We call this “Human-First AI Fluency.”
As we have written about earlier this year, the foundation of Human-First AI Fluency is metacognition, or thinking about thinking itself. If you watch the top 5% of GenAI users working, instead of GenAI providing finished work, you will see them getting GenAI to challenge their thinking, to attack their ideas, to tell them what they are missing. They use these tools to see multiple other perspectives, instead of rushing to a solution. And they almost never send out anything just produced by an AI.
Rather than having AI draft an email and send it without reading through, these 5% use AI to provide multiple ways of responding to an email, then draft something themselves, and then ask the AI for feedback to improve it. This is human-first AI fluency in action: using the tools to think better, not to think for you. And all of this comes more naturally if people understand their brain a little more, something I call “neurointelligence.”
It’s time to shift the narrative. GenAI isn’t a technology to roll out. And it’s not even a way of reimagining work. It’s a whole new way of thinking. Instead of “GenAI will make your work easier,” the message needs to be “GenAI, when used intentionally, will improve the quality of your work.” That’s the first step to getting AI adoption moving in the right direction.
Reduce the threat
While leaders were expecting younger populations to lead the charge, a study showed that while around half of Gen Z are using AI, those feeling hopeful about it dropped to 18% from 27% a year ago. Another study showed AI was less popular than ICE (the U.S. Immigration and Customs Enforcement agency). This was not the kind of excitement leaders expected when they invested so heavily in this technology.
For some, the resistance is environmental. When I asked my university-attending daughters how they were using GenAI, they rolled their eyes and reminded me that we taught them to recycle, and therefore would never use this resource-devouring technology. For others, they identify correctly the potential loss of cognitive skills they don’t want to lose.
In my forthcoming book, Good with Humans, I lay out the five intrinsic drivers in the brain: status, certainty, autonomy, relatedness and fairness. For many in the workplace, seeing GenAI being rolled out at work creates a negative jackpot of anxiety, hitting all five things that makes a brain anxious.
Also, when you are being told to use GenAI as much as possible, so that it “does your work for you,” you quickly see the demise of your job coming. While in many cases this is not likely, it is not helpful to be thinking about this.
Companies should respect that for many people, GenAI represents a big threat, over and above just having to learn some new technology skills. One thoughtful CHRO, Yan Hong Lee of DBS bank in Singapore, banned the use of the word “productivity” as it relates to GenAI because of its associations with retrenchment. Instead, she focuses on the “What’s in it for me?” for all stakeholders.
Other things companies can do involve going at a more realistic pace. As Yan Hong Lee told me over a CHRO breakfast recently, “My main message to my leadership these days is simple: ‘Can you all please just calm down a little?'” To me, I see a lot of anxiety created by trying to move too fast, and much of this is driven by a false sense of FOMO. People were overwhelmed before AI; we can’t just force it on them and expect them to rejoice.
Make hard thinking easier
The final step for leaders to roll out GenAI more effectively is to make hard thinking easier. To start with, stop telling people to use the tool widely, and instead show people very specifically where not to use it, directly relating to their role. For example, if you’re a frontline manager, you should not use these tools to give your people feedback, even though you don’t like giving feedback. And if you are in sales, never ever send a client an AI-written email.
Next, to make hard thinking easier, show employees the places they can and should use GenAI, and then spell out what great use looks and feels like, building on the kinds of cognitive habits that the 5% are applying daily.
With this approach, we believe that the 5% can become 50% or more. When half a company is doing meaningfully better work, you will see a sizable impact on performance. Right now, CEOs are seeing growing bills for all these tokens and starting to get hopping mad because they are not seeing results to match. Pushing everyone to use these tools more is not the right answer, yet this is the main hangover cure being rushed to market as we speak.
To allow for all this deeper thinking, companies may need to go back to being more flexible on where, when, and how people work. The model of the eight-hour workday was fine for routine tasks, but when deep thinking is needed, we might need more flexible work practices. Our best thinking is more likely after a long walk than a long meeting.
Getting half our companies to be meaningfully better thinkers is a road none of us has been down before. Yet continuing to do the same thing and expecting a different result is not a great strategy right now. We’ve had the FOMO, and now we have the hangover. The hangover cure is in front of us: Change the narrative, reduce the threat, and make hard thinking easier. Now we just need the stomach to swallow it down and digest it in full.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
This story was originally featured on Fortune.com
