Baseball has always prized split-second decisions. A catcher flashes signs. A hitter reads the pitcher’s grip. Managers wave runners or call for the bullpen. But this season, a quiet shift happened in clubhouses and dugouts across the majors. Players and coaches started asking large language models for advice. Right there on league-issued iPads.
The practice spread faster than anyone expected. Futurism first highlighted how hitters consulted AI chatbots before stepping to the plate. They fed the models recent at-bat data, pitcher tendencies, even weather conditions. The responses came back crisp. “This guy throws his slider away when he’s ahead in the count. Look for the fastball inside.” Some batters treated the tablets like a digital hitting coach. Instant. Private. And, for a while, allowed.
Yet the technology’s limits showed early. A June study cited in coverage found AI models performed poorly at true sports prediction. They hallucinated. They lacked real-time context. Still, the temptation proved too strong. Teams didn’t stop at hitters. They built custom apps. Those apps pulled live game data. Then they spit out suggestions on substitutions, defensive alignments, and yes, pitch calling from the dugout.
From Curiosity to Competition
The escalation caught MLB’s attention. On June 11, a memo went out from the commissioner’s office. It gave teams more than a month to adjust. The ban took effect July 16, just before the second half began. Morgan Sword, MLB’s executive vice president of baseball operations, laid it out plainly in the memo obtained by The Athletic. “In many cases, the custom tab had expanded the use of the dugout iPads beyond their originally intended purpose to include recommendations regarding substitutions, pitch calling, and other in-game decisions traditionally made by players and coaches.”
Sources told reporters as much as a third of teams had used the iPads this way. One front-office executive put it bluntly to BroBible: “Gotta stop the cheating before there’s cheating now.” The words carry weight. They suggest the line between assistance and advantage had already blurred.
But here’s where it gets complicated. MLB had permitted some customization. Teams could upload static information. Scouting reports. Pre-game notes. Anything available before first pitch. The problem arose when live data entered the mix. Real-time pitch sequencing. In-game adjustments. Suddenly the iPad wasn’t just a reference tool. It became a decision partner.
Former reliever Adam Ottavino pointed to the New York Mets’ technology use as a factor in prompting the league’s move, according to ESPN. The Mets had leaned on tech. Others followed. Innovation in baseball often starts with one club gaining an edge. Then the rest scramble to catch up. Think of the Oakland Athletics’ moneyball approach decades ago. Or the widespread adoption of defensive shifts before they were restricted.
This time the tool is different. Generative AI doesn’t just analyze numbers. It converses. It offers narrative advice. A hitter might type in specifics about a pitcher’s release point. The model responds with probabilities drawn from vast training data. Some players found it helpful for focus. Others saw it as distraction. The divide split clubhouses.
And the ban hasn’t satisfied everyone. Some front offices expressed frustration. They argue the technology simply speeds up analysis that humans already do. Why ban a tool that processes information faster? The league disagrees. Decisions on the field should come from players and coaches. Not from silicon and code. At least not yet.
The memo allows continued use of iPads for static uploads. But anything added faces review by MLB. That clause leaves little room for creative interpretation. Teams know the scrutiny will be high. Violations could bring fines or worse. No one wants to test the boundaries now.
Still, the story doesn’t end with the ban. Baseball’s relationship with technology runs deep. Video replay. Statcast tracking. Pitch clocks. Each change met resistance before becoming standard. AI could follow the same path. Just not in real time during games. Not through dugout tablets. The line has been drawn.
Experts remain skeptical of the technology’s current power. Those lab tests show AI struggles with the chaotic nature of baseball. Too many variables. Human intuition still wins. Pitchers adapt. Hitters adjust mid-at-bat. A chatbot can’t feel the tension of a full count with runners on base.
Even so, the experiments revealed something larger. Clubs hunger for any edge. In a sport where games turn on single plays, marginal gains matter. One better pitch call. One smarter substitution. Over 162 games, they add up. The AI push reflected that hunger.
What’s next? Perhaps AI moves to pre-game preparation only. Teams might analyze opponent tendencies hours before first pitch. Build detailed plans. Then leave the in-game work to humans. That compromise could satisfy both sides. Technology for study. Instinct for execution.
Or the arms race continues underground. Private devices. Off-site analysts texting suggestions. The league will watch closely. New rules often spawn new workarounds. History shows as much.
One thing feels certain. The conversation about AI in baseball has only started. Hitters once asked chatbots for pitch advice on iPads. That era lasted briefly. But the questions it raised will linger. How much help is too much? Where does preparation end and competition begin? MLB has offered one answer for now. Teams and players will spend the rest of the season testing it.
Recent coverage from Sports Business Journal notes pitch-calling sits at the center of this battle. The league appears particularly focused there. Dugout pitch calls have long drawn suspicion. Sign-stealing scandals still sting. Adding AI only heightens the concern.
So the iPads stay. But their role shrinks. Back to reference tools. The chatbots? Silenced during games. For now.
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