Impact & ROI
Measure the business value of AI investments. Track productivity gains, time savings, and quantifiable returns across engineering teams.
Annual ROI
1416%
$15.16 return per $1 spent
Payback period: 0.8 months
Hours Saved/Week
8.5h
$1,964,650.90/month value
Velocity Gain
+51%
12.8 commits/engineer/week
PR Cycle Time
-57%
Now 6.2 hours average
Defect Reduction
-45%
2.1 bugs/1K LoC
ROI Summary
Investment
Annual AI Spend$1,676,400.00
Implementation (amortized)$16,666.67
Training (amortized)$25,000.00
Total Investment/Year$1,718,066.67
Annual Returns
Time Savings
$23,593,960.00Velocity Gains
$1,850,000.00Quality Improvements
$420,000.00Onboarding Savings
$180,000.00Total Returns/Year$26,043,960.00
ROI
1416%
Return Per $1
$15.16
Payback Period
0.8mo
ROI by Team
Performance and ROI breakdown across 8 engineering teams
| Team | Engineers | Adoption | Hours Saved/Week | ROI | Primary Tools |
|---|---|---|---|---|---|
| Frontend | 135 | 85% | 975h | 428% | Cursorv0ChatGPT Plus |
| Product Engineering | 220 | 82% | 1534h | 412% | CursorChatGPT Plusv0 |
| Platform Engineering | 85 | 89% | 642h | 385% | CursorGitHub CopilotClaude Pro |
| Backend | 130 | 78% | 862h | 371% | CursorGitHub CopilotClaude Pro |
| Data Engineering | 95 | 76% | 613h | 356% | Claude ProGitHub Copilot |
| Infrastructure | 72 | 68% | 416h | 312% | GitHub CopilotChatGPT Plus |
| Mobile Engineering | 65 | 71% | 392h | 298% | GitHub CopilotChatGPT Plus |
| Security | 48 | 62% | 253h | 285% | Claude ProChatGPT Plus |
Highest ROI Team
Frontend
428% ROI
Highest Adoption
Platform Engineering
89% adopted
Total Hours Saved
5687h/week
Across all teams
Time Savings Breakdown
8.5 hours/week per engineer
Coding
4.2h/week$357.00
Code Review
1.5h/week$127.50
Debugging
1.2h/week$102.00
Documentation
0.9h/week$76.50
Testing
0.7h/week$59.50
Total Hours Saved/Week5338h
Monthly Value$1,964,650.90
Annual Value$23,593,960.00
AI Users vs. Non-AI Users
Performance comparison across engineering teams
| Metric | AI Users | Non-AI Users | Improvement |
|---|---|---|---|
| Engineers | 628 | 222 | - |
| Commits/Week | 12.8 | 8.2 | 56% |
| PR Cycle Time (hrs) | 6.2 | 15.1 | 59% |
| Incident Response (hrs) | 3.2 | 6.1 | 48% |
| Lines of Code/Week | 842 | 505 | 67% |
| Defect Rate (per 1K LoC) | 2.1 | 4.2 | 50% |
Key Insight
AI users are 56% more productive while maintaining 50% fewer defects. PR cycle time reduced by 59%.