Workflow · Production
GitHub Enterprise: enterprise customer stories featuring GitHub Copilot and AI-powered development
The problem
(not stated)
Workflow diagram · grounded in source
1
Enterprises adopt AI-powered development
trigger
“Cathay embraces AI-powered development to deliver securely at scale”
2
Copilot empowers engineers
ai_action
“Duolingo empowers its engineers to be force multipliers for expertise with GitHub Copilot”
3
Development cycles accelerate
output
“How AMD compressed development cycles from weeks to days with GitHub Copilot”
Reported outcome
Enterprises using GitHub Copilot and GitHub Enterprise report accelerated development cycles and higher developer productivity, with WEX achieving 30% higher developer productivity and Trimble saving 1,000 hours of developer time per day.
Reported metrics
developer productivity increase (WEX)30%
developer time saved per day (Trimble)1,000 hours
development cycle time (AMD)weeks to days
GitHub Copilot users (Accenture)12,000 developers
Reported stack
GitHub CopilotGitHub EnterpriseMicrosoft Azure DevOps
Frequently asked questions
What did this team achieve with this AI workflow?
Enterprises using GitHub Copilot and GitHub Enterprise report accelerated development cycles and higher developer productivity, with WEX achieving 30% higher developer productivity and Trimble saving 1,000 hours of de…
What tools did this team use?
GitHub Copilot, GitHub Enterprise, Microsoft Azure DevOps.
What results were reported?
developer productivity increase (WEX): 30%; developer time saved per day (Trimble): 1,000 hours; development cycle time (AMD): weeks to days; GitHub Copilot users (Accenture): 12,000 developers (source-reported, not independently verified).
How is this workflow AI workflow structured?
Enterprises adopt AI-powered development → Copilot empowers engineers → Development cycles accelerate.