Expert Warns Racing Leaders Of The Importance Of Properly Adopting Ai In The Next “Two To Four Years”

Expert Warns Racing Leaders Of The Importance Of Properly Adopting Ai In The Next “Two To Four Years”

Expert Warns Racing Leaders Of The Importance Of Properly Adopting Ai In The Next “Two To Four Years”

Wednesday 11 February, 2026 – Global artificial intelligence (AI) expert Mr Danilo McGarry has warned racing leaders at the 41st Asian Racing Conference in Riyadh of the importance of ensuring their organisations become ‘AI-first’ in the next “two to four years”.

Speaking on the second day of the conference at a session titled : ‘AI, Big Data And Virtual Reality’, Mr McGarry outlined his concerns around the potential for a “massive decline in the amount of interest in horse racing” should the sport not keep pace regarding AI.

“You don’t have forever to transform. I would say most of your organisations have about two to four years to transform because the people that you serve are changing and they want different things tomorrow than they did today,” he said.

“There are new sports coming up every six to 10 months. New sports that understand attention, marketing and entertainment, and they are taking the attention away from your potential new customers that would like to go and see horse racing.

“You are competing with more sports than you ever were before and this will not stop. What you do as organisations to transform the way you market and transform the way you create that immersive experience has to accelerate.

“I believe if you don’t do this over the next few years you will start to see a massive decline in the amount of interest in horse racing as new sports become interesting and market themselves better.”

Mr McGarry predicted a significant decrease in “job categories”, down from 800 to 100, in the next four years as AI grows and outlined ways organisations can embrace the technology.

These include education and building an understanding of the different forms of AI, engaging the right people to help set AI strategies, re-engineering processes with AI at the forefront and ensuring organisations use and scale AI properly.

“This is what I like to call the perfect storm. Just like any other storm, if you prepare for it correctly you will come out the other side better than everybody else. But if you don’t, and if you ignore it, you will come out the other side battered and bruised,” he said.

“I think you should look at this as an opportunity and not as a threat. It’s really important that you get really comfortable with this topic and actually start learning how it is and what it can do for your organisations and for the sport of racing, because this truly is transforming industries.”

Mr Todd Harple, Director of Innovation and Strategy, Stanford Sports Equity Lab, wondered if racing is “data-rich and somewhat insight-poor” and spoke of how AI can help people make sense of things.

Danilo McGarry, Entrepreneur, Ai Expert, Global Board Advisor, Podcaster

Todd Harple, Director of Innovation and Strategy, Stanford Sports Equity Lab

The other speaker during Wednesday’s morning session was Kitman Labs founder Mr Stephen Smith, who drew a focus to the “phenomenal changes in human performance” in the past 30 years and the lack of a proportionate progress in thoroughbreds, pointing to the fact that Secretariat still holds the record time for the Kentucky Derby in 1973.

After years of taking a data-driven approach to player performance, Mr Smith believes that “tailored data-driven equine athlete pathways could transform the industry and provide breeders and trainers with a significant advantage over competitors who are still adopting traditional approaches”.

“I think we can very, very quickly take the learnings we have taken from the human performance world and apply them to equine performance,” he added.

“We can look at progression rates from every stage of an equine athlete’s career and start to analyse the masses of information that have been collected.”

Stephen Smith, Founder, Kitman Labs

Panel Discussion

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