Should you optimize the human process, or bring in AI with a human-in-the-loop? Every input is a lever. Move a slider and the risk-adjusted P&L, the break-even projection, and the recommended human/AI split all recompute live. Same math as the Python engine (roi_tracker).
The CFO interview, as sliders. Type an exact number in any value box.
1 · Current human process (baseline)
What the work costs today, with people - and how much of it there is.
2 · Optimize-the-humans alternative
Before buying AI: how much cheaper could the human process get with lean / tooling, and what would that cost to do?
3 · Model pricing & routing (AI path)
Live token prices per 1M tokens. Router sends simple work to the cheapest fallback, complex work to the cheapest flagship. ● = auto-selected
| Model | Input $/1M | Output $/1M |
|---|
4 · Task mix & token size
5 · Infrastructure & build cost (AI path)
6 · Risk (the Hallucination Tax)
AI is not free of consequence. These deduct from AI savings.
7 · Process sensitivity (drives the split)
How error-costly and judgment-heavy is this work? High sensitivity keeps more of it human, even when AI is cheaper.
8 · Qualitative measures (Human ↔ AI)
Beyond cost. Slide toward whoever is stronger on each dimension: left = Human wins, right = AI wins.
Live. Recomputes on every change.
Three ways to run the same process. Lowest bar wins.
Cumulative cash vs staying all-human. Where a line crosses $0, that investment has paid back.
Where to draw the human / AI line, given cost and sensitivity.
Cost is one axis. These are the rest.
AI ROI Calculator · browser mirrors python -m roi_tracker · MIT