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The gap in personalization and AI adoption in sportsbooks compared to tech leaders like Netflix or Amazon is a clear pain point. While automation is widespread, many critical trading functions still rely on human intelligence embedded in software rules rather than dynamic machine learning.
This reliance on hardcoded rules often means risk assessment focuses narrowly on the 3–5% of «root customers» who cause damage, overlooking the 95% of profitable players and the opportunities to optimize across the broader market.
The modern sports betting industry is at a pivotal crossroads. The real challenge lies not in the availability of algorithms but in how operators choose to deploy them.
Many core sportsbook functions—from automated pricing to risk assessment—are already handled by sophisticated systems. Yet, as discussed in our recent webinar «There’s No AI in Sportsbook (Yet): Why the Industry Is Behind, and How AI Will Redefine the Game«, these systems often depend on hardcoded rules rather than dynamic AI.
The result is a narrow focus on minimizing risk from the small fraction of damaging customers while missing opportunities to enhance profits across the majority of players, who also often cross-sell into casino products.
To truly unlock AI’s potential, sportsbooks must adopt a mindset shift. One provocative insight from the webinar emphasized embracing the sharps—expert bettors who exploit weak lines—as part of the system’s learning process.
Traditionally viewed as a liability, sharps can act as a real-time feedback loop, helping to balance odds and spot anomalies faster than internal systems alone. For instance, if a sportsbook only offers overs on volatile markets like shots on target, it misses the chance to learn from bets on the unders.
The message is clear: operators may need to sustain temporary losses—essentially “paying customers”—if it provides valuable data to refine AI models. This approach, known as testing in production, uses high-volume, informed bets to improve accuracy, adaptability, and operational excellence.
While speed and data accuracy remain crucial, the next frontier is a philosophy where competitive market interactions drive risk system evolution. The true edge belongs to the operator who learns from every single bet, no matter how sharp the customer.
For more insights on the future of data and AI in sports betting, watch the full webinar – There’s No AI in Sportsbook (Yet): Why the Industry Is Behind, and How AI Will Redefine the Game.
