AI tools disproportionately amplify the productivity of top performers, making them exceptional. A manager's highest leverage activity is to focus the majority of their time on unblocking and supporting these individuals to maximize the team's overall output.
Contrary to the impulse to automate busywork, leaders should focus their initial AI efforts on their most critical strategic challenges. Parkinson's Law dictates that low-value tasks will always expand to fill available time. Go straight to the highest-leverage applications to see immediate, significant results.
The next wave of AI productivity won't come from crafting the perfect prompt. Instead, professionals must adopt a manager's mindset: defining outcomes, assembling AI agent teams, providing context, and reviewing their work, transforming everyone into an "agent orchestrator."
As AI tools become operable via plain English, the key skill shifts from technical implementation to effective management. People managers excel at providing context, defining roles, giving feedback, and reporting on performance—all crucial for orchestrating a "team" of AI agents. Their skills will become more valuable than pure AI expertise.
While many believe AI will primarily help average performers become great, LinkedIn's experience shows the opposite. Their top talent were the first and most effective adopters of new AI tools, using them to become even more productive. This suggests AI may amplify existing talent disparities.
Managers often spend disproportionate energy on low-performing employees. The highest-leverage activity is to actively invest in your top performers. Don't just leave them alone because they're doing well; run experiments by giving them bigger, more visible projects to unlock their full potential and create future leaders.
A study identifies a persona of highly effective AI users, “Augmented Strategists,” who achieve the highest net productivity gains. A key differentiator for this group is that they are two times more likely to have received substantial skills training, proving that targeted upskilling is essential for creating valuable AI adopters.
The role of a top engineer is shifting from writing code to orchestrating multiple AI agents simultaneously. Notion's co-founder now queues tasks for AIs to work on while he's away, becoming a manager of AI talent rather than just an individual contributor, dramatically multiplying his leverage.
The true ROI of AI isn't just efficiency; it's the opportunity to reallocate time from low-value tasks to uniquely human activities. Use the bandwidth gained to build deeper client relationships, foster community, and engage in creative work.
AI disproportionately benefits top performers, who use it to amplify their output significantly. This creates a widening skills and productivity gap, leading to workplace tension as "A-players" can increasingly perform tasks previously done by their less-motivated colleagues, which could cause resentment and organizational challenges.
To maximize the effectiveness of 'digital workers,' they must be managed like human employees. This includes regular reviews to check outputs, provide feedback, and offer 'coaching' by connecting them to new information. It's an ongoing process, not a 'set it and forget it' implementation.