AI Procurement & Vendor Risk

AI Procurement & Vendor Risk is the track for the people on the buy-side of AI — the procurement leads, third-party risk managers, vendor management offices, contract counsel, security and privacy reviewers, and product owners deciding which AI vendors to hire. Most enterprise AI today is built on third-party components: foundation models from a handful of providers, vector databases, embedding APIs, fine-tuning platforms, agent frameworks, evaluation services, RAG infrastructure, voice and vision APIs, and a long tail of vertical AI SaaS. Every one of those vendors carries risk that the buyer ultimately answers for — performance risk, data risk, IP risk, security risk, regulatory risk, concentration risk, and reputational risk. Procurement and vendor risk is where those risks are surfaced, allocated, and managed.

The lessons here are written for the practitioners who actually run procurement and vendor management for AI. Every topic explains the underlying procurement and risk-management discipline, the AI-specific twist (because AI vendors do not behave like traditional SaaS vendors), the contractual or operational lever that gives the buyer control, and the failure modes (what gets a vendor onboarded that should not have been, what makes a contract un-enforceable when an incident occurs, what blows up an exit). The aim is that a reader of the track can run a defensible AI vendor selection, negotiate a fit-for-purpose contract, manage the vendor through the relationship, respond to incidents without losing leverage, and exit cleanly when the time comes — whether the buyer is a startup buying its first model API or an enterprise running a portfolio of dozens of AI vendors.