RPA plus AI, document processing, and workflow automation. Value comes from labor hours recovered and errors eliminated.
Your Program
Risk Adjustment
Your ROI Model
Break-Even Timeline
3-Year Projection (Risk-Adjusted)
| Metric | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| Annual benefit | |||
| Annual cost | |||
| Net benefit | |||
| Cumulative ROI |
Benchmark Comparison: 3-Year ROI
How to Read This Model Like a CFO
A calculator produces numbers. The harder job is knowing which numbers survive contact with a finance review. Three things every executive team should internalize before presenting an AI business case.
Why AI ROI is harder to measure than traditional IT
Traditional IT projects replace a known cost with a known cost. AI programs change how work happens, which creates three measurement problems:
- Attribution: productivity gains blend with other initiatives. Fix: define a control group or pre/post baseline before launch, not after.
- Time lag: benefits compound as adoption grows. Fix: model an adoption ramp (this calculator uses your deployment timeline for that) instead of assuming day-one value.
- Redeployed time: hours saved only become dollars if they are redirected to revenue work or absorbed via attrition. Fix: agree with finance up front on the "capture rate" of saved hours.
The hidden costs CFOs miss
License fees are usually the smallest line. Budget for the full stack of ownership costs:
- Governance: model risk review, audit trails, and compliance documentation, typically 10-15% of program cost in regulated industries.
- Retraining and enablement: ongoing training as tools and workflows evolve, not a one-time launch event.
- Integration maintenance: every system the AI touches becomes a dependency that must be maintained through upgrades.
- Model drift monitoring: models degrade as data and behavior shift. Someone must own detection and retraining, permanently.
How to present this to your board
Boards do not want 40 slides of methodology. They care about three numbers:
- Payback period: when the program stops consuming cash. Under 18 months is fundable without debate. Over 30 months needs a strategic rationale.
- Risk-adjusted NPV: present the discounted number, not the best case. Boards trust executives who discount their own projections.
- The downside case: what is lost if the program achieves half its target. If the half-case still clears the hurdle rate, approval is straightforward.
Research Foundation
Every benchmark in this calculator comes from named, published research. No synthetic statistics.
EBITDA improvement attributed to AI among AI high performers
McKinsey Global Survey on AI, 2024Faster task completion for developers using GitHub Copilot in controlled study
GitHub / Microsoft Research, 2023Average return per $1 invested in AI across surveyed enterprises
IDC, 2024Of AI projects fail to deliver expected ROI without proper change management
Gartner, 2024Higher project success rate for organizations with strong change management
Prosci Change Management Benchmark, 2023Revenue growth for companies in the top AI maturity quartile vs the bottom quartile
BCG, 2023Want a second set of eyes on your model?
Arjun Jaggi advises Fortune 500 executives on AI strategy, business cases, and board presentations. Bring your numbers, leave with a defensible model.
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