The corporate AI adoption hangover is now a boardroom reality: companies worldwide are expected to spend over $2.5 trillion on AI in 2026, a 47% rise on 2025, yet leaders report little measurable business impact and a workforce doing worse work, not better.
The diagnosis comes from a leadership researcher who spent the past year questioning hundreds of executives about their AI strategies. Almost all said they feared falling behind rivals on AI, a dynamic the researcher labels FOMO, fear of missing out. That fear drove the spending. Now, after months of rollouts, the hangover has set in.
Three symptoms of the corporate AI adoption hangover
The researcher identifies three symptoms. First, widespread employee pushback that took leaders by surprise. Second, anxiety over the absence of visible business results. Third, a growing number of staff producing worse work while feeling more overwhelmed, the opposite of what the investment was meant to achieve.
The most common remedy being reached for is to push employees harder to use tools companies have already sunk millions into. The researcher argues this will make the problem worse, not better.
The core mistake, according to the researcher, is treating GenAI as a technology rollout rather than a fundamental change to how people think. Tools such as Co-Pilot, Gemini and Claude have been pitched internally as ways to offload cognitive effort. That framing, the researcher says, is attracting the wrong kind of use from the wrong people.
Poor and average performers (who together make up well more than half of most organisations) are using GenAI to write emails, summarise meetings and build presentations. Their raw output rises, so they assume quality has too. Meanwhile, colleagues on the receiving end are buried under a faster flow of largely average-quality material and reach for AI themselves just to cope.
How one bank’s approach points to a different path
Not every organisation is repeating the same mistakes. DBS Bank‘s chief human resources officer, Yan Hong Lee, banned the word ‘productivity’ in any discussion of GenAI because of its associations with job cuts. Instead, she frames AI adoption around what employees personally gain from it.
According to BriefAsia, more than 70% of DBS employees now use AI tools, collectively generating 1.8 million prompts a month. The bank’s approach appears to have steadied its workforce: The Straits Times reports DBS’s attrition rate in Singapore stands at just 2.8%.
Lee told a recent CHRO breakfast: ‘My main message to my leadership these days is simple: “Can you all please just calm down a little?”‘
The researcher cites the DBS example as evidence that pace matters. Many organisations, driven by a false sense of FOMO, are moving faster than employees can absorb.
Gen Z sentiment data reinforces the concern. Around half of Gen Z workers are using AI, but those feeling hopeful about it fell to 18% from 27% a year ago. A separate study found AI was less popular among workers than ICE, the US Immigration and Customs Enforcement agency.
What leaders should do instead
The researcher sets out three steps. Reposition GenAI not as a tool that thinks for you, but as one that sharpens your thinking. Reduce the threat it represents to workers’ status, autonomy and job security. And make deep thinking easier, including by being explicit about where employees should not use these tools at all, a frontline manager giving feedback, or a salesperson emailing a client, are cited as examples where AI should stay out.
Around 5% of employees with GenAI access, the researcher finds, have worked this out themselves. They use AI to challenge their own ideas and stress-test their reasoning, never sending outputs unread. The argument is that structured training in what the researcher calls ‘Human-First AI Fluency’ could bring that figure to 50% or more.
The researcher’s framework will be set out in full in a forthcoming book, Good with Humans.
