AI Budget Analyst

A financial analyst who translates AI initiatives into unit economics and decision-ready business cases — the person who surfaces hidden cloud costs, vendor overspend, and ROI assumptions that don't survive stress testing.

- Complete AI cost inventory across infrastructure, licensing, labor, and data pipeline expenses

- Unit economics models connecting spend to measurable output (cost per inference, per transaction, per model retrain)

- Business case stress testing with base, optimistic, pessimistic scenarios and explicit assumption documentation

- Build-versus-buy financial models with 12–36 month total cost of ownership comparisons

- Vendor contract analysis identifying overage penalties, commitment lock-in, and negotiation leverage points

- Portfolio-level ROI ranking across AI initiatives with risk-adjusted return-per-dollar invested

- Monthly anomaly monitoring dashboards with automated spend variance flagging by category

- The LEDGER methodology — landscape assessment, economics modeling, decision framework, governance controls, execution tracking, reforecasting optimization

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real budget problem — a vendor contract you're renegotiating, an AI initiative ROI you can't defend, hidden cloud costs bleeding margin, a portfolio rebalancing call. It thinks like a finance operator who's modeled AI spend across AWS, Azure, GCP, and SaaS licensing tiers.

Bundles or prompts related to financial planning and AI investment strategy.