The Winning Sports Organisations Won’t Be the Ones That Adopt AI First

There is a lot of chatter online about how AI will shape the future of sport. Some of it will probably be right, but a lot of it will not.

What I see first-hand, speaking with coaches and people working inside professional sporting organisations, is much more practical. Most people know AI is going to be important. They know their competitors are looking at it, they know they probably need to be doing something, but many are still trying to understand what that something should actually be.

That challenge is made harder by the reality of elite sport. Coaches have very little time, particularly during the season. Everything revolves around the next game. If the game is being played at 7pm on Saturday, nobody is moving kickoff because the club has just introduced a new piece of technology that takes three weeks for the staff to understand.

That makes getting new technology adopted inside a professional sports organisation incredibly difficult.

At the same time, almost every major sporting organisation in the world is now investing in, experimenting with, or at least discussing AI.

The danger is adopting technology because it looks like the future, rather than because it supports the long-term strategy of the organisation.

A team can feel like it is charging into the future with a new AI platform, only to discover two years later that the map it was given sent it in completely the wrong direction.

That can be expensive, but the bigger problem is that it damages trust.

Coaches are already sceptical about new technology coming into the building, and understandably so. Professional sports teams are constantly approached by companies promising the next breakthrough in recruitment, performance, medical, analytics or player development. Many of those companies will not exist in a few years.

So why should a coach automatically trust the next one?

Trust in elite sport has to be earned.

This is why I believe the smartest AI companies, and the smartest sporting organisations, will start with something proven. They will start with science, evidence, a methodology or a process that already works, and then ask how AI can make that process faster, easier or more powerful.

That is very different from starting with AI and then trying to use it to prove that an idea or product works.

One approach uses AI to amplify something valuable. The other asks the customer to take a leap of faith.

In elite sport, that is a risky proposition.

AI is not a strategy

Another mistake I see is organisations talking about having an “AI strategy”.

AI itself is not a strategy.

The strategy should be about winning, recruiting better players, developing athletes faster, reducing injuries, improving coaching, understanding opponents or making better decisions.

AI is simply another tool that can help an organisation achieve those outcomes.

That means the first question a sporting organisation should ask should not be, “Which AI platform should we buy?”

It should be, “What problem are we actually trying to solve?”

If an organisation cannot answer that question clearly, buying more technology is unlikely to solve the problem.

If a club already understands its philosophy, processes and what good looks like, AI can become incredibly powerful. It can add speed, identify patterns, reduce administrative work and surface information that might otherwise be missed.

What it cannot do is replace strategy, preparation or good coaching.

Humans still coach humans

I firmly believe that humans will continue to coach humans.

Great coaches are not great simply because they have access to more data. They are great because they understand people. They build trust, communicate clearly, recognise what motivates different players and know when someone needs to be challenged or supported.

AI should not replace that. It should help those people make better decisions.

One of the simplest ways to think about AI is as a very smart intern.

Imagine an intern joins your organisation tomorrow. They can read thousands of documents, analyse enormous amounts of information, work extremely quickly and produce an answer in seconds.

Would you immediately allow that intern to make your most important decisions?

Of course not.

You would give them work, check it, correct mistakes and teach them how your organisation operates. Over time, as they proved themselves, you would give them more responsibility.

AI should initially be treated in much the same way.

The technology is learning, but organisations also need to learn how to use the technology properly. That relationship takes time, and trust grows through repeated evidence that the technology is helping rather than getting in the way.

The forgotten part: implementation

The other major part of AI adoption that does not receive enough attention is implementation.

From the outside, a sporting organisation can look like one cohesive unit. The coaches, players, performance staff, recruitment team, medical department, analysts and executives all wear the same badge.

That does not mean they all think the same way.

Resistance to change exists in professional sport just as much as it does in the corporate world. People worry about established routines being disrupted, about new systems creating more work, and increasingly about whether AI will eventually threaten their role.

This is why implementation and handholding are so important.

You can build the most sophisticated AI product in the world, but if the coaching staff stop opening it after three weeks, it is worthless.

New technology has to fit into the lives and workflows of the people who are expected to use it.

The best AI tools will not force coaches to completely change the way they work. They will reduce friction, save time, surface useful information and gradually become something staff do not want to work without.

That is when technology becomes embedded inside an organisation rather than becoming another platform that sits unused on a laptop.

What should sporting organisations be asking?

Before adopting another AI product, I think every organisation should ask itself a few simple questions.

What problem are we actually trying to solve?

What evidence exists that the underlying product, methodology or idea works?

How does this fit within our existing sporting philosophy and strategy?

Will our coaches and staff realistically use it?

Can the people making decisions understand why the AI is making a particular recommendation?

If those questions do not have convincing answers, the technology probably is not ready to be inside the building.

Ultimately, the sporting organisations that succeed with AI will not necessarily be the organisations using the most AI.

They will be the organisations with the clearest strategy, the best people, the strongest decision-making processes and proven systems that technology can enhance.

AI should sit underneath all of that, quietly helping good people become better at what they already do.

The question for sporting organisations should not be, “How much AI are we using?”

It should be, “Are we making better decisions because of it?”