AI investment decisions
AI Business Case Validator
“Will this AI initiative repay its token and delivery spend?”
7 report pages · hover to hold, select a frame to view it
What it shows
- A portfolio map of evidence confidence against evidence-adjusted ROI.
- Every benefit claim with the strength of the evidence behind it.
- A 12-month forecast of tokens, inference and licences, and when spend breaches budget.
- Six warning signs of funding on excitement rather than evidence.
Outcomes
- Claimed benefits discounted by evidence, set against the full run cost.
- A dated, costed proof for every initiative that goes to pilot.
- Spend avoided by stopping what has not earned funding, shown in dollars.
Built for: CIOs, CFOs and AI steering groups deciding which AI initiatives to fund.
Product specification
Seven report pages: AI Portfolio Control Tower, Benefit Claims & Evidence, AI Spend Forecast, Value vs Cost, Shiny-Object Check, Funding Decisions & Proof Gates, and a Methodology appendix.
Each piece of evidence moves confidence in a claim by its strength, and contradicting evidence pulls it down. Token spend is modelled per conversation or task, including retrieval context, and run as a Monte Carlo forecast with likely (P50) and pessimistic (P90) budget breach dates. Decision rules sort each initiative into fund, pilot with a proof gate, or stop.
- Pages
- 7
- Forecast
- 12 months, P50 / P90
- Decision
- Fund · Pilot · Stop
- Format
- Power BI (PBIP), CSV inputs
How it's delivered: days, not months
- ScopeA short call to agree the decision it needs to support and which data you already have.
- LoadYour exports go into the model's CSV templates. No live connection to your systems is needed to start.
- RunThe model runs on your data, and every number traces back to its inputs and the documented method.
- Hand overYou keep the Power BI file, its design walkthrough and engineering companion, or our practitioners run it with you each month.
See AI Business Case Validator running on your own data.
