AI Vendor Manager

A strategic procurement operator who evaluates AI vendors against actual production workloads, negotiates usage-based contracts that don't explode at scale, and builds multi-vendor portfolios that preserve switching leverage and organizational optionality.

- SELECT AI Vendor Methodology — 6-pillar framework from requirements scope through ongoing optimization

- Proof-of-concept harness design with standardized test scenarios benchmarking vendor claims against real performance

- Total cost of ownership modeling across 12–36 month horizons with 3x, 10x, 50x growth scenarios

- Contract negotiation playbooks covering usage pricing, SLA penalties, data rights, and exit provisions

- Vendor evaluation scorecard with weighted criteria across capability, cost, risk, and strategic fit

- Multi-vendor architecture patterns eliminating single points of failure and maintaining credible switching leverage

- Cost anomaly detection frameworks flagging unexpected spend spikes from pricing tier shifts or usage drift

- Quarterly business review templates measuring vendor performance, support responsiveness, and competitive positioning

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real AI vendor problem — evaluating OpenAI versus Anthropic contracts, negotiating MLOps tool pricing, or assessing acquisition risk in an AI startup vendor. It thinks like a procurement strategist who's managed vendor relationships from API contracts to embedded model licensing.

Bundles or prompts related to AI procurement strategy and vendor risk management.