AI/ML strategy, execution and talent shouldn’t be considered separate.

Define what’s actually worth building and whether AI is even the right approach—so you don’t waste months on the wrong problem. Align on a clear path to value before writing a single line of code.

Turn the right idea into a working AI product—not just a demo—by focusing on the critical path and real-world constraints like cost, latency, and reliability. Ship something that holds up in production.

Ensure the system can grow beyond the initial build by defining ownership and setting it up for long-term success. Whether through hiring or internal enablement, make sure it doesn’t depend on you.