At a glance
Who: City of San José.
What: The City has announced its in-house AI training programmes have reached a milestone of more than 1,000 trained employees.
Why: To skill-up the workforce and create a national model for municipal AI adoption.
When: The programme was launched in 2024.
The City of San José has announced its AI training programmes have reached a milestone of more than 1,000 trained employees, set when it launched the programme in 2024.
Built entirely in-house, the programme has trained roughly 15 per cent of the City’s total workforce and has established San José as a national model for municipal AI adoption. The City aims to expand training to 2,500 employees – approximately 30 per cent of the entire city workforce – by June 2027.
AI training
San José claims its approach sets it apart from peer cities. While many local governments contract AI training to outside vendors, San José built its curriculum from scratch – then empowered its employees to run with it.
Programmes range from self-paced online modules to a rigorous 10-week, hands-on course where staff design and deploy AI tools tailored to their specific roles. As a result, the City reports employees across nine departments are spending less time on repetitive administrative tasks and more time directly serving residents.
Developed in partnership with San José State University, the programme uses a train-the-trainer model, equipping employees to bring AI skills back to their departments and train colleagues directly. Each AI assistant developed through the AI Upskilling programme helps staff save 100 hours or more each year.
“Every time someone needed help with a Power BI dashboard, it meant finding time on my calendar. Now the assistant handles those questions instantly – we’ve saved hundreds of hours across the team, and nobody’s waiting on me to get unstuck”
A San José Fire Department employee offers a glimpse of what the programme makes possible. He built an AI tool that instantly verifies every fire truck is fully equipped before a crew deploys. What once required hours of manual asset tracking now happens in seconds, saving hundreds of staff hours each year.
Elsewhere, an employee from the Department of Transportation built a tool that automatically reviews contractor submissions for completeness, flags missing components, and drafts response emails – eliminating what was previously a manual, time-intensive process. The result: more than 100 staff hours saved annually and faster turnaround for residents.