The Spurs' AI Playbook: How San Antonio Turned ChatGPT Into a Competitive Edge

The San Antonio Spurs didn’t adopt AI because it was trendy. They adopted it to win, on the court and in the front office. CEO RC Buford said it plainly: "We were looking to create real competitive advantages… and free our brilliant minds to tackle bigger problems."

What They’ve Achieved in Six Months

• 1,800 staff hours saved every month. That’s 21,600 hours a year, the equivalent of 10 full-time roles now redeployed to higher-value work.

• AI fluency up from 14% to 85% across the organization.

• 94% of employees feel more confident using AI daily.

How They Did It

1. People-first rollout. Director of Innovation Charlie Kurian piloted ChatGPT with 150 volunteers, paired live training with hackathons, and let demand grow organically. Adoption "pulled" itself rather than being forced.

2. Purpose-built GPTs:

   • Fan Voice GPT crunches thousands of post-game comments in minutes, flagging sentiment swings.

   • Transformative Leadership GPT localizes training content for global programs in hours instead of weeks.

   • Counterfeit Merchandise GPT scans resale listings to protect brand integrity.

3. Culture over tools. Every GPT is anchored in the club’s long-standing "Pound the Rock" mindset: small, deliberate improvements that compound.

Three Lessons for Enterprise Leaders

1. Start with human pull, not tech push. Train early adopters, celebrate quick wins, and let curiosity spread AI fluency.

2. Measure in business hours, not pilot counts. Converting time saved into strategic capacity: 10 FTEs for the Spurs, resonates in the C-suite.

3. Let functional leaders own use cases. Marketing built sentiment bots, retail tackled counterfeits, L&D redesigned workshops. Distributed creation keeps solutions relevant and sticky.

What Executives in Other Industries Can Learn

The Spurs remind us that competitive advantage flows from culture, clarity, and courage. Culture that rewards experimentation, clarity about the business metric each model must move, and courage to walk away when a tool or workflow is not the right fit. Follow that playbook and the score takes care of itself.

Check out the OpenAI case study and video for the full play-by-play →