What if AI isn’t changing work nearly as much as it’s exposing the parts of work we never understood?

For centuries, we’ve believed that better rules would lead to better work, where productivity could be engineered and human unpredictability could be streamlined into neat workflows. GenAI arrived as the latest expression of that faith, promising faster operations and smarter decisions, in theory. But as organizations began putting AI into practice, reality exposed how mistaken our assumptions were about what makes “work” actually work.   
 

Like Alice stepping through the looking glass, the deeper we move into this new world, the more the once-familiar logic of work begins to warp. Some of our most confident predictions about AI turned out to be mirages, and our attempts to compress messy reality into clean lines of code only threw the human complexity we once mistook for corporate inefficiency into sharper relief.

The Alice in Wonderland stories offer a useful lens to understand this specific moment, capturing the universal feeling of realizing the rules you trusted no longer explain the world you’re in. The deeper Alice falls, up becomes down, big becomes small, and meaning unravels the moment she tries to pin it down. AI is provoking a similar reckoning in the workplace, overturning assumptions about how we work, why we work, and who we are when the autonomy and competence that shape our professional identities have suddenly become negotiable.  
 

Below are three of the most compelling contradictions we found in our research, How to Win Mindshare in the GenAI Race  

Hedonic Entropy: The Diminishing Returns Of Productivity Gains (And Why Motivation Is The Only True Multiplier)
 

Our first finding overturns a basic assumption about GenAI. We tend to believe people turn to AI only for the tasks they dread yet the data show something more revealing: people who use AI are 25% more likely to use it more for the tasks they already enjoy. This finding suggests a deeper truth: even the most advanced tools can’t push humans toward tasks they fundamentally resist. AI can remove friction, but it can’t manufacture motivation, the real bottleneck of modern work. 
 

This is Hedonic Entropy: automate the tasks people dislike and productivity only rises to a point. Efficiency has a short emotional half-life; we’re wired to acclimate to ease, which means every efficiency gain quickly dissolves into expectation. But deepen the work they enjoy and broaden the surface area of their curiosity, the upside of GenAI becomes infinite.  
 

Efficiency may open the door, but curiosity is what pulls people through it—just as it pulls Alice deeper into Wonderland. Alice’s journey begins with a spark of interest, not an urge to escape. Likewise, curiosity (not efficiency) may be the real engine of GenAI adoption. 
 

The Enterprise Adoption Lesson: If the ceiling on AI adoption is human motivation and not technical capability, leaders need to design AI initiatives around what makes work more meaningful, not just more efficient. 
 

The B2B Advertising Lesson: If you’re selling AI, resist positioning it as a tool of relief. Efficiency messaging hits a ceiling; possibility messaging scales. Creative that helps people see new possibilities inside their work is far more motivating than creative that simply promises to make their to-do list shorter. 
 

The Optimist’s Dread: When The AI Opportunity Feels Like A Ticking Clock

Our second finding disrupts another familiar narrative: the people most afraid of being replaced by AI aren’t the Pessimists—it’s the Optimists who are 15% more likely to be concerned. They’re the White Rabbits of the workplace: the ones who see the emerging terrain most clearly and therefore feel the stakes most acutely. Their optimism lets them see the possibilities AI could unlock, but it also makes it impossible to ignore the futures where those gains don’t include them. And like the White Rabbit, who rushes through Wonderland under the constant threat of execution, they understand just how unforgiving a system can be when it decides you’re no longer needed. 
 

That clarity shapes their behavior. They’re always glancing at the clock, convinced that if they can just run fast enough, they’ll stay ahead of the madness because speed feels like the only moat in the age of AI. To pause is to risk falling permanently behind. “I’m late!” becomes “I’m falling behind.” 
 

The Enterprise Adoption Lesson: If AI feels like an arms race, leaders must slow the narrative long enough to show where people still belong in the future.
 

The B2B Advertising Lesson: If you’re selling AI, you need to understand the fear that sits beneath people’s optimism; otherwise, your creative could accidentally trigger it. The job of good AI messaging isn’t just to avoid provoking fear (audiences can sense when a message glosses over the human cost and can decode subtext faster than any model) but to communicate in a way that reinforces human value and agency. Because if you don’t provide that meaning, they’ll write their own version of the story, and it won’t favor your brand.
 

The High Performer’s Trap: When The Mimicry Of Mastery Erodes Your Edge
 

Our third finding exposes the paradox of mastery: High Performers are 25% more likely to over-reliance on AI than Lower Performers. Intuitively, you’d expect High Performers to have the least to fear—after all, they’re the ones with the strongest skills, the deepest instincts, the people who supposedly need GenAI least. And you’d expect Lower Performers to over-rely on AI, precisely because they have more gaps to fill. But the findings suggest that High Performers aren’t comforted by their advantage; they’re more attuned to how quickly GenAI can erode it.
 

High Performers are Alice on the mushroom, staring down the Caterpillar’s unnerving question: “Who are you?” Top performers have the most to lose when GenAI destabilizes the old scarcity model of mastery—the instincts, edge, and craftsmanship that once set them apart are now the very things GenAI can convincingly mimic, at least in a world where most people aren’t equipped to spot the difference.
 

In Wonderland, Alice’s usual forms of competence lose their footing; her manners, logic, and confidence no longer map cleanly onto the world around her. The Caterpillar forces this reckoning yet offers no answers, only the cryptic instruction that one side of the mushroom will make her grow and the other will make her shrink. What she becomes next is up to her. It’s the moment in the story where ability and identity fall out of sync, and she must decide who she is without the markers that once made her feel capable.
 

GenAI confronts High Performers with the same provocation the Caterpillar offered Alice: Who are you when the rules of work change? It’s too early for anyone to offer definitive answers, but the corporate mandate toward metamorphosis waits for no one. Like Alice, we all must decide what we’ll grow into, what we’ll shed, and who we’ll become when the old markers of mastery no longer hold.
 

The Enterprise Adoption Lesson: When AI threatens the traditional markers of mastery, leaders must create new ones that reward judgment, taste, and human insight.
 

The B2B Advertising Lesson: If GenAI threatens the surface-level markers of mastery and leaves the human core exposed, now is the time for brands to remind people who they are beneath the performance. If High Performers recognize the risk of our world sliding into the Turing Trap, where mimicry eclipses real mastery, the brands that champion the human core will earn the deepest trust. In that spirit, AI is best positioned not as a replacement for expertise but as its cocoon, a space where human capability evolves rather than becomes obsolete.

GenAI moves professionals through a familiar Wonderland arc: curiosity pulls us in, fear speeds us up, and identity forces us to choose a direction. But not everyone successfully emerges from it. Alice keeps evolving while the Mad Hatter stays trapped in his endless tea party, that’s all motion but no progress, all activity but no outcomes. Too much of the corporate GenAI rollout resembles this, where superficial, ceremonial activity that looks like progress yields nothing beneath the surface.
 

If we want to evolve, and not just orbit around the gesture of progress, brands must frame AI not as an escape from the chaos, but as the way to navigate through it. The winners will champion real expertise over convincing mimicry and cast AI as a space where capability grows, not where it gets erased. We can’t escape Wonderland, but we can wake up from it. And the brands that help people do that will lead the next chapter.
 

To learn more about the B2B Institute’s 2026 Trends for the Contrarian Marketer, please visit our website or reach out to your LinkedIn sales representative.  

Source: LinkedIn B2Bi Sponsored 2025 Global GenAI CEP Research Study in Partnership with EBI (US: n=408)