Episode 23 — Stand Up an AI Risk Intake Process: Bring New Use Cases Under Control (Domain 2)
An effective AI risk intake process serves as the "front door" for all AI-related initiatives, ensuring that no model is developed or deployed without a preliminary risk screening. This episode details how to design an intake workflow that captures essential information such as the intended use case, data sources, and potential impact on third parties. For the AAIR exam, candidates should understand how this process differentiates between low-risk experiments and high-stakes production deployments, allowing the organization to apply resources where they are most needed. We discuss the use of standardized intake forms and automated triggers that alert the risk team when a proposed project exceeds specific risk thresholds. Best practices include making the intake process user-friendly to encourage compliance and prevent the rise of shadow AI. By institutionalizing this "first look" at new AI use cases, risk professionals can provide early guidance that shapes the design of the system, reducing the likelihood of costly architectural changes or regulatory interventions later in the lifecycle. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
