Businesses everywhere are racing to adopt AI. Whether it’s automating content, predicting behaviour, refining targeting or scaling personalisation, AI promises to elevate digital performance and unlock new efficiencies.
But while the dream of an amazing AI-enabled digital experience is very much alive, the reality is often very different. Research shows that 95% of corporate AI initiatives show zero return. And interestingly, the lack of success is not explained by the choice of tools either.
It’s about the approach. And that’s where Experience Optimisation (EO) comes in.
Navigating complexity
In today’s marketing landscape, having a digital experience – even an AI-enabled one – isn’t a differentiator anymore. Instead, the focus is on the quality of that experience and the bigger picture.
Your customers don’t differentiate between your ads, your app, or your website – all they see is one brand, and expect consistency across touchpoints. And if any of them fall short, it can compromise the entire experience.
At the same time, there is an overwhelming number of tools available to improve digital performance across different areas, from AI content assistants to personalisation engines, testing platforms and behavioural analytics tools, and the landscape is constantly evolving. Keeping up with this complexity and applying AI in a way that has a positive impact on their customers is a challenge for many brands experimenting with the technology.
Coupled with the desire, or, in many cases, the pressure to leverage AI, this has created an environment where many organisations feel compelled to implement tools without first building the right conditions for success.
Yet AI tools are only as effective as the foundations supporting them. Without clean data, fully integrated systems and a culture that empowers people to make the most of the technology, there’s a risk that the AI implementation will only automate inefficiencies instead of accelerating growth.
Unlocking commercial impact requires more than standalone improvements or isolated initiatives.
Commercialising the digital experience
Many organisations already invest in AI to support the user experience (UX), brand development, content creation, personalisation and conversion optimisation, but few bring these elements together in a coordinated way.
This can result in scattered progress. Like a new interface that looks great but doesn’t convert, a personalised journey that lacks consistent messaging, or content that performs well in one channel but doesn’t support users across the entire journey.
To turn digital experiences into a driver of measurable commercial outcomes, businesses need a holistic approach that connects every element shaping those experiences. It’s not enough to launch something new. What matters is how well it performs, how quickly it adapts and how reliably it delivers value across the customer lifecycle.
This is where turning the focus on Experience Optimisation (EO) can make a difference.
Foundation for excellence
Experience Optimisation starts with a deep focus on customers, understanding their needs