Managing Third-Party AI Risk: A C-Level Playbook for Vendors, Models, and Data Supply Chains

Enterprises increasingly deliver value through models and data they did not build. This monologue gives C-level leaders a pragmatic playbook to turn third-party AI suppliers from uncontrolled risk into governed strategic partners. I cover how to assess vendor capabilities, design contractual SLAs for model performance and data quality, embed technical due diligence into procurement, operationalize monitoring and incident response for external models, and align commercial terms with shared outcomes. Listeners will get concrete decision frameworks—when to buy, build, or partner—plus governance checkpoints that integrate procurement, legal, security, and data teams. The episode balances the trade-offs between speed and control, explains measurable KPIs for supplier-managed models, and shows how to scale safe adoption without centralizing or stifling innovation. This is a practical, non-technical guide tailored for CEOs, CTOs, CDOs, and Heads of Procurement who must make executable decisions about AI suppliers.Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.