Enterprise AI ROI & Productivity Calculator
Quantify the exact dollar return and annual hours saved from deploying modern AI coding assistants and LLM workspaces across engineering, design, and product teams.
Investment Parameters
Industry benchmark: GitHub and McKinsey report 3.5 to 5.5 hours saved per developer weekly on code generation, testing, and documentation.
45 Hours
Equivalent to adding 1.1 full-time team members without additional recruiting or overhead.
$200 / mo
Total monthly license investment across 10 active seats at $20/seat.
Calculation Methodology & Productivity Benchmarks
The BunusRadar AI ROI Model synthesizes empirical telemetry from Fortune 500 engineering deployments and peer-reviewed software studies. Calculations assume a standard 50-week operating year, excluding paid time off and national holidays.
Developers completed coding tasks 55.8% faster and felt 88% more fulfilled in their work when assisted by AI code generation.
Generative AI accelerates software development throughput by 20% to 45% of annual engineering overhead, predominantly in refactoring and documentation.
Because modern tooling seats cost $19 to $25 per month while senior engineers cost over $65/hr, reclaiming less than 30 minutes monthly pays for the entire license.
Frequently Asked Questions
How should we factor in onboarding time and learning curve?
Initial productivity gains typically stabilize within 2 to 3 weeks. To model a conservative ramp, consider reducing initial hours saved to 2.5 hours per week during the first quarter.
Can I present this calculation to my CFO or executive committee?
Yes. Use the 'Copy Executive Report' button above to generate a formatted executive brief detailing software expenditure, gross reclaimed hours, and net annual profit impact.