# Essential visibility to strategically scale engineering AI transformations

## Measure impact and ROI

Quantify how AI impacts productivity, quality, and the developer experience.

## Accelerate adoption

Harness cross-SDLC visibility to deploy AI strategically and safely, without hesitation.

## Stay in control

Mitigate risk and stay ahead of the curve with appropriate governance and guardrails.

# AI ENGINEERING REPORT 2026

## acceleration whiplash

The definitive data on AI's engineering impact. What's working, what's breaking, and what leaders need to do next.

- Engineering throughput is up
- Bugs, incidents, and rework are rising faster
- Two years of data from 22,000 developers across 4,000 teams

### "Data-driven insights into our engineering processes empower us to deliver greater value to our clients faster and more efficiently.”  
**Diego Tartara**  
Chief Technology Officer, Globant

# Our solution

## Turn AI adoption into measurable ROI

From coding assistants to autonomous agents, AI is reshaping how teams build. Faros helps you measure what's working and fix what isn't.

## Accelerate AI adoption with a proven step-by-step framework

Pilot, learn, and scale using a results-driven framework. From onboarding to activation, ensure AI adoption sticks—with built-in gamification, enablement, and executive visibility.

- Power user and dormant license identification
- Cohort comparisons, tool A/B tests, and before-and-after metrics
- Weekly executive summaries, insights, and recommendations

## Get the real ROI of AI coding tools—no guesswork

Unlike other solutions, Faros measures AI coding assistants' and agents' impact accurately, filtering out noise and confounding factors.

- Capture true ROI signals with precision analytics and causal analysis
- Identify the best coding assistant and model for your teams
- Share a CFO-ready report built on a trustworthy business case

## Every productivity dimension matters

Velocity is not the whole story. Track AI’s impact on code quality, security, developer satisfaction, and tech debt accumulation.

- Measure leading indicators and lagging outcomes
- Administer surveys to understand the evolving developer experience
- Act swiftly based on personalized AI recommendations

## Pinpoint what’s helping—and what’s holding you back

Immature processes and platforms wipe away AI gains. Faros highlights shifting bottlenecks and alerts on missed opportunities.

- Detect where A is under-performing
- Diagnose bottlenecks and implement fixes
- Get alerts when gains stall or decline

## Enforce safety and quality—right in the IDE

AI-generated code can introduce risk. Faros distinguishes between human and machine-generated code to inform your oversight.

- Flag PRs that require extra scrutiny
- Monitor code quality with real-time checks
- Enforce governance and guardrails at scale

## Highlights

### Adoption and usage

- % of AI-generated code by repo and PR
- License utilization per team
- Feature usage by language and editor
- Multiple coding assistant comparisons

### Pilots and evaluations

- A/B comparisons and ROI calculations
- PR merge rates, PR review time
- Diff size, code smells, test coverage
- Developer satisfaction and time savings

### Rollout and impact

- Feature, task, and code cycle times
- CFR, bugs, incidents, vulnerabilities
- Emerging bottlenecks and infrastructure gaps
- Backlog health and delivery outcomes

### Governance

- AI-generated code tagging
- Policy orchestration for risk mitigation
- Codebase health metrics and refactoring alerts
- Audit trails for AI regulatory compliance

# Unlock real AI impact with Faros

See the platform in action.