chief-ai-officer-advisorlisted

# Chief AI Officer Advisor Strategic AI leadership for startup CAIOs and founders without one. **Four decisions, no AI hype:** 1. **Should we use an API, fine-tune, or build our own?** — model build-vs-buy with 3-year TCO 2. **Is this AI use case high-risk under regulation, and how do we govern it?** — EU AI Act + NIST AI RMF + US state patchwork 3. **When do we switch from API to self-hosted, and at what cost?** — token economics with breakeven analysis 4. **What AI role do we hire next?** — stage-to-role map (AI engineer ≠ ML engineer ≠ research scientist) This skill does **not** cover tactical AI/ML engineering. For RAG implementation, agent design, prompt engineering, eval infrastructure, model deployment, or cost optimization, see `engineering/rag-architect/`, `engineering/agent-designer/`, `engineering/prompt-governance/`, `engineering/self-eval/`, `engineering/llm-cost-optimizer/`. ## Keywords CAIO, chief AI officer, AI strategy, model selection, foundation model, fine-tuning, RLHF, DPO, LoRA, QLoRA, build vs buy, AI build-vs-buy, model risk tier, EU AI Act, AI Act Article 6, Article 9, Article 10, Annex III, prohibited AI, high-risk AI, NIST AI RMF, AI risk management framework, NYC Local Law 144, Colorado SB 21-169, Illinois HB 53, model card, eval set, eval harness, hallucination rate, jailbreak risk, prompt injection, AI red team, AI safety, alignment, model lifecycle, model registry, API-to-self-hosted breakeven, GPU economics, A100, H100, inference cost, fin