The sports industry is talking more than ever about artificial intelligence. From performance analysis to fan engagement and operational efficiency, AI is seen as a key driver of the future.
But there is a fundamental problem that is often overlooked.
Before AI can create value, sports organizations need to fix their data.
This was one of the key insights shared by GSIC member Darrick “DJ” Johnson, Founder and CEO of Sherpa Sports AI, in the first episode of the GSIC Podcast.
A Fragmented Industry
Unlike other industries, sports organizations have historically operated with disconnected systems.
Scouting platforms, contract management tools, financial systems, and performance data often exist in silos, making it difficult to build a unified view of operations.
As DJ explains:
“Something that I noticed early on in my career was how fragmented these systems were. In other industries, companies integrate their tools. Sports wasn’t that way.”
This fragmentation creates inefficiencies not only for organizations, but also for athletes, coaches, and front office teams.
Why the Problem Still Exists
One of the reasons this issue persists is structural.
For many years, sports organizations relied on “one-size-fits-all” software solutions that did not allow customization or integration.
Without real competition or pressure to innovate, many organizations simply adapted to the limitations of available tools.
At the same time, expectations have changed.
Today, clubs, federations, and leagues want to:
- leverage artificial intelligence
- improve decision-making
- personalize fan experiences
- optimize operations
However, as DJ points out:
“You can’t run AI applications if your infrastructure is not ready.”
Data First, AI Later
One of the most important messages from the conversation is simple but critical:
“AI is only as good as the data it pulls from.”
For sports organizations, this means that the first step is not adopting AI tools — it is understanding and organizing their data.
According to DJ, organizations should start by:
- Identifying all existing data sources
- Bringing them into a unified view
- Defining the outcomes they want to achieve
- Building a technology strategy from there
Only then can AI deliver real value.
The Opportunity Ahead
Despite the current challenges, the outlook is optimistic.
The sports industry is now going through a transformation similar to what other sectors — like banking or healthcare — experienced in previous years.
New technologies, cloud platforms, and specialized solutions are creating a path forward.
At the same time, organizations are becoming more aware of the importance of owning and leveraging their data.
Looking ahead, DJ highlights a clear trend:
- organizations will increasingly own their data
- technology will become more modular and integrated
- AI will become a core part of decision-making
And most importantly:
“The early adopters in the sports industry of AI will be the winners.”
From Conversation to Action
At GSIC, these types of conversations are key to understanding where the industry is heading — and where real opportunities lie.
The challenge is no longer whether AI will transform sports.
The real question is:
Are organizations ready to support it?
