Time-to-Value (TTV) in AI finance is the elapsed time between the activation of an AI agent and the moment it delivers measurable financial value, first detected anomaly, first hour saved, first verified overcharge. It is the most reliable indicator of whether an AI finance solution will actually hold in production or remain a demo.
The TTV gap defines the AI finance market. Generalist AI tools deliver impressive demos but require months of customization before producing usable output on real data. Enterprise AP platforms promise full automation but deliver after 6-to-12-month implementations that often miss their original ROI targets. Specialist AI for finance, purpose-built around concrete use cases, operates on a fundamentally different curve.
Phacet's TTV benchmarks, measured across production deployments:
- First agent in production: under 1 week for most clients
- First detected anomaly on real data: within the first PoV cycle (typically 1–2 weeks)
- First measurable financial impact: within the first month (overbillings caught, hours recovered)
This is the structural advantage of incremental AI deployment: scope discipline forces fast value delivery. One use case, real data, immediate output, versus the traditional model of build-everything-then-deploy.
For DAFs evaluating AI finance tools, TTV is the question that separates marketing from delivery. The right comparison isn't what does it do?, it's when will it deliver? A 1-week TTV on supplier price control is a measurable commitment. A 6-month implementation roadmap is a deferred risk.
