How a Tier-1 Financial Institution Increased Copilot Adoption from 6% → 72% and Achieved 2.4× Developer Velocity

Overview

This case study summarizes the outcomes from an Engineering Excellence engagement inside a global financial institution. The client faced slow delivery cycles, inconsistent development practices, and stalled AI adoption. GitHub Copilot usage was limited to a small group of engineers with no governance, measurement model, or coaching in place.

Using the Engineering Excellence Framework, Intellibus helped the organization increase Copilot adoption from 6% → 72% and improve Developer Velocity from 5.7 → 13.6 Story Points per Developer, resulting in a 2.4× throughput uplift — achieved without adding headcount.

Starting Point

• Copilot adoption stalled at 6%
• Developer Velocity baseline: 5.7 SP/Dev
• No standardized workflows or quality gates
• Teams using inconsistent engineering practices
• Limited visibility into cycle time and productivity metrics
• Regulatory pressure on modernization and delivery performance

What We Implemented

• Discovery of architecture, workflow and cultural blockers
• Standardized engineering practices across squads
• GitHub Copilot rollout with governance + coaching
• AI usage guidelines aligned to financial-sector compliance
• Developer Velocity measurement model + squad telemetry
• Weekly pairing sessions and behavior-driven coaching
• Quality gate improvements across the pipeline
• Leadership dashboard for adoption, velocity and cycle-time

Outcomes Achieved

Why This Case Study Matters

• Demonstrates measurable Copilot ROI inside a heavily regulated financial institution
• Highlights that AI adoption requires standards, structure and coaching — not just tool access
• Provides a clear benchmark for CIOs evaluating their Copilot journey
• Shows that measurable uplift can occur within 90 days
• Validates the Engineering Excellence Framework as repeatable across enterprise environments