From AI High to AI Burnout: The Intrinsic Motivation Trap

GenAI is boosting productivity but draining the spark that makes work feel meaningful. Here’s what leaders need to understand before the energy runs out.

A funny thing happens when the machine starts thinking for us.

You crank out a polished performance review in minutes. Your emails sound like they were written by someone with perfect emotional intelligence and unlimited time. You finish a project that used to take days… in an afternoon.

It feels great. Until it doesn’t.

Because the moment you return to a task without AI—budget planning, goal setting, mentoring a team member, you feel it: the drag. The boredom. The lack of spark. What used to feel meaningful now feels like a slog.

That’s not just in your head. It’s real. And new research published by Harvard Business Review spells it out.

What the HBR Research Found

In four studies with over 3,500 participants, researchers asked professionals to complete real-world tasks like writing emails and brainstorming ideas with and without GenAI assistance.

The results were clear:

• Productivity jumped. AI-assisted work was faster, more polished, and more engaging.

• But motivation dropped. After using AI, people reported an 11% decline in intrinsic motivation and a 20% increase in boredom when switching to unaided tasks.

  
  

The very tool that made them feel efficient left them feeling empty when the next task didn’t involve AI.

This test was on individuals but should concern CEOs and other leaders who are implementing AI in their organizations. Intrinsic motivation is among the most important factors in keeping people engaged in work and predicting whether they will be innovative and creative. Without it, employees may do their jobs but their heart is not in it. While the AI is great for writing emails and automating semi-rote tasks, it is not nearly as effective in tasks that require judgement and non-linear thinking.

In other words, AI is phenomenal but if it induces what I call “AI Burnout”, then the long-term effects may undermine the ability of your employees and your company to grow and innovate.

Source: HBR – Gen AI Makes People More Productive—and Less Motivated

Why the AI High Doesn’t Last

Generative AI removes friction. No blank page. No bottlenecks. No overthinking. But friction is often where meaning lives. When AI handles the hard parts, we lose the challenge that made the work rewarding in the first place. We become spectators to our own output.

And when we return to solo work?

It’s like stepping out of a high-performance car and pushing a shopping cart uphill.

We’ve Seen Disruption Before — But Never at This Speed

Every few decades, a technology paradigm shift rewrites the rules of work. Not just what we do, but how it feels to do it and how businesses deliver value.

For example:

• Cloud computing severed our tie to the machine room. With a few lines of code, anyone could deploy at scale. But with abstraction came distance. The joy of building gave way to the stress of orchestrating invisible systems.

• Mobile computing promised freedom. But the office followed us home. What began as flexibility blurred into always-on fatigue.

• SaaS democratized powerful tools, but at the cost of uniqueness. When every team runs the same stack, differentiation gets harder. We configure, but we don’t create. We move faster, but everything starts to look the same.

Each of these waves increased technology leverage and reduced friction. Except friction isn’t always bad. Friction gives us grip. Texture. The satisfying resistance that makes results feel earned.

Then came GenAI, and it moved faster than anything before. The numbers don’t lie:

As of June 2025, ChatGPT has approximately 474 million unique monthly users on its standalone platforms (website and app), with an additional 65.5 million users accessing ChatGPT via Microsoft Copilot, totaling 521 million unique monthly users when combined. Multiple sources report ChatGPT has 400 million to 474 million weekly active users as of early to mid-2025. ChatGPT.com receives about 5.19 billion visits per month as of March 2025. Combined with Copilot, total monthly visits reach approximately 5.3 billion

And make no mistake — most of the people in your organization are using Gen AI tools to do their jobs, in one way or another. They are too good to ignore for low-hanging fruit like writing emails, doing basic research on topics, or summarizing documents and meeting transcripts.

But there is a critical difference between GenAI and other technology paradigm shifts. This time, the shift isn’t just technical. It’s psychological.

We’re not just changing tools. We’re changing what we expect from work and how progress feels. We have always chased more speed and shorter wait times, but Gen AI compresses the amount of work and thought required to nearly zero.

Instant outputs bring instant gratification. But when the magic isn’t available on the next task? We get annoyed, just like when we have to wait for a slow data connection. The drop-off in our interest, attention and motivation is real. We are spoiled by speed.

And that’s the real challenge. It’s not just keeping up with the technology. It’s keeping people engaged through it and continuing to support and foster the parts of human talent that are more intangible yet even more critical than ever before.

What This Means for Leaders

The real risk isn’t laziness, it’s disengagement and lack of innovation and motivation. As it stands now:

• People do the work.

• They use the tools.

• But the spark fades.

