b0gy Posted on Jun 1 • Originally published at b0gy.com AI vendor selection is not software procurement # ai # strategy # security When you buy a SaaS tool, your data sits in someone else's database. When you buy an AI service, your data flows through someone else's model. It has the posibiliy to become training data. Your data might get embedded in weights you can never inspect. It might surface — partially reconstructed — in another customer's retrieval results. Procurement teams treat these as the same purchase. Same checklist — SOC 2, uptime SLA, data encryption at rest — check every box, sign the contract, and discover six months later that their customer data has been training a global model by default. Or that their embeddings are locked in a proprietary format with no export path. Or that the vendor quietly added an AI sub-processor whose data handling invalidates three of their customer contracts. SOC 2 Type II and ISO 27001 are table stakes — almost every SaaS vendor has them nowadays. They tell you the vendor has a security program. They tell you nothing about what happens to your data once it enters the model. ISO 42001 — the AI management systems standard — is the first certification that actually covers AI governance: how training data is sourced, how models are monitored, how risks like bias and hallucination are managed. Most vendors don't have it yet. The ones that do are telling you they take AI-specific risk seriously, not just infrastructure security. Your data has more owners than you think The thing that trips up most procurement teams is sub-processing — when your vendor passes your data to another company for processing. In traditional SaaS, this is usually a hosting provider or an analytics tool. In AI, it's the model provider. Different thing entirely. Best example: AWS Bedrock and Claude on Anthropic's platform both let you use Claude. Both run on AWS infrastructure. They are not the same product. AWS Bedrock: AWS is the sole processo
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