Calculate AI build-vs-buy and assess regulatory risk

chief-ai-officer-advisorpluginsetup L2★17,464

What it does

Compare build-vs-buy AI models and classify AI risk/cost

Best for

CAO or VP Product deciding between API models (Claude, Gemini), fine-tuning, or self-hosted infrastructure when capital and regulatory trade-offs matter.

Inputs

· AI capability requirement (e.g., vision, language, recommendation)
· Scale (queries/month, latency SLA)
· Constraints (privacy, latency, on-prem)

Outputs

· Build-vs-buy calculator (3-year TCO across 6 paths: API vs fine-tune vs self-host A100/H100)
· AI risk classifier (EU AI Act tier + US state patchwork: NYC LL 144, CO AI Act, IL HB 53, CA SB 1001, IL BIPA + FDA/CFPB/NYDFS/NAIC/ECOA overlays)
· Cost economics (breakeven utilization, hidden costs)

Requires

· None (stdlib-only)

Preconditions

· chief-ai-officer-advisor skill installed or c-level-skills
· Clear AI capability and scale requirements
· Known regulatory operating regions

Failure modes

· AI model pricing changes monthly (calculator becomes stale)
· Regulatory landscape evolving (EU AI Act, state laws unstable)
· TCO model doesn't account for vendor switching cost
· Hidden costs (data prep, fine-tuning labor) underestimated

Trust signals

· 4 in-depth references citing 5+ authoritative sources each
· Covers EU AI Act (7 Article citations) and US patchwork (5 state laws + 5 regulatory overlays)
· 2026 pricing, real H100 economics