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A Trip Down the Rabbit Hole: When AI Productivity Becomes Counter-Productive
- Anna Amoresano
- Sep 17
- 4 min read
Updated: Sep 19
Introduction: Where This Article Began
One morning over coffee, I started thinking about innovation and ideas. Mostly, everyone has ideas. Some are brilliant. Some are brilliant but mistimed, and some should never see the light of day. The world does not need my AI-powered espresso machine that also gives motivational speeches.
I often heard, “no idea is a bad idea.” It’s a polite way to keep meetings moving, but let’s be real: ideas don’t matter until they’re in motion. These days, I run every idea to the AI sandbox. Café, airport, or desk — doesn’t matter. I toss it into an AI prompt and see if it survives. Some implode immediately. Others show a spark. The range is wide — from a disposable video snippet to a SaaS platform worth scaling. The lesson? Momentum doesn’t come from brainstorming; it comes from taking action.
And here’s the kicker: that habit sparked this very article. It got me wondering — when does AI help us move faster, and when does it just drown us in possibilities? When is it productivity, and when is it just… counter-productive?
Here is a great example - I just spent 40 minutes engineering a prompt to create this animation:
The Productivity Paradox
Some individuals are wired to know it all—to be on every loop, to close every knowledge gap. For maximizers or high-certainty seekers, generative AI can feel like a double-edged sword: it offers more— more options, more facts, more angles—precisely what fuels their urge and exactly what overwhelms it. AI promises speed, yet for some it breeds rabbit holes, decision deferral, and creative fatigue—turning a tool into a trap.
Why Certain Personality Types Are Especially Vulnerable
Satisficers are individuals who make decisions by choosing an option that is "good enough" rather than searching for the absolute best possible solution. Psychologist Barry Schwartz famously showed that maximizers — those who strive to evaluate every option — often end up less satisfied and more regretful. In contrast, satisficers move forward with “good enough” decisions and avoid paralysis. AI makes the maximizer’s dilemma worse by surfacing infinite choices.
Intolerance of Uncertainty (IU)
Some people cannot stand “not knowing.” They over-collect information in search of certainty. Yet the more they consume, the more anxious and overwhelmed they become. AI, with its limitless answers, feeds this loop.
Personality and Information-Seeking
Studies on the Big Five personality traits link openness and extraversion with higher information-seeking online, while neuroticism and conscientiousness also play roles. These traits explain why some individuals compulsively chase “more” knowledge, even when it becomes counter-productive.
How AI Turns “More” into Less
Choice Overload → Decision Paralysis
Too many options paralyze decision-making. Research on the “paradox of choice” shows that more alternatives often lead to less satisfaction. AI only accelerates this effect by generating endless possibilities.
Cognitive Load & Fragmentation
While AI automates routine tasks, it introduces new burdens: verifying outputs, filtering noise, switching between contexts. This increases mental strain instead of reducing it.
“Productivity Theatre”
A polished AI draft can feel like progress, but it may not reflect your voice or intent. The result? Endless editing, second-guessing, and tinkering. For perfectionists, this is a rabbit hole disguised as productivity.
Why AI’s Productivity Boost Is Uneven
AI is not a universal accelerant. Research suggests that novices or those doing routine tasks often see large productivity gains. Experienced professionals, however, sometimes experience neutral or even negative effects. And across demographics, adoption is uneven: for example, gender disparities have emerged in academic publishing since generative AI tools became widespread.
The lesson: AI’s benefits depend on context, personality, and how thoughtfully it’s used.
Practical Implications
For leaders and consultants, the takeaway is clear: the value of AI lies not in volume but in discernment. To prevent AI from becoming counter-productive:
Set limits. Define the scope of what you want before prompting AI.
Simplify outputs. Ask for fewer, sharper results rather than an avalanche of options.
Protect your voice. Treat AI drafts as scaffolding, not finished work.
Encourage breaks. Downtime and reflection often spark better ideas than nonstop iteration.
Closing Thought
Ideas without execution are noise. AI can help us explore and refine, but it can also overwhelm. If you take pride in “closing the loop,” your real skill is deciding which ideas to activate. Build virtual buckets, set boundaries, and keep your mental house in order. Too much unmanaged knowledge isn’t power—it’s chaos.
And here’s the irony: this article was one of those unplanned, coffee-fueled ideas. A wandering thought, an AI sandbox, and suddenly… voilà, a blog post. Case in point. Sometimes productivity means running with the right idea at the right time. And sometimes it means laughing at the fact that even writing about counter-productivity can start as a trip down the rabbit hole.
References
Liu, Y., Wu, S., Ruan, M., Chen, S., & Xie, X-Y. (2025). Generative AI makes people more productive—and less motivated. Harvard Business Review.
Dillon, E. W., Jaffe, S., Immorlica, N., & Stanton, C. T. (2025). Shifting work patterns with generative AI. arXiv.
Simkute, A., et al. (2024). Ironies of generative AI: productivity loss in human-AI interactions. arXiv.
Brynjolfsson, E., Li, D., & Raymond, L. (2023). Generative AI at Work. arXiv.
St. Louis Fed. (2025). Impact of generative AI on work productivity. St. Louis Fed On The Economy.
Business Insider. (July 2025). AI coding tools made experienced developers less productive.
TechRadar. (April 2025). The GenAI ‘crutch’: why teams must learn before they lean.
Time. (June 2025). MIT study: AI use diminishes brain engagement and creativity.
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