AI ROI
AI ROI is the measurable financial return on an AI investment, calculated as the value generated (cost savings, revenue uplift, risk reduction) net of total cost of ownership.
What is AI ROI?
AI ROI calculations should include build cost, operate cost (model APIs, infrastructure, monitoring, retraining), governance cost (documentation, audit, risk), opportunity cost, and the value side (FTE redeployment, cycle time reduction, error rate reduction, compliance fines avoided). Honest ROI work shows ranges, not point estimates, and tracks the actual outcome against the original case at six and twelve months.
How does AI ROI apply to enterprise AI?
Buyers should require an ROI hypothesis at the end of discovery, with a re-measurement plan in production. Vendors that refuse to commit to outcome metrics are usually selling hours rather than results.
Related terms
- Build vs Buy AI - Build vs buy is the strategic decision between developing an AI capability internally or in partnership, versus licensing a finished product from a vendor.
- Enterprise AI - Enterprise AI is AI deployed inside a large organisation, integrated with systems of record, governed by enterprise risk and compliance, and accountable to multiple stakeholders.
- Discovery Phase - The discovery phase is the first stage of an AI engagement, in which scope, data, workflows, success criteria, and constraints are mapped before any system is built.
- Consulting AI - Consulting AI is the engagement model in which an external team provides AI strategy, design, build, and operate services to an enterprise client.
External references
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