The AI Productivity Paradox: Why Working Faster Might Be Burning You Out

You’ve finally mastered your AI coding assistant. Prompts flow naturally, code generates in seconds, and that backlog of features you’ve been putting off? You’re crushing through them at unprecedented speed. There’s just one problem: you’re more exhausted than ever.

The Core Insight

A new study from Berkeley Haas School of Business reveals what many of us have been feeling but couldn’t articulate: AI doesn’t reduce work—it intensifies it. Researchers Aruna Ranganathan and Xingqi Maggie Ye studied 200 employees at a U.S. technology company from April to December 2025, and their findings flip the productivity narrative on its head.

The study uncovered a new work rhythm that emerges when AI enters the picture:

“AI introduced a new rhythm in which workers managed several active threads at once: manually writing code while AI generated an alternative version, running multiple agents in parallel, or reviving long-deferred tasks because AI could ‘handle them’ in the background.”

Workers reported feeling like they had a “partner” that created momentum. But the reality was continuous attention-switching, constant checking of AI outputs, and a growing pile of open tasks. The cognitive load was immense, even as the work felt productive.

Why This Matters

Simon Willison, one of the most thoughtful observers of AI tooling in our industry, captures the personal impact perfectly:

“I’m frequently finding myself with work on two or three projects running parallel. I can get so much done, but after just an hour or two my mental energy for the day feels almost entirely depleted.”

This isn’t just about individual burnout. It’s about a fundamental shift in how we understand sustainable work. For decades, we’ve built intuitions about pacing, focus time, and recovery. AI hasn’t just changed our tools—it’s disrupted our entire framework for knowing when we’re pushing too hard.

Even more concerning: people are losing sleep because the “just one more prompt” dopamine hit is irresistible. The gamification of productivity has found its ultimate form.

Key Takeaways

• Perceived vs. actual productivity diverge wildly. Workers feel more productive with AI while potentially doing unsustainable work
• Parallel execution is a double-edged sword. Running multiple AI tasks simultaneously creates cognitive load that compounds fatigue
• The “partner” illusion is seductive. Having an AI collaborator creates momentum that’s hard to step away from
• Traditional productivity metrics miss the intensity factor. Output per hour doesn’t capture the sustainability dimension
• Organizations need “AI practice” policies. Just like we have meeting hygiene and focus time blocks, we need structured approaches to AI tool usage

Looking Ahead

The HBR piece calls for organizations to build an “AI practice”—structured guidelines for how AI is used to prevent burnout and separate genuine productivity gains from unsustainable intensity.

But I think the solution goes deeper than policy. We need new mental models for what “productive” means in an AI-augmented world. The old heuristics—hours worked, features shipped, PRs merged—don’t account for the hidden intensity cost.

Perhaps the most important skill of the next decade won’t be prompt engineering. It will be knowing when to close the AI window and go for a walk.

The AI productivity tools are incredible. They really can multiply your output. But multiplication applies to exhaustion just as much as to code. We’re going to need new wisdom about sustainable work practices—and we’re going to have to build that wisdom from scratch.

Based on: “AI Doesn’t Reduce Work—It Intensifies It” by Simon Willison