Undoubtedly, AI technology plays a pivotal role in the sports betting industry.
From enhancing data analysis and odds calculation to refining user experience and supporting responsible gaming, AI stands at the intersection of innovation and user satisfaction.
AI-based customer relationship management (CRM) systems can be used to analyse user behaviour, preferences and trends to personalise digital experiences for bettors. This helps sportsbooks gain an edge over the competition while keeping their clients happy.
However, while the benefits are clear, the incorporation of AI in sports betting is not without its challenges. These may range from security concerns and data privacy issues to ethical dilemmas and potential over-reliance on machine-driven predictions, all of which require careful navigation.
Generative AI versus analytical AI
When it comes to bringing AI to your sportsbook, it’s important to note that there different types of AI. The technology spans from generative AI and analytical AI to open and closed options – more on that later.
Generative AI stands out for its capacity to create new content or predictions autonomously. This produces outputs that were not part of its training data. In sports betting, this might translate into generating promotional content or simulating potential game outcomes based on complex models.
Analytical AI combs through existing data to identify patterns, correlations or anomalies. In sports betting, analytical AI can be used for odds calculations, analysing bettors’ past performance, or predicting future game results based on historical data.
Additional tools like chatbots can help bettors make better choices. They also have the added potential benefit of growing engagement through easy and entertaining text interaction. For instance, a user may inquire about the current odds for an upcoming football match. The chatbot can instantly fetch the latest odds, relevant statistics and team news, giving the bettor information to make an informed wager.
Furthermore, chatbots can engage users in casual conversation, answering queries about sports events or even explaining betting rules. These interactions can save users time searching for data and keep them engaged with the sportsbook’s platform. This then increases the likelihood of placing bets.
Downsides and challenges
As this technology continues to improve, operators should consider some of the significant issues AI presents in sports betting.
As stated earlier, AI isn’t just generative or analytical. It’s also open or closed. In a closed AI model, the technology’s algorithm is private; a model that some call a “black box”. In an open AI model, the algorithm is open source, meaning that – like open source software – the AI’s learning model can be accessed by anyone on the internet.
Open AI could pose a threat to the safety and privacy of bettors. AI models can learn and remember specific data points, meaning that, if they are open source, users’ sensitive personal information – like financial data – could be included in the code. This could put bettors at risk. Additionally, algorithms themselves are fallible. Since they’re made by humans, AI models can reflect human biases, which can impact the accuracy of predictions and, eventually, the fairness of betting practices.
As such, closed AI models are preferred to ensure the privacy of all data that sportsbooks aggregate and manage. Although open AI is more cost-efficient and flexible, closed AI will offer security and privacy for all customers and support your business with bespoke solutions.
Ethical considerations and impact on responsible gambling
Unfortunately, the closed AI option isn’t as simple as it appears. While it will maintain the privacy of your users’ personal information, it’s possible that a closed AI algorithm could make bettors trust your platform less. As a result, what users see as a lack of transparency could decrease customer loyalty over time.
There are also ethical concerns when it comes to AI and sports betting, particularly as their predictive capabilities can inadvertently fuel addictive behaviours. Honing in on a user’s preferences and habits, these systems can amplify the urge to gamble beyond one’s means, sidestepping the industry’s commitment to responsible gaming.
Limitations and weak points
Although AI is created by humans, the algorithm cannot match the human side of sports betting, from bettors’ intuition to athletes’ year-to-year (or even week-to-week) performances. AI’s reliance on historical data to make predictions could lead to misleading predictions for bettors, as it does not leave room for the nuances of human judgment or gameplay. Emotions and situational awareness are key factors in sports betting, neither of which can be replicated or replaced by AI technology.
To meet compliance requirements and maintain the security of user data, sportsbooks must adhere to data protection regulations, such as GDPR. As AI continues to evolve, ensuring sustained compliance for your sportsbook will require constant attention. This could also be particularly challenging in the US, where sports betting is highly regulated and rules vary between states.
While AI is indeed a game-changer for sports betting, brimming with untapped potential, it’s necessary to recognise and mitigate its challenges and risks.
In the second part of this series, I will examine a few strategies that sportsbooks can employ to optimise AI’s capabilities and harness its full power.