Businesses can get a more accurate view of internal capabilities by using AI to analyze objective data from platforms like GitHub and Jira. This approach bypasses unreliable employee self-assessments to infer true skill proficiencies and can even flag when critical knowledge is concentrated in too few people.

AI can provide more consistent and objective management than the bottom 50% of human managers, who often bring personal biases and emotional issues into their roles. This challenges the default assumption that human management is always superior.

An AI agent with access to work product can serve as an impartial manager. It can analyze performance quantitatively, like a sports coach reviewing game tape, and deliver feedback without the human biases, office politics, or emotional friction that complicates traditional performance reviews.

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.

A powerful and safe use of AI for managers is not to generate performance reviews, which can feel impersonal, but to perform 'agentic search.' The AI can pull context from code, Slack, and documents to highlight employee wins and contributions that a manager might otherwise miss, especially as individual output increases.

To evaluate candidates, run the same case study through an AI agent like Claude. This creates an objective performance floor; if a human candidate cannot outperform the AI's output, they fail to meet the minimum standard for the role, providing a practical filter in the hiring process.

Instead of pausing junior hiring due to AI, Cloudflare's CEO argues for the opposite strategy. He suggests inserting new graduates directly into legacy teams to act as catalysts for adopting new AI tools and workflows from the ground up.

When applied to culture, AI's primary strength isn't automating HR tasks or replacing human judgment. Instead, it excels at pattern recognition and contextual reasoning at scale. It analyzes vast amounts of nuanced, qualitative employee feedback to identify deep-seated issues that traditional quantitative surveys miss.

AI can analyze past employee data to predict future tenure, identifying non-obvious correlations that humans miss in spreadsheets. It can surface patterns related to geography, education, and other unexpected factors, shifting hiring from intuition to data-driven predictions.