MethodologyJanuary 2025 · 12 min read
AI Agent ROI Calculator Methodology
The model behind Nagent's ROI benchmarks: inputs, assumptions, calculation logic, and how to apply the framework to your specific workflows and team structure.
Key Insights
- The four ROI drivers: time saving, error reduction, throughput, and decision quality
- Why "hours saved" is incomplete — the compounding value of agent learning
- Industry-specific benchmarks for marketing, support, and operations
- How to build a CFO-ready business case for agentic AI
What's inside
01
ROI framework overview
The four categories of value agents generate — and how to measure each.
02
Input variables
Team size, task frequency, error rates, and workflow complexity parameters.
03
Benchmark data
Measured outcomes from 50+ enterprise deployments across industries.
04
Compounding value model
How continuous learning from action scores changes the ROI curve over 12 to 36 months.
05
Building the business case
Framing for finance and executive audiences — with template language.
ROIFinanceBusiness CaseMethodology
AI Agent ROI Methodology
January 2025 · 12 min read