When founders ask me where to start with AI, my advice is always the same: don’t begin with the technology.
Start by identifying the biggest bottlenecks in your business. Look for inefficient workflows and decisions that could be improved through better information.
Those projects usually generate the quickest measurable returns while creating the foundations for broader transformation.
AI, by itself, is no longer a differentiator. Access to powerful models is becoming increasingly widespread, so the businesses that succeed over the next decade won’t necessarily be those using the most AI. They’ll be the ones that treat AI as infrastructure rather than a bolt-on.
As AI adoption accelerates, almost every business now has access to similar technologies. That means competitive advantage won’t come from using more AI tools than everyone else.
It will come from how effectively businesses integrate those technologies into their core operations.
At GymBeam, we’ve deliberately focused on building systems that allow growth to outpace operational complexity rather than simply adding more software to existing processes.
That’s a different way of thinking about AI. Too many organisations are layering AI onto inefficient workflows instead of redesigning those workflows altogether.
One of the biggest challenges every founder faces is sustaining growth without costs rising in parallel.
Historically, expansion often meant creating more processes and adding more layers to the organisation. AI changes that equation.
We’ve embedded AI into internal operations, content creation, localisation and customer personalisation.
We’ve automated administrative workflows that previously consumed significant amounts of time, allowing our teams to focus on work where human judgement and strategic thinking make the greatest difference.
Today, our AI-powered customer support systems handle around 400 customer chatbot requests every day, resolving routine queries instantly while freeing our teams to focus on more complex customer needs.
Saved 3,000 hours of human capacity
Across the business, AI has also saved more than 3,000 hours of human capacity, equivalent to roughly a year and a half of full-time work for one employee.
The most valuable AI applications are often the least visible. They sit behind the scenes, removing friction from the organisation rather than attracting attention. In my experience, those projects frequently deliver the most measurable commercial returns.
When repetitive work disappears, our talented employees can spend more time solving problems and creating value for customers.
We’ve also seen AI change the economics of international growth. Traditionally, entering a new market required building larger teams to translate content and support local operations. That created a largely linear relationship between growth and headcount.
Today, our AI models translate and localise content across more than 18 languages while also generating audio through our own text-to-speech technology. What was once a cost tied directly to people increasingly scales through computing power instead.
As businesses become increasingly reliant on AI, founders also need to be more diligent about data security.
At GymBeam, we work with highly sensitive customer information through our DNA-based personalisation products.
Protecting that data isn’t simply a compliance exercise – it’s fundamental to maintaining customer trust. That’s why I believe ownership and control should sit at the heart of every AI strategy.
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Third-party AI providers are great for experimentation and rapid deployment, and we continue to use external solutions where they make sense. But the capabilities that genuinely differentiate our business are the ones we invest in ourselves.
Building greater ownership of our AI infrastructure gives us more control over data, and a more predictable long-term cost structure. It also reduces dependence on the pricing models and roadmaps of individual vendors.
Data sovereignty is key
Increasingly, I believe data sovereignty will become a source of competitive advantage rather than simply a regulatory requirement.
Ultimately, the companies that create lasting value from AI won’t be those that simply adopt it fastest, but those that build the capability to own, control and continuously improve it.