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The Governance Gap: Why Buyers are Exposed
Traditional AI lifecycle models and governance frameworks remain hyper-focused on developer-controlled responsibilities, largely ignoring the critical governance role buyers perform through selection, adaption, adoption, and deployment. If you buy a commercial AI solution, you need to know exactly where your responsibilities begin and end, otherwise, you risk eroding trust, inviting litigation, and diminishing your strategic return on investment (ROI).

Introducing Distributed AI Governance
This video presents the Distributed AI Governance framework, essential research for organizations that procure and deploy commercial AI solutions. The central finding is profound: AI governance is not a monolithic concept, but rather a dynamic distribution of responsibility that evolves as the AI solution archetype shifts. We move beyond high-level principles to provide a granular analysis of where, when, and by which stakeholder risk can be directly controlled.