How AI will redefine sportsbooks – and become a foundational layer for strategic growth

Daniel Netzer, chief product and technology officer at real-time sports data solutions provider LSports, explains how AI will play an integral role in the future of sports betting – and operators that fail to seize the opportunity will be left behind.


⚙️ Where AI is Making an Impact Already

AI is already embedded across several key operational areas:

1. Personalisation & Engagement

  • AI adapts sportsbook and mobile UX to user behaviour.

  • Push notifications and tailored insights cater especially to Gen Z, who expect instant, relevant, bite-sized content.

2. Odds Management & Risk Detection

  • AI helps price over 2 million events/year (vs. 100,000 in the past).

  • Used in automated odds calculation, in-play risk monitoring, and fraud detection.

3. Customer Support

  • Chatbots and AI-driven CRMs handle large volumes of interactions.

  • Improves responsiveness and consistency.


⚖️ The Human-AI Balance: Augmentation Over Automation

🔍 The Core Challenge:

Operators must strike a balance between automation and maintaining a human touch—especially given the highly regulated and trust-sensitive nature of gambling.

👤 Expert Perspective (Netzer):

“AI should be used for efficiency, and humans for empathy.”

Where AI fits best:

  • Data-heavy, time-sensitive tasks (e.g., risk analysis, flagging issues, bet settlement).

  • Scaling operations without proportional headcount increases.

🚫 Where humans are still essential:

  • VIP management, dispute resolution, compliance decisions.

  • Cultural judgment and strategic planning.


🧩 Barriers to AI Adoption in Gambling

1. Infrastructure & Legacy Systems

  • Many operators lack the data architecture needed to support AI models (e.g., unified data sources, modular systems).

  • Modernisation is a precondition for effective deployment.

2. Ethics, Regulation & Trust

  • AI use in gambling must navigate compliance, fairness, and responsible gambling.

  • There’s a real risk of reputational damage if transparency and ethical use aren’t prioritised.

3. Limited Access to Official Data

  • Exclusive data deals limit innovation and prevent open AI development.

  • Industry leaders advocate for open data ecosystems, akin to open-source AI models.


🚀 The Future: AI as a Foundational Layer

🔮 5-Year Outlook:

AI will be fully integrated across sportsbook operations: BDG Game

🏦 Operational Efficiencies:

  • Automated trading desks settling bets in real time.

  • Predictive analytics to anticipate user needs and betting patterns.

🛡️ Responsible Gambling:

  • Shifting from reactive (after harm) to proactive (early intervention).

  • AI models flag at-risk players before issues escalate.

🧾 Compliance & Reporting:

  • Automated compliance checks and real-time regulatory reporting.

  • Reduces human error and speeds up processes.


🧠 Strategic Takeaways for Operators

🔧 Future-Proofing Requirements:

  1. Cloud-native, modular architecture

  2. High-quality, unified datasets

  3. Flexible systems that allow AI plug-ins and upgrades

🧑‍💻 Talent + Trust + Tech:

  • Investment in AI-literate talent is critical.

  • Transparent deployment builds trust with users and regulators.


🧪 Cross-Industry Lessons

From Cybersecurity:

  • Blend AI automation with human trust-building.

  • Systems must be bulletproof, but humans handle the relationship.

From Healthcare:

  • Ethics and transparency in data use matter.

  • Build trust by protecting user data and proactively managing risk.


🧠 Final Word

While AI hasn’t yet transformed gambling as radically as predicted, the groundwork is being laid. Operators who:

  • Invest in infrastructure

  • Build ethically-grounded AI strategies

  • Blend AI with human expertise

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