Unified Insights • AI value dashboards
What Did You Actually Get From Your AI Tooling Investment?
Most organizations can tell you how many Copilot licenses they have. Very few can tell you what those licenses delivered in code quality, delivery speed, security posture, or business value. The AI value dashboards close that gap.
70%
of developers report a 20%+ productivity boost from AI tools
—Forrester / Worklytics, 2025
6%
of organizations generate meaningful bottom-line impact from AI
—McKinsey Global Survey, 2025
7.2%
drop in software delivery stability for every 25% increase in AI adoption
—DORA Accelerate State of DevOps, 2024
What the AI value dashboards measure
Track true AI impact: tool by tool, team by team.
Track true AI impact, tool by tool
Connect GitHub Copilot, Claude Code, Cursor, Amazon Q, Windsurf, and other popular AI coding tools directly to the outcomes that matter:
- Team-level outcomes: not just individual acceptance rates
- Code quality: defect rate, rework rate, vulnerability introduction rate
- Delivery speed: cycle time, time to PR, deployment frequency
- Security posture: findings introduced by AI-assisted code vs. human-written code
Compare who uses AI vs. who doesn’t
Cohort analysis shows you the real delta: teams using AI tools compared against teams that aren’t, over the same time period, on similar work. Are the results what you expected?
- Deployment frequency: are AI-adopting teams shipping more often?
- Change failure rate: is AI-generated code more or less stable in production?
- Mean time to recovery: are failures resolving faster or slower?
Map engineering investment to business value
Investment Spectrum connects engineering activity to the financial picture Finance cares about:
- Software capitalization: capitalized and non-capitalized cost with historical trends
- Resource cost allocation: by team and initiative
- Planned vs. unplanned work: ratios and trends
- Developer focus summaries: where engineering time is actually going
The data that makes every engineering budget conversation credible — without manual reconciliation across spreadsheets.
Run what-if scenarios
Hummingbird AI answers the questions that require synthesis across your entire data set:
- “Is Cursor or Copilot producing better quality-adjusted productivity in our mobile team?”
- “Which engineering teams have the strongest return on their AI investment, and what separates them from the teams that don’t?”
- “Which teams would benefit most from expanding AI adoption, based on current failure rate patterns?”
See it in action
AI ROI in under 90 seconds.
GitHub Copilot dashboard
Already using GitHub Copilot? Measure its actual impact.
A dedicated dashboard connects Copilot activity to delivery outcomes, not just the metrics Copilot reports itself.
- Acceptance rate by team and individual (context, not ranking)
- Code quality correlation: does AI-generated code perform differently in production?
- Delivery performance by tool adoption level
- Security impact: does AI-generated code introduce more or fewer vulnerabilities?
“What did we get from our AI investment?” is no longer a question you need to deflect.
The AI value dashboards produce board-ready reporting: continuously updated, no manual data assembly.
AI tool adoption trends, productivity delta against non-AI teams, security impact, delivery performance, and Investment Spectrum cost-to-value data all in one place.
30 minutes to show you
- What your AI tooling is actually delivering
- Where it isn’t performing as expected
- The ROI number your CFO will ask for
- Where to invest next