The result? Burnout disguised as productivity. Fast outputs with flat energy. Technically competent teams that feel emotionally disconnected. And, frankly, outputs that feel like they are generated by AI — even if they aren’t. Going through the motions literally means just that. Take away the heart and the spark, and the end result is a paint-by-numbers version of productivity, with teams that no longer ask “Why?” or “Is there a better way?”

Teams start hitting deadlines, but stop asking harder questions.

They ship the work on time but lose the emotional connection to why it matters, and they lose the understanding of what makes great work different and unique. When it happens, it can be hard to spot. But over time, it manifests in higher turnover, fewer discussions about ideas, and individuals and teams moving away from risks, defaulting to what the LLM told them is the best average answer.

Because LLMs predict based on the average, too, the questions they ask and the answers they provide match a pattern and will always remain average. That may work for an email thread, but it fails miserably for efforts to, say, launch a new product that has never been tried before or for screening non-traditional hires for new and unusual roles.

My Take for CEOs, Boards, and Leadership

I’ve lived through more than a few technology waves, each one promising to “free us up” to do higher-value work. I’ve built teams through client-server, cloud, mobile, and now AI. Each wave came with the same promise: more leverage, less grind. And each time, we underestimated how that shift would feel to the people doing the work.

In some ways, the promise was delivered. But Gen AI is different.

• It doesn’t just change how we work.

• It doesn’t just change the pace.

• It changes the experience.

The dopamine hits are real. So is the disorientation that follows. It changes how it feels to work. We get high but we are getting high on our own supply and don’t have an antidote when we crash back to Earth.

Reality check. We’re entering an era where AI may do 80% of the job. That’s a gift and a threat. Because if we’re not careful, we’ll design teams that look productive on the surface… but feel hollow underneath because they stop caring about the 20% that matters and are no longer able to psychologically handle “slow-burn” tasks.

Discovery will take a back seat to Perplexity.

Leaders now face a choice: treat AI as a way to do the same work faster, or use it as a forcing function to rethink how we work, ensuring that human judgment, storytelling and creative problem solving remain at core of what truly drives progress..

It doesn’t have to be this way.

Here are a few experiments you could try to combat AI Burnout.

• Mandate a “What Did the AI Miss?” Slide

For every presentation or proposal assisted by GenAI, include a slide listing 3 things the model didn’t see. This forces deep review and critical sensemaking.

• Require a “Human Theory of the Case”

For any major deliverable that uses GenAI, ask: “What would your human instinct have done differently?” Add it as a required section in decks and strategy docs.

• Install “Creative Detours” in Product Workflows

Insist on at least one unconventional experiment in every roadmap cycle—even if it’s likely to fail. Track and reward the exploratory intent, not just the outcome.

• Use ‘Narrative Debt’ as a Red Flag

When teams can’t clearly explain why they made key decisions, mark that as “narrative debt.” Track it like technical debt. If it piles up, it’s a signal of lost meaning.

• Add a ‘First Principles’ Layer to Approvals

For strategy or hiring plans, require one paragraph explaining the first-principles thinking behind the decision—no GenAI assistance allowed.

• Bring Back “Founder’s Voice” Memos

Ask senior leaders or project leads to write freeform internal memos in their own words, explaining why a project matters. Make this a norm before launches.

• Track ‘Non-AI Originated Ideas’

In retros and pitch meetings, highlight which ideas began with human insight vs. tool output. Over time, analyze what type of value each source creates.

• Make Space for Face-to-Face

In-person moments are harder to scale, but they are also harder to replace. When used intentionally, they rekindle connection, spark richer debate, and help teams re-arch to a shared purpose. Not everything needs a whiteboard, but some breakthroughs still happen best around one.

Final Thought: Reclaim the Spark

The real opportunity isn’t to eliminate human friction.

It’s to elevate human potential and encourage us to spend more time focusing on what humans are good at. These suggestions can help us retain and regain that focus.

Let AI be the accelerant. But let the hard parts, the creative sparks, the strategic pivots, and the leadership calls still belong to us.

That shift doesn’t happen by default. It takes intentional design:

• Small rituals that reinforce what matters (like asking “What did the AI miss?” during team reviews)

• New norms that reward exploration over efficiency (like tracking non-AI-originated ideas)

• Leaders must actively set the expectation that work should be purposeful, thoughtful, and rooted in human judgment, not just fast, efficient, or AI-generated.

Get that right, and the payoff isn’t just better metrics. It's more energized teams. And in an AI-saturated world, energy might be the most undervalued competitive advantage we have.

Preserve that, and we won’t just be building faster teams. We'll be building more fulfilled ones–aligned, inventive and ready for what comes next.