Building AI-Powered Team

AI adoption is one of the biggest challenges and at the same time one of the biggest opportunities for business.
Some teams report significant productivity boost. Others say: “AI might be useful for some tasks.”

So what’s the difference?
AI adoption is not about access to the tools. Just buying licenses and giving them to engineers doesn't work. The team need to rethink how they work and integrate these tools into their daily workflow. And that’s already classic change management task.

On this topic, I recently came across the GitHub Internal Playbook for building an AI-powered workforce. They highlight that AI adoption is not really a technical problem, it’s a human one.

GitHub suggests 8 pillars to drive adoption at the organization level:
- AI advocates. Internal champions who scale adoption through peer-to-peer influence and feedback.
- Clear policies. Defines rules for using AI.
- Learning & development. External and internal training and education.
- Metrics. Track adoption, engagement, and business impact.
- Ownership. A central owner who orchestrates the program and drives the overall strategy.
- Executive support. Visible leadership commitment and strategic vision.
- Right tools. Different tools for different roles.
- Communities. Peer-to-peer learning, knowledge sharing, and collaborative problem-solving.

And in reality, the key part here is the people on the ground, the experts who drive the change, adapt the tools to real tasks, and teach others. This is also covered in more detail in the companion article Activating your internal AI champions.

You can’t roll out AI top-down.
You can’t standardize it with one template for everyone. Every team has its own context. Without understanding it, any “unified approach” will fail.

#leadership #ai