AI Intake

AI intake refers to the formal process of documenting, evaluating, and approving new AI projects or systems before they enter development or deployment. This typically involves capturing project details, assessing risks, identifying data and compliance requirements, and ensuring alignment with organizational AI governance policies. Effective AI intake processes help enterprises maintain control over their AI footprint, prevent rogue AI development, and ensure that all systems undergo appropriate risk assessment before resources are committed.

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ResearchUS2026-07-23

DDMI's Two-Step AI Approval Model Shows How Enterprises Can Operationalize Use-Case and Product Review as Separate Gates

Data-driven enterprise DDMI has published a detailed account of how it operationalized AI governance through a two-step approval process, reviewing use cases first and then the specific product or tool. The approach incorporates legal and regulatory checks, security assessments, continuous monitoring, and data-location guardrails. The case study, published by Dataversity, offers a replicable blueprint for compliance teams building or refining structured AI intake workflows.

approval process continuous monitoring data governance risk controls AI intake enterprise governance DDMI