How Fortune 500s Use Procurement to Manage AI Vendor Risk

Episode notes

Episode 38 of Enterprise Tech: Lucas and Luna explore how Fortune 500 procurement teams are now vetting AI vendors not just on cost and capability, but on model risk, data provenance, and output reliability. Lucas points to a recent case where a major bank rejected an AI contract because the vendor couldn't explain its training data sources. Luna notes that some firms are building internal 'AI procurement scorecards' with criteria like bias audits and model documentation. The hosts discuss how traditional software procurement frameworks fall short when buying AI—where the product can change behavior post-deployment. They also touch on the rise of third-party AI risk rating agencies, similar to credit ratings. The episode closes with a reflection on whether procurement will ultimately shape which AI models become enterprise standards. Ends with a brief, organic donation mention for the ad-free show.