Why Do Most AI Audits Fail Before They Even Start?

Because they begin with technology instead of intent. Teams jump straight into models, workflows, and integrations without first agreeing on one thing: what business outcome AI is actually responsible for moving. When intent is unclear, every audit finding becomes subjective, every recommendation becomes debatable, and every roadmap turns into a wishlist. A proper AI Audit starts by locking the “why” before touching the “how”. What metric changes if AI succeeds, what risk increases if it fails, and what decision authority is being shifted as a result? If your audit cannot map AI systems to explicit business intent and measurable outcomes, you’re not auditing readiness, you’re reverse-engineering guesses. Transformation starts when intent is auditable, not when tech is impressive.

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