Future intelligence: AI and the gambling industry
As casino capabilities evolve, so too does the need for the latest technological advancements to make the market bigger, better and more attractive to players. One of the fastest-growing areas is artificial intelligence, a process in which software is programmed to perform human tasks. By Marese O'Hagan
Artificial Intelligence (AI) has influenced how the gambling industry operates in multiple ways. It has widened the industry’s horizons, creating an environment where machine-operated capabilities are almost limitless.
Practically every area of the industry takes advantage of the applications of AI, from developers creating games to operators monitoring customer play.
AI is also changing how the world develops outside the industry, becoming a key component of self-driving cars and medical advancements.
Last year, Grand View Research estimated the global AI market was valued at $62.35bn in 2020, and predicted that this would rise to more than $930bn by 2028.
Reflecting on recent years, Paolo Personeni, managing director of managed betting services at Sportradar, sees AI as indicative of how the industry has matured and essential to its ongoing development.
“Our industry has undergone significant digital transformation in the past five years and artificial intelligence has been critical in its evolution,” he says. “[It] is an essential component of product development.”
It could be argued that the gambling industry is an ideal testing ground for AI. AI functions through harvesting data, which allows it to analyse statistics and occurrences to continually improve upon its accuracy.
And data is at the heart of how AI operates in the gambling industry, as Lloyd Danzig, founder and managing partner at Sharp Alpha Advisors, points out. “The gambling industry relies heavily on the leveraging of historical data to anticipate future outcomes and behaviours,” says Danzig.
“This is a core competency required for game design, oddsmaking, risk management, customer profiling, rewards programme optimisation and fraud detection.”
Aiming for the goal
AI’s use in sports betting is particularly key, says Personeni, as an asset to ensure Sportradar’s products and solutions are as accurate as possible. “For Sportradar, one of our core focus areas is on utilising machine and deep learning to develop exceptional computer vision capabilities, which is a form of artificial intelligence that teaches models to interpret and understand videos and images,” he explains.
“While we, as individuals, are very good at understanding what is happening in front of us at sporting events, we have limited capacity in the amount of data we can manually interpret, record digitally and upload.”
This can lead to AI picking up on specific aspects of gameplay, which Personeni sees as a bonus for customers.
“Computer vision provides a hundred-fold increase in the level of statistics and data that we can produce and then feed into our products and services that we offer to our clients,” he says.
“For example, by calculating velocities and trajectories of players we can predict when players will go offside or predict when an attack is mounting.”
AI that goes further than data crunching, focusing on to-the-minute information, is already being used in sports betting and esports betting.
Real-time AI is the top choice for these areas, wherein data providers must provide the most up-to-date information on gameplay. Pandascore CEO Flavien Guillocheau revealed last year that the operator creates 300 data points every half-second for League of Legends with its AI, with an accuracy of over 99%.