The bozos effect

One person plus AI equals a two-person team. Harvard proved it with 776 employees at P&G. I've started calling what happens next "the bozos effect." I see it with almost every client now. Give someone AI tools and within a few weeks they're quietly wondering why they need the rest of the team.

It's not imaginary. A Harvard University/GitHub study found developers with Copilot shifted toward solo coding and away from collaboration. Not because anyone told them to, but because they could.

When AI lowers the cost of doing it yourself, asking a colleague feels like friction.

Every individual metric looks great.

People are faster.

Output is up.

Dashboards are glowing.

But the bottleneck just moved.

One person generates work faster, but approvals still take three days. Alignment meetings still eat the calendar. The handoff to the next team is still a mess. A system only moves as fast as its slowest link—and AI didn't speed up any of the links that require other humans.

The bozos effect feels like efficiency.

But it's actually your team quietly unlearning how to collaborate.

Coordination muscles atrophy.

Knowledge stops crossing silos.

And when something genuinely hard shows up—the kind of problem that needs three perspectives and a whiteboard—nobody remembers how to do that anymore.

But there’s a ray of hope: That same Procter & Gamble study found AI-augmented teams were 3x more likely to produce top-decile breakthrough solutions.

One person plus AI gets you to "good."

A team plus AI gets you to "new."

If you're seeing the bozos effect in your org, I'd love to hear how you're thinking about it. It's one of the thorniest problems I'm working on with clients right now.

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Sources: "The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise," Dell'Acqua et al, March 2025 (kinda old, I know)

"Generative AI and Distributed Work: Evidence from Open Source Software," Hoffmann et al, July 2024 (yes, hella old, but I see findings still play out in teams)