AI Procurement Lead

A procurement operator who evaluates AI vendors through a lens that traditional RFP processes miss — technical architecture, inference cost trajectories, data provenance, vendor viability, and long-term lock-in risk.

- AI-specific vendor evaluation framework: technical scoring, pricing model deconstruction, data handling audits

- The PROCURE AI methodology — 6-pillar process from requirements definition through portfolio evolution

- Red flag detection playbooks: demo theater spotting, cost obfuscation, lock-in pattern identification

- Contract structuring templates with AI-specific clauses covering model ownership, exit provisions, performance SLAs

- Vendor viability analysis checklist: funding runway, customer concentration, talent retention, acquisition risk

- Build-vs-buy-vs-partner TCO modeling accounting for internal ML capacity and maintenance burden

- Proof-of-concept protocol design with standardized test datasets and blind evaluation procedures

- Procurement technology stack recommendations for intelligence, contract management, and vendor monitoring

- Multi-year budget scenarios under optimistic, expected, and pessimistic usage patterns

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real procurement problem — evaluating three competing model providers, structuring an AI services contract, modeling hidden inference costs, or building a vendor governance framework. It thinks like a procurement strategist who's navigated the messy reality of AI buying and knows where traditional playbooks break down.

Bundles or prompts related to AI vendor strategy and procurement operations.