Neural Notes: How AI is transforming the business of sport

Welcome back to Neural Notes, a weekly column where I look at some of the most interesting AI news of the week. In this edition, I’m gratuitously capitalising on the Olympics by taking a look at how AI is being used on the commercial side of sports.

AI-powered analytics and data are increasingly used to enhance performance and strategic decision-making in sport.

The NBA and Premier League leverage AI through Second Spectrum to analyse performance data such as player movements, shooting accuracy and fatigue levels in real time. This allows them to pivot their strategies and make informed decisions regarding subs and play calling in-game.

It also provides data, personalisation options and augmentation viewing to fans via their apps.

In Formula 1, AI now plays a crucial role in race strategy and performance optimisation. Teams use AI to process car telemetry data during races, including information on tyre wear, fuel levels and engine performance.

This means engineers can make decisions around pit stops, tyre management and overall race tactics.

This is the sexy side of AI in sport. It’s performance-enhancing, fun use of tech, and increasingly visible. In F1 in particular, fans are able to access a chunk of race and driver data in real-time.

For the more technical and those who want to dive deeper, Github is a rich source of data that fans can use to build their own analytics tools.

But what about the logistics behind the sports themselves?

Su Jella is the director of data and insights at Tennis Australia and a recent winner of the Women in AI APAC awards. Jella is an expert in the use of AI-driven analytics to improve business operations and fan engagement.

Which is another way to say: the things that help bring money into sports.

AI and the fan experience

AI is becoming increasingly important in how fans personally experience sports in stadiums and on their devices.

“AI is used very much from an automation capability to provide real-time alerts, real-time information to businesses, but also provide experiences that can really enhance the way customers consume their events, services or products,” Jella tells SmartCompany.

She emphasises the role of computer vision in harnessing AI capabilities: “Computer vision has a lot to do with how people interact in a human environment where there’s a lot of movement and experiences being delivered”.

As we move closer towards smart stadiums, there will be more ways to increase the level of service and hospitality through AI and technology in general.

“Imagine ordering your food via an app and having it delivered to your seat, minimising the time away from watching the game,” Jella said.

I don’t have to imagine.

I had this exact experience in Yankee Stadium just last year. Uber Eats was trialling direct-to-seat delivery for both food and merchandise.

I did cheekily ask whether this theoretically meant you could order outside food into the stadium. I was already imagining having an Indian Home Diner kebab (IYKYK) kebab delivered to Allianz Stadium. But I was quickly informed that geofencing prevents this from happening.

And so I opted for a comically large hot dog, a questionable blue slushie, and an Aaron Judge jersey.

In the spirit of comparison, someone else in our group headed to a food stand to see how long each service would take.

My order arrived in 5:07 minutes. My colleague took 23:09 minutes and missed a home run during their absence.

I’m all for scrutinising new tech, but I had to admit that the significantly reduced wait time and ability to not miss any of the game, was impressive.

Jella also highlights how AI can enhance real-time interactions and engagement.

“If you are perhaps having a prize or a competition taking place at the same time within that stadium or arena, you can make that a lot more interactive from an AI perspective. You can have prizes delivered in real-time, know who your customers are, and use computer vision data to enhance that experience,” she explains.

But it’s not just about the in-person experience. AI is also changing the way fans interact with the game beyond the stadium.

In recent years IBM’s Watson AI has been used to provide fans with real-time insights and personalised content through the official Wimbledon app. This included match highlights, player statistics, and even predictive analytics to suggest which matches would be the most exciting to watch.

This level of personalisation ensures fans are more connected to the sport, regardless of their physical location.

But to get the most out of these immersive experiences for fans, Jella points out the need for more connectivity.

“If you look at the Olympics, there’s a lot of matches, tournaments and activities happening at the same time. One person cannot obviously see all of it,” she says.

“I could be watching a swimming event now, but I do want to know what’s happening in hockey. So how do I get that information across to myself really quickly, really easily?”

According to Jella, there needs to be a significant enhancement from 5G to 6G to provide deeply immersive experiences.

“We already see it with mobile technology. We see it a lot where it’s becoming a lot more interactive and immersive in the way we use our phones. It’s basically your entire life in your pocket,” she says.

“And that’s how entertainment itself is going to also change – having the experience in your pocket, in the palm of your hand – and being able to make decisions on the go for situations or events and activities like that.”

AI and operation efficiencies in sports

AI is also weaving its way into the operational side of sports. From managing peak crowd flows during major events to ensuring adequate stock levels for concessions, AI-driven insights help streamline operations and enhance overall efficiency. And that means boosting revenue.

“[Sports organisations] can use AI on different levels during peak periods – as well as outside of peak periods – to really help manage data from its overall chaotic format into a more structured format that can be analysed and then be provided from a point of recommendation and insight back into business decision-making,” Jella says.

“It’s the way we enhance that very technologically innovative way customers consume the actual event. A lot of it has to do with real-time.”

A notable example of AI enhancing operational efficiencies and security is the use of AI-powered crowd management systems at the Mercedes-Benz Stadium in Atlanta.

These systems analyse data from various sensors and cameras to predict crowd movements and optimise resource allocation, such as directing cleaning crews to high-traffic areas and adjusting staffing levels at concession stands during peak times.

“AI provides real-time information that helps businesses make immediate adjustments. Managing peak periods in stadiums becomes much more efficient with AI predicting when and where crowds will move, ensuring resources are optimally allocated,” Jella says.

She also sees the importance of this beyond the literal and figurative sporting arenas.

“What I do see happening in the future is the ability to automate processes. That’s going to be within any business, regardless of being in sport or in entertainment. The level of automation you can deliver within the organisation is crucial,” Jella says.

She also points out the need for infrastructure, as well as ethical governance, to support AI’s growth in the business sector.

“There’s a huge infrastructure piece that we have to think about as well. Do organisations have the right cloud platforms in place to actually manipulate and build and deliver models?” Jella says.

“There will [also] be a growing need to embed human-in-the-loop practices that will drive AI governance and ethics as organisations grow to embed AI models and practices. Teams will be further diversified to have skills and knowledge that address these gaps.”

Never miss a story: sign up to SmartCompany’s free daily newsletter and find our best stories on LinkedIn.