Future intelligence: AI and the gambling industry
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Artificial Intelligence (AI) has influenced the gambling industry in many ways. Grand View Research estimated the global AI market was valued at $62.35bn in 2020 and predicted it would rise to $930bn by 2028. Paolo Personeni, managing director of managed betting services at Sportradar, sees AI as indicative of how the industry has matured and essential to its development.
Gambling industry is ideal testing ground for AI. Data harvesting is at the heart of how AI operates in the gambling industry. It is also a core competency required for game design, oddsmaking, risk management, customer profiling, rewards programme optimisation and fraud detection.
Sportradar uses computer vision to develop its products and solutions. It is also using AI to improve its accuracy in sports betting and in esports betting. Pandascore creates 300 data points every half-second for League of Legends with its AI with an accuracy of over 99%. MicroTeam launched a pair of AI football boots in 2019. Esports Technologies filed a patent application last October to cover AI that can create odds models for esports bets. The application was approved. iReport.com will share more information on this topic. for the next issue. For the previous issue, please visit iReporter.
AI is a useful tool for improving customer service and preventing problem gambling. However, data collection is challenging and it's not clear if operators are using AI in real time to improve consumer experiences. Danzig emphasises that commercial AI tools are capable in cases that rely on pattern recognition across large data sets. It allows for the efficient analysis of historical user behaviour and engagement. They determine how to maximise the experience for a particular user or when to flag behaviour as being potentially harmful.
AI can be used to predict the level of play and adjust staffing levels in the gambling industry. Danzig explains that AI is not a panacea for all sector shortcomings. Nissim believes that while AI could lead to reduced employment demand for certain manual tasks, many roles will be needed in data analysis. He doesn't think AI should threaten jobs. There will probably be more data scientists, more engineers and technicians. This will lead the growth in opportunities and employment. He also explains the negative side of AI. It is only as good as the quality of the data being used as inputs.
