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An assessment of how prepared an organization is to adopt, govern, and benefit from AI responsibly. AI readiness considers: whether leadership has defined an AI strategy, whether there are clear policies governing AI use, whether the team has sufficient AI literacy, whether data infrastructure can support AI workloads, whether governance processes (approval, monitoring, incident response) exist, and whether the organization understands its regulatory obligations. AI readiness frameworks are used by consultancies, regulators, and industry bodies to help organizations self-assess before AI adoption. The NIST AI RMF's 'Govern' function maps closely to readiness — governance infrastructure is what makes AI adoption sustainable rather than reactive.
Why this matters for your team
A simple AI readiness assessment before expanding AI use reveals gaps — missing DPAs, no incident process, unclear data policies — that are cheap to fix now and expensive to fix under regulatory pressure. It takes one hour and produces a prioritized governance to-do list.
Before piloting an AI customer support tool, a team completes an AI readiness assessment and discovers it lacks an incident response process and has no signed DPA with its current AI vendor — two gaps it closes before expanding AI use.