Artificial Intelligence (AI) and Machine Learning (ML) technology in sports is primarily known for leveraging data and enabling analytics engines which can be made available to broadcasters, sports betting operators and other outlets.

However, over the last 12 months, AI/ML has started to be implemented across a wide range of sectors in the sports industry, particularly in a bid to enhance fan engagement. 

Technologies such as HearMeCheer, a virtual reality (VR) AI application that aggregates ‘crowd noise’ from at-home fans using smartphone microphones which broadcast’s the sound in real-time inside stadiums during live games, is just one example of how this technology is looking to further integrate itself into sports.

Insider Sport spoke to Jagdish Mitra, Chief Strategy Officer and Head of Growth at Tech Mahindra, about the rise of AI/ML in the sports industry, what is seen as the next big sector for these solutions, plus the benefits and dangers of using this technology.

Mitra commented: “AI is definitely a game changer. Today, sports business is all about knowing what your fans want and delivering hyper-personalised experiences to them. AI is definitely helpful in learning what your fans’ preferences are.

There are innumerable opportunities that exist for the media and broadcast sector in terms of leveraging AI/ML. There are instances of solutions that enable the real time interweaving of relevant event data points with a live match presented to broadcasters and commentators and generating relevant anecdotes from historical events pertinent to the current live event.

“This not only enables the broadcasters to present a compelling story but also presents new ways to monetise data and content from past events. We believe that AI will not only boost revenues in this sector but also open new business models of engagement with data (and therefore intelligent information) content.”

As Mitra touched on, it seems that the industry has started to shift past using AI/ML to simply acquire data which can then be collated. Instead, solutions are being created to enhance broadcasts and to bring more instant data to enhance stories which could be told throughout a match or event.

Additionally, the technology firm’s head of growth has recently seen that in the last year AI/ML is starting to integrate itself with other sectors of the sports industry, such as sports betting and analytics. He attributed this to the use of solutions available from AI/ML to monetise leveraged data and content.

Mitra explained: “In the last 12-18 months there has been an increasing focus by multiple niche players to leverage data and content and monetise this by enabling new layers of information inference and visualisation through AI/ML and AR/VR.

“While this is predominantly being used by broadcasters and actual sporting bodies (content owners), there seems to be a trend to elevate the use of AI/ML technologies to new areas such as fan engagement, sports betting, player performance management & analytics. We believe this is an area where exponential growth is expected over the next few years.

“Sports Analytics powered by AI is expected to become a $5 billion market by 2025 and will be predominantly driven by AI engines.”

However, when handling technologies it is crucial to be aware of the risks and dangers of relying on these solutions, especially if AI/ML has hardly been implemented into the specific sector. 

Mitra highlighted that it’s imperative that a pragmatic approach should be taken when integrating AI into solutions, whilst also developing and learning more about the technology through its initial successes/failures.

“A lot of AI/ML solutions hinge on the basic premise that the data integrity and data volumes are right for an AI engine to make the right predictions,” said Tech Mahindra’s chief strategy officer.

“Investors in AI for sports need to be aware of risks of early failures and the need for continuous learning. In addition, the challenges of reliable and trustworthy data providers make it that much riskier to ensure accurate outcomes for fans and other consumers of such data. 

“A pragmatic and measured approach to AI is required to ensure that fans are able to get the right data and the technology brings home an accurate and unrivalled experience of real-time sports viewing interspersed with intelligent (read AI-based) informational anecdotes.”

To conclude, Mitra discussed how AI/ML can continue to help sports viewership through initiatives such as HearMeCheer and the integration of AR/VR during broadcasts. In a world where the stadium experience for spectators is either void or limited, it is imperative that fan engagement during match days are given more of a focus.

Mitra stated: “AI can specifically help in boosting viewership outside the stadium by engaging with fans in real time and sharing AI-driven personalised snippets of information wherever the fan might be.

“Fans can leverage real-time event insights on their favourite teams/events anywhere and be able to engage with other like-minded fans.

“AI can bring together concepts of virtual stadiums outside the physical one by bringing fans from across the globe together. They do so by learning about their past preferences and giving them the experience of being in a stadium by coupling AI with AR/VR experiences.”

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