While strategy and vision are important, most teams are looking for concrete starting points. This article approaches Running Effective Architecture Reviews for AI Projects from a practical angle, focusing on steps that can be taken in the next one to three quarters.
It outlines a small number of pragmatic patterns, shows how to define a sensible scope, and suggests artefacts that help maintain alignment as work progresses. The emphasis is on incremental progress rather than large, risky bets.
Examples are drawn from real projects, with attention paid to what actually helped teams move forward: how problems were framed, how stakeholders were engaged, and how outcomes were measured.
Readers should be able to translate the ideas into their own environment, adapting details while preserving the underlying intent.