AI Coding Assistant Productivity ROI Calculator
Calculate the return on AI coding assistants (GitHub Copilot, Cursor, Codeium, Tabnine, JetBrains AI) — developer hours times measured productivity gain times fully loaded engineering cost minus license spend. Get a per-developer monthly net benefit and team-wide annual savings.
What the Research Actually Shows
The 2024 GitHub-Microsoft randomized controlled trial of 4867 developers found Copilot users completed tasks 26 percent faster on average, with newer developers (under 5 years) seeing 27-39 percent gains and senior developers seeing 8-13 percent. METR's 2025 independent study put real-world gain at 10-18 percent (lower than vendor claims). McKinsey's 2024 study aligned with the higher range for greenfield code (35-55 percent faster) but found near-zero gain for legacy code maintenance. Pick your assumption carefully.
ROI Formula
Monthly Savings = Devs × Hours/Month × Productivity Gain % × Loaded Hourly Cost
Net ROI = (Savings - License Spend) / License Spend × 100
License Pricing as of 2026
GitHub Copilot Business: USD 19/dev/month, Copilot Enterprise: USD 39/dev/month. Cursor Pro: USD 20/dev/month, Cursor Business: USD 40/dev/month. Codeium Teams: USD 12/dev/month. JetBrains AI Pro: USD 20/dev/month. Amazon Q Developer Pro: USD 19/dev/month. Self-hosted options (Continue, Tabby) trade license fees for inference cost — budget USD 30-80/dev/month in LLM bills.
Why Most ROI Cases Are Wrong
Common errors: (1) using vendor-quoted productivity numbers (always optimistic), (2) measuring only code-writing time when the dev cycle includes debugging, reviewing, testing, and meetings, (3) ignoring code review burden — AI-generated code needs more review, not less. The realistic adjustment: multiply your raw productivity gain by the share of dev time spent actually coding (typically 25-40 percent, not 100 percent). A 30 percent coding-time productivity gain on a dev who codes 30 percent of the week is a 9 percent net hour gain.
How to Build a Defensible Business Case
Use coding-time-only productivity gains from peer-reviewed research (15-25 percent is the safe band), apply the coding-time share of total dev time, and use fully loaded engineering cost (salary times 1.4 for benefits and overhead, divided by 1900 working hours). Subtract license cost. Year-one ROI of 200-400 percent is realistic; vendor claims of 1000 percent plus are usually wrong. Track actual productivity through cycle time and PR throughput, not LOC.
Sources: GitHub-Microsoft RCT 2024 (Cui et al.), METR Productivity Study 2025, McKinsey GenAI in Software Engineering 2024, GitHub Pricing (2026), Cursor Pricing (2026). Last updated: April 2026.
Frequently Asked Questions
Why are vendor productivity claims so much higher than this calculator?
Vendors measure code-writing time on isolated tasks, not full developer time. A 55 percent gain on coding time becomes a 14-22 percent gain on total dev time once you factor in meetings, code review, design, debugging, and waiting on CI. This calculator uses the realistic total-time math.
Does Copilot work better for senior or junior developers?
GitHub-Microsoft 2024 RCT showed juniors (under 5 years) gain 27-39 percent while seniors gain 8-13 percent. Juniors get more help generating boilerplate; seniors hit diminishing returns because they already type fast and have strong patterns. License ROI is generally stronger for junior-heavy teams.
Should I include increased code review burden as a cost?
Yes — AI-generated code shows 41 percent more bugs in production (GitClear 2024) and gets reviewed 11 percent slower. Add a 5-10 percent productivity penalty on reviewers if your team commits AI-generated code without strong testing discipline. The net is still usually positive but smaller.
Is Cursor or Copilot a better ROI?
Cursor (USD 20) generally beats Copilot (USD 19) for productivity in qualitative dev surveys (DX Report 2025), driven by stronger multi-file context and agent features. Copilot is stronger on enterprise SSO and compliance. ROI difference is small; pick on workflow fit.
What if my team uses self-hosted models?
Replace the license cost field with your monthly inference cost per developer — typically USD 30-80/dev/month for serious daily use on Llama 3.1 70B class models, plus GPU infrastructure amortization. Self-hosting wins below 100 devs only at scale or with strict data residency requirements.
Is this tool private?
Yes. All calculations happen in your browser. Your headcount, salary, and gain assumptions are never sent, stored, or shared.