LSports' Chief Product and Technology Officer, Daniel Netzer, recently discussed the crucial role of artificial intelligence in the future of sports betting, noting that operators who fail to seize AI opportunities will face the risk of elimination. Although the application of AI in the betting industry is still in its early stages, the global market is expected to grow from $189 billion in 2023 to $4.8 trillion by 2033, with the demand for AI-assisted decision-making among young bettors growing rapidly, indicating that AI will become the foundational layer for strategic development in sports betting.
Current Status and Challenges of AI Applications
Although artificial intelligence technology has swept through the gambling and gaming fields and is widely considered crucial for a range of business operations from marketing to odds management, the application of AI in the betting industry has been relatively slow. A Gartner survey shows that while most CEOs see AI as a potential transformation tool, about two-thirds of companies have not yet established operational and business models suitable for an AI-driven world.
Research from MIT shows that currently, only about 5% of AI pilot projects have achieved significant revenue growth, with most projects having limited impact on profits. This reflects the challenges and complexities faced by AI technology in practical applications.
Market Demand and Growth Drivers
The United Nations Conference on Trade and Development predicts that the global AI market size will increase 25-fold over the next decade, soaring from $189 billion in 2023 to $4.8 trillion by 2033. This growth trend is also evident in the sports betting sector.
A YouGov study found that one-third of bettors aged 18 to 34 used AI-assisted gambling decisions in the past year, with another 19% considering its use. 43% of young bettors indicated they might use AI for betting decisions in the next 12 months, a trend that also reaches 25% among the 35 to 54 age group.
Technology Applications and Implementation Scenarios
As a provider of real-time sports data solutions, LSports has observed significant growth in AI demand. Its quarterly report shows that global sports betting data consumption has grown by 19% year-over-year, mainly driven by emerging leagues and esports.
Netzer pointed out that AI has been applied in multiple areas of the betting industry: "From player engagement and personalization to adaptive sports betting and mobile applications. At LSports, we apply AI to transaction operations, fraud detection, and the automation of high-capacity tasks."
Human-Machine Collaboration and Best Practices
Netzer emphasized that AI in sports betting will not completely replace traditional manual systems but will form an optimal model of human-machine collaboration. "The risk of relying entirely on automation is too high. The expertise of traders and risk managers cannot be replaced by AI overnight."
He believes the ideal balance is "using AI to improve efficiency and using humans to generate empathy," with AI handling data-intensive tasks and humans focusing on relationship-driven work, such as VIP management, dispute resolution, and strategic decisions requiring ethical judgment.
Future Development and Industry Trends
Netzer predicts that within five years, AI will "be embedded at every level of sports betting," from millisecond-level settlement automated trading desks to highly personalized customer journeys. Responsible gambling will also shift from passive response to predictive intervention, enabling operators to identify high-risk players early.
Compliance work will be automated, reducing errors and improving reporting mechanisms. As augmented reality and virtual reality technologies advance, AI will serve as an "invisible co-pilot" providing a more immersive fan experience.
Implementation Recommendations and Success Factors
For sports betting companies planning to adopt AI, Netzer recommends ensuring a flexible, data-rich infrastructure. "Operators need a unified data source, high-quality data, cloud-based architecture, and modular systems."
He cites the cybersecurity and healthcare industries as examples of how to successfully address similar challenges: "Operators can build trust through responsible practices, ensuring data security, strict compliance, and customer protection."
Industry Transformation and Innovation Opportunities
Netzer believes that removing restrictions on official data rights will be an important step, bringing opportunities for innovation. He compares it to the innovation driven by the open-source model in the generative AI field: "In just six months, its progress is equivalent to a decade of advancement in other technologies."
As the next generation of solutions emerges, AI will become the foundational layer of every sports betting strategy, from pricing models and personalization to real-time engagement and predictive analysis, reshaping the industry landscape.
