A clearly defined problem, with an owner and a way to measure value, gives an AI initiative a reason to exist beyond novelty.

Not every problem needs generative AI, an agent, or a predictive model. The right AI approach follows from the problem, not the other way around.

AI systems are only as good as the data behind them. Availability, quality, and access determine what's realistically possible.

An AI capability still has to fit into how real people work. Where it sits, and who uses it, shapes the entire design.

Existing systems, APIs, and infrastructure determine how much new work is required versus how much can be reused.

Sensitive data, access controls, and human oversight need to be designed in from the start, not added afterward.

Ownership, budget, timeline, and engineering capacity determine whether a good idea actually ships.