Over a few short years, artificial intelligence has transitioned from a future ambition to become a competitive necessity. Around 78% of businesses worldwide now use AI in some form, yet a significant gap remains between adoption and financial return. While many organisations have embraced AI tools, relatively few are unlocking their full value.
The businesses seeing the greatest returns are not those deploying AI in isolated use cases, but those embedding AI into the foundations of their operations. Companies that use AI to optimise workflows, improve decision-making and strengthen core capabilities are seeing measurable returns, while those treating it as an add-on risk falling behind.
For businesses with ambitions to scale, the question is no longer whether to invest in AI, but how.
Data sovereignty is becoming a competitive advantage
Ownership and control must sit at the heart of an AI strategy. As a health and nutrition business, we handle highly sensitive customer information, including genetic data used in our DNA-based personalisation products. Maintaining control over how that information is processed and protected is fundamental to customer trust.
While third-party AI platforms offer convenience, businesses seeking sustainable growth increasingly need greater ownership of the infrastructure and computing capabilities that power AI. Ensuring AI inference runs within our own environment means sensitive customer information remains within our ecosystem rather than being transferred to external providers.
This approach is becoming increasingly important as AI adoption accelerates. UK Government research found that nearly half of businesses using AI technologies had no specific cyber security practices in place. As regulation evolves and consumers become more aware of how their data is used, data sovereignty will increasingly become a source of competitive advantage rather than simply a compliance requirement.
Delivering more personalised customer experiences
The importance of data sovereignty becomes even clearer when considering one of AI’s most powerful applications – personalisation.
Consumers increasingly expect brands to understand their individual preferences rather than offer generic, one-size-fits-all experiences. AI is enabling businesses to meet those expectations at a scale that would previously have been impossible.
Across e-commerce, AI-driven product recommendations and intelligent search capabilities are helping customers discover products that are most relevant to them. The result is a better customer experienceand improved commercial performance.
At GymBeam, we have taken this a step further through our DNA-based personalisation offering. By combining genetic analysis with AI, customers can receive tailored nutritional guidance based on their unique biological profile. Delivering this type of service requires sophisticated AI capabilities alongside complete control of the data pipeline, particularly when handling highly sensitive information.
Freeing teams from repetitive work
While customer-facing innovation often attracts the most attention, some of the most immediate returns from AI are being realised behind the scenes.
We have automated a range of internal workflows, including administrative tasks that previously consumed significant amounts of time and resource. These are not necessarily the most visible AI applications, but they often deliver some of the fastest and most measurable benefits.
By removing repetitive work, AI enables employees to focus on activities where human judgement and strategic thinking add the greatest value. Rather than replacing people, AI amplifies their capabilities and allows organisations to operate more efficiently without compromising quality.
Accelerating content and localisation
The benefits of AI are equally visible in international expansion. Traditionally, entering new markets required significant investment in translation and content production. Growth often depended on building larger teams to support each additional market.
AI has fundamentally changed that equation. Businesses adopting AI translation and text-to-speech technologies can reduce localisation costs significantly while increasing the speed at which content can be adapted for new audiences.
Our AI models translate and localise content across more than 18 languages while also generating audio versions of articles using in-house text-to-speech technology. What was once a largely linear cost tied directly to headcount can now scale through computing power.
Building for scale and resilience
As AI becomes embedded across customer experience and content creation, businesses must also consider the economics of long-term adoption.
Third-party AI tools and APIs are often excellent for experimentation and rapid deployment. However, as usage grows, variable pricing models can become increasingly difficult to predict and manage. What begins as a small operational expense can quickly become a significant cost centre when AI is integrated across multiple functions.
Building greater ownership of AI infrastructure changes that equation. It transforms AI from a largely variable operating expense into a more controllable long-term investment. It also provides businesses with greater flexibility to adopt new models and avoid becoming dependent on a single provider’s roadmap or pricing structure.
In a market evolving as rapidly as AI, that flexibility is becoming an important source of resilience.
The future belongs to businesses that build, not just buy
The broader principle underpinning our approach is vertical integration.
We invest in and own the parts of the AI stack that create genuine differentiation, while continuing to use best-in-class external solutions where it makes little sense to reinvent them. This combination allows us to operate with the leverage of a much larger company, scaling content, markets and operations without increasing costs and headcount at the same pace.
The next phase of AI adoption will not be defined by which businesses use the most tools. Almost everyone now has access to the same technologies.
The real differentiator will be how deeply AI is embedded into the foundations of the organisation.
Businesses that treat AI as a bolt-on capability may achieve incremental efficiencies. Those that treat it as infrastructure will create lasting competitive advantages, unlock new opportunities for growth and be better positioned to adapt to whatever comes next.
