I’ve been watching the “productivity” discourse lately, and frankly, it feels like we’re walking into a trap.
There is this sweeping narrative that Artificial Intelligence is the ultimate cure for “task paralysis”—that crushing, frozen state where you stare at a blinking cursor or a mountain of Jira tickets until your brain just… shuts down. For neurodivergent workers, especially those battling ADHD, the promise is beautiful: AI as a cognitive scaffold, breaking down overwhelming projects into manageable micro-steps.
But after digging through the recent data, I’m not convinced we’re looking at a productivity revolution. I think we’re looking at a looming competency crisis.
The Veneer of Competence
Let’s talk about Gen Z. There is a massive, uncomfortable tension emerging in the workforce. Recent studies show that while nearly 80% of Gen Z workers are heavily dependent on AI, they are scoring poorly on actual AI literacy.
This is what I call the “Veneer of Competence.”
We see young professionals delivering high-quality outputs—perfectly drafted emails, clean code, structured project plans—but there’s a growing suspicion that they don’t actually understand the logic behind the output. They are hitting “generate,” getting the result, and moving on. If you can produce the work without understanding the failure modes of the model you’re using, you aren’t an expert; you’re just an operator.
And here is the kicker: a staggering 40% of Gen Z workers are reportedly engaging in “Shadow AI”—using these tools behind their managers’ backs to automate tasks without any oversight. This isn’t just a governance nightmare; it’s a massive accumulation of technical debt. We are building workflows on top of black boxes that we don’t fully control or understand.
Exoskeletons vs. Prosthetics
I keep coming back to a mental model I’ve developed: the Exoskeleton vs. Prosthetic model.
When we use AI for project management, we have two choices. We can use it as a prosthetic—a replacement for a missing limb or skill. If you use AI to bypass the “struggle phase” of learning how to structure a logic flow or manage a timeline, you are essentially letting your cognitive muscles atrophy. You’re replacing your ability to think with a digital crutch.
Or, we can design AI as an exoskeleton. This is the goal: technology that provides structural support and leverage—handling the data-heavy forecasting and risk assessment—while leaving the core “musculature” of human decision-making and critical verification intact.
The problem? Right now, much of what’s being marketed to combat ADHD or executive dysfunction feels more like a prosthetic. It promises to “conquer overwhelm,” but I worry it might just be replacing one form of distraction with another: prompt engineering fatigue. Instead of fighting the task, you’re fighting the tool.
The Death of the Knowledge Worker
We are witnessing a fundamental structural shift. We are moving away from the era of the “Knowledge Worker” and into the era of the “Orchestration Worker.”
In this new world, “doing” is no longer the primary value driver. The real competitive advantage isn’t being able to write the code or draft the report; it’s the ability to verify the output.
The industry is currently obsessed with building better models, but I think we are ignoring the real crisis: the impending collapse of human-in-the-loop verification capabilities. If an entire generation grows up bypassing the necessary struggle required for deep expertise, who is going to be left to tell when the AI is hallucinating?
My Verdict
AI is a magnificent tool for mitigating the symptoms of executive dysfunction, but we cannot mistake a symptom-masking tool for a cure for professional development.
If you use AI to skip the hard parts of learning, you aren’t becoming more productive; you’re becoming more fragile. The future belongs to those who use AI to amplify their logic, not those who use it to replace it. We need to stop celebrating “output” and start demanding “understanding.”
