A professional soccer coach’s recent admission that he uses AI to shape tactical decisions is a major change for the sports industry. Seattle Reign FC (NWSL) head coach Laura Harvey is probably not the first coach to use ChatGPT to gain an on-field advantage, but she may be the first to openly admit it. What does your organization need to know about this latest development in the evolution of the sport, and what should you do to keep up with your opponents?
Seattle coach leans into AI and gets results
Coach Laura Harvey recently said, soccer-like On the podcast, she shared how she used ChatGPT for tactical experiments in the field. Specifically, I explained that you start by typing a prompt such as “What is Seattle Reign?” But then the question moved on to “What formation should I play to beat NWSL teams?” The coach, who won the NWSL’s Coach of the Year award three times this year, said the AI suggested his team adopt a “back five” defensive formation against two specific opponents.
She emphasized that AI did it, but do not have Providing detailed playing instructions (“They didn’t tell me how to play or what to do in it”), she and the coaching staff investigated the suggestions, introduced new formations and reported improved match results.
The Reign finished near the bottom of the league in 2024, but are sitting in fourth place in 2025 heading into their final season. Does that suggest that the tactical changes recommended by the AI may have contributed to the recent rise in rankings?
Extensive AI applications in sports
Here’s how AI is being implemented in three key areas relevant to sports industry executives.
game tactics and strategy
AI is ideal for ingesting large amounts of historical real-time match data and simulating multiple scenarios to support tactical decision-making (e.g. predicting opponent strategies, simulating formations, etc.). In fact, a 2024 academic paper details how football clubs can harness the power of AI.
According to the study, the AI model worked with elite soccer clubs to recommend formation adjustments (corner kick routines, opposition counter tactics) and in tests performed up to 90% better than traditional setups. In fact, many clubs use “collective dynamic” models to track movement patterns and inform in-game adjustments.
Player personnel management and recruitment
You can use AI to filter and identify potential talent. A recent article describes how national athletic programs and Google Cloud partnered to analyze decades of scouting reports to uncover hidden gems. More interestingly, research on “blind scouting” shows that AI can anonymize players to reduce human bias and focus scouting attention on tactical and technical merits rather than physical characteristics.
Scouting industry sources claim that up to 65% of professional scouts at the highest level in English football believe AI will impact their roles within five years. What does this mean for the industry? AI technology has the power to extend reach, accelerate filtering and support the ROI of talent investments, especially for clubs with limited budgets. This helps transform scouting and recruiting from a “gut feeling” model to one that leverages augmented intelligence.
Health, load management, longevity
AI is increasingly being applied to training and sports science. Combine GPS tracking, biometrics, and genomics to predict injury risk and optimize return-to-game scenarios. According to reports, clubs are already leveraging AI to manage external loads. This technology is optimized to monitor metabolic and immune markers to help athletes stay healthy even on tight schedules.
Best practice tips for executives
If you’re leading a club, league or technology provider entering a new era, here are some recommendations to ensure you implement AI into your sports strategy in a responsible and effective way.
Define clear use cases and value metrics
- Start small. Instead of “let’s let the AI choose the entire game plan”, it’s better to start with a simulation of your next opponent’s formation.
- Establish KPIs. Would you like to see changes in scores and goals in games over a period of time, improved substitution success rates, fewer injury days, or more consistent changes in recruitment rates?
Incorporate human-machine workflows (not “machines replace coaches”)
- Make sure the coach/GM remains the focal point. AI should support human judgment, not replace it.
- Create a “tactical validation loop.” AI suggests options, coaches and staff evaluate them, and humans adapt and personalize them before implementing them on the field. Harvey said she and her staff “thoroughly considered” the AI proposal to see how it would fit with the team and the game itself before deciding to implement it.
- Maintain trust and buy-in in coaching by positioning AI as an “assistant” rather than a decision maker.
Invest in data infrastructure and orchestration
- High-quality data (player tracking, opponent video, performance logs) is a prerequisite. Without clean input, AI recommendations will be weak.
- Connecting tactical, performance, and recruiting data systems allows information to flow to all areas and provides shared insights.
- Remember, Seattle’s use of AI-powered formations required the coaching staff to “dig deep” into the way it played. Data alone is not enough.
Keeping good governance, transparency and ethics in mind
- Be clear about your limitations. AI models make predictions, but they aren’t perfect. Treat them like probabilistic Support tools.
- Address bias and privacy issues before integrating AI solutions into your organization. Make sure you have an ethical framework in place, especially for scouting and biometric applications.
- Protect your data. It is unique and has its own value. Please take all necessary steps to protect yourself from competitors.
Carefully scale innovation
- Try out AI tactics in low-risk situations (such as small tactical changes, training simulations, etc.) before investing large budgets or making public claims. have a good time Proof of concept before full deployment.
- Monitor the operational impact of the new model. Are your staff actually using your AI suggestions? Has the implementation changed your decision-making workflow? Are your players skeptical of your use of AI and need to be educated on how and why?
- Encourage cultural change. Success is not just about technology adoption, it also requires experimentation and a mindset of continuous innovation.
- Stay on top of developments in AI, especially given how quickly it changes and improves. Must understand and be willing to experiment with the latest AI products. Because we know our competitors will.
Consider your communications and branding strategy
- Disclosures like Harvey’s use of ChatGPT are double-edged at this point. It signals innovation, but it also invites scrutiny from people who don’t understand or trust AI.
- Prepare internal and external communication strategies. Players and staff need to understand how AI is being used, what it doesn’t do, and how it fits into the team’s strategy. And we need to consider how best to get information out to the public so we can control the narrative.
