Red flags, governance signals, and 75 role-specific questions for professionals evaluating AI projects before they commit time, budget, or credibility.
Most AI initiatives fail because the wrong questions weren’t asked early enough. This guide gives developers, architects, project managers, QA teams, consultants, and sales professionals a structured way to evaluate AI projects by spotting weak foundations, poor data practices, and governance gaps before they become costly problems. Backed by frameworks from NIST, the U.S. Department of Defense, GAO, McKinsey, and Stanford’s AI Index, this is the reference your team reaches for when an AI project needs real scrutiny.
