Are you using AI, or working with AI?
The question is no longer whether AI is being used, but whether the organization has built a shared way of working around it. The organizations that do this deliberately and systematically will be the ones that succeed on their commercial growth journey.
A question worth raising in the leadership team
We meet a lot of elite sports organizations, and AI comes up constantly when we discuss their digitalization and commercial development. When we ask how their people, or more importantly the organization as a whole, work with AI, the answer is often "we don't have an overarching strategy". Questions like: Where does the information people paste in end up, and how does the next person benefit from what the last one learned? Which AI-native tools are you using? How do your systems feed each other? tend to get vague answers. Our impression is that many employees are still using different tools, some on personal accounts and some on free plans, and many of them start from scratch every day.
That's why we want to pose a question we believe more leadership teams in sport need to take a position on. Are you using AI, or are you working with AI? The difference may sound small, but it determines whether the impact stays with individual employees or becomes part of the organization's knowledge and intellectual property.
From individual users to a shared way of working
People in sports organizations often wear several hats at once, matchdays and seasonal peaks dictate the calendar, and a large share of working time goes into keeping every stakeholder happy. In that reality, time is the scarcest resource, and that's exactly why AI is so valuable when it's used the right way.
When each employee uses tools in isolation, nothing scales. Knowledge of what produces good results tends to sit with whoever figured it out through trial and error. Quality varies depending on who wrote the prompt. And when member data, partner agreements or internal documents end up in tools the organization hasn't approved, questions about data protection and GDPR arise.
A structured way of working turns this around. The organization chooses together, builds together and learns together. Every improvement then becomes an asset for everyone, not just for the person who created it.
Have you chosen your platforms, or have the platforms chosen you?
Anyone who has followed our work knows we often point out how system choices in sport tend to be driven by vendors' sales pitches rather than the organization's actual needs. In our view, the same pattern is playing out with AI. New models and services are launched at a pace that makes it hard to keep up, and whichever tool happened to show up first easily becomes the one people use.
We recommend treating the choice of AI platform like any other strategic system decision. Start from your needs, then evaluate different models and platforms together with the people who will actually use them. Can you build shared projects with shared context? How well does it work with the tools you already use for documents, email, CRM and marketing automation? Where is your data stored, and who has access to it? What will it cost over time once the whole organization is on board, and how easy is it to switch if circumstances change?
Once the decision is made, buy licenses for one or more shared platforms for everyone who needs them. It's a cost you need to weigh up, but the alternative is a patchwork of personal accounts where the organization has neither control over the information nor the ability to build on what works.
Context is where the real efficiency gains are
In our experience, this is where the greatest untapped potential lies. Most people using AI on their own start every conversation by explaining who they are, which organization they represent, who the text is for, what tone to use and what the output should look like. That takes time, and the result is still often generic because the tool lacks the background a colleague would have had.
Today's AI platforms make it possible to gather that background in projects with clearly defined context. That's where you put your brand platform and tone of voice, your target audiences, your ticketing, membership and partnership offers, the season's key dates, templates for recurring documents and the knowledge that would otherwise be scattered across inboxes and folders. Once that's in place, a short prompt is enough to get a draft that already sounds like your organization. A newsletter to season ticket holders ahead of the derby, a follow-up after a partner meeting or a reply to a member asking about their renewal then takes one sentence instead of half a page.
The impact goes beyond the time saved per task. Everyone gets the same starting point on information, tone and brand, and new starters write in the club's voice from their very first week. When something changes, such as a new partner, a new offer or an adjusted tone of voice, the context is updated in one place and flows through to everything produced from then on.
Context needs to be managed like any other business-critical asset, with a clear owner and routines for keeping it up to date. AI is only ever as good as the data and context it has access to.
It all starts with data control
An AI platform that sits in isolation from the rest of the business only realizes part of its potential. If documents live in local folders, information about fans and partners is scattered across systems that can't be connected, and work happens by copying text back and forth, AI becomes just another tool alongside all the others.
The real impact comes when the whole chain connects. When documents, calendar, email, CRM and marketing automation live in tools that can be connected to the AI platform in a controlled way, AI can work with real information. That's why part of our work is helping organizations move to tools that support AI use, with clear rules on what information may be used and by whom.
It's the same principle that runs through everything we do. Whoever owns and controls their own data is also in a position to use it, with or without AI.
The time you free up needs a purpose
There's a misconception that AI is about doing the same work with fewer people. That's not how we see it, and in our view it's not what sport needs either. In an industry where revenue goes first and foremost into sporting competitiveness, most organizations already run lean, with people who wear many hats.
The value lies in getting routine tasks done faster, freeing up time for the work that needs people: creative thinking, partner relationships, the fan and member experience, and developing new revenue opportunities. That's where the growth is, and it's rarely where the time goes in a working week dominated by firefighting.
How far have you come?
We think the questions below are a good starting point for a conversation in the leadership team.
- Have you jointly evaluated different AI models and platforms and decided which one to use?
- Does everyone who needs it have access to the same platform through the organization's licenses?
- Do you have projects with defined context covering brand, tone of voice, target audiences and offers, and is someone responsible for keeping it current?
- Do your people know which information may and may not be used in AI tools?
- Are your other tools connected to the AI platform, or does work happen through copy and paste?
- Are you procuring AI-enabled tools that align with the organization's strategy and its other AI tools?
- Do you know what the time you free up should be used for, and are you tracking the impact?
If the answer to several of these is no, you're in good company. Most sports organizations we meet are in the same position, with committed people who have experimented on their own but without a shared structure to lean on. That's not a criticism, just an observation of where the industry stands today. Going forward, the gap will open up between the organizations that take the time to build that structure and those that keep leaving it to each individual.
How we help
We help sports organizations make AI a natural part of everyone's working day, and we do it using the same methodology as in all our engagements: analysis, implementation and evaluation.
We start by mapping how AI is used today, by whom and where the needs are greatest, and identify the use cases that create the most value for each role. We then lead the evaluation of models and platforms based on your needs. Once the choice is made, we work with you to build the context that makes the difference day to day, draw up guidelines for responsible data handling and help you move to tools that connect the whole chain. Hands-on training makes sure the new way of working sticks, and we track the impact in terms of time saved, increased output and effect on sales.
The goal is the same as in everything we do: to leave behind an organization that stands more firmly on its own feet, where routine tasks get done faster and people have more time for what actually drives results.
About Stratigo Sports Business
Stratigo Sports Business helps sports organizations with Digital strategy & development, Commercial growth, Data-driven marketing and Analytics, data & AI. Curious how AI could become a natural part of your organization's day-to-day work? Get in touch with Johan Sonesson at johan.sonesson@stratigosportsbusiness.com
