Many organizations treat AI adoption as a technology challenge. But a big obstacle can be the new demands placed on middle managers, who are expected to implement AI, maintain quality, and develop their teams all at once. If you want AI adoption to deliver lasting value, you need to invest in the people in the middle layer.
Protect time for learning. Don’t expect managers to figure out AI on top of their existing workload. Set aside dedicated time for experimentation, encourage teams to document what works, and create a central place where everyone can find proven prompts, workflows, and guidance. When learning is built into the work, improvements spread faster.
Reward the behaviors that matter. Update performance expectations to recognize coaching, knowledge sharing, and AI adoption—not just output. Encourage managers to develop their teams, share successful practices, and contribute what they learn, so knowledge compounds across the organization.
Close the gap between strategy and execution. Give managers clear standards for how AI should be used instead of leaving them to make judgment calls on their own. Involve them in implementation discussions, train them to evaluate AI-generated work, and create opportunities for them to learn from one another.
