Major League Baseball’s (MLB) move to restrict dugout iPad functionality is a reminder that AI governance is showing up everywhere, including in the middle of professional baseball games. According to reports, MLB disabled custom tablet tabs after concerns that teams were using AI-powered tools to support real-time decisions on substitutions, pitch calling, and other in-game strategy. The league’s concern appears less about technology generally, and more about preserving the line between permitted data access and automated strategic recommendations during live competition.

That line matters. Sports have always evolved with analytics, video, scouting systems, and performance data, but AI changes the speed, scale, and nature of decision support. A tool that helps a team review video before a game feels very different from one that recommends the next pitch in real time. Once AI starts influencing live decisions, leagues must answer harder questions: What tools are fair? What level of automation is acceptable? Who is accountable for the decision? And how can rules keep pace when technology moves faster than the rulebook?

The takeaway extends well beyond baseball. Organizations adopting AI need clear use-case boundaries, not just broad permission to “use technology.” MLB’s crackdown shows why governance must be specific: what the system can access, when it can be used, who can rely on it, and which decisions must remain human-led. Whether the setting is a dugout, a trading desk, a hospital, or a hiring situation, the same principle applies: AI may be powerful, but without thoughtful guardrails, it can quickly move from helpful tool to rule-changing force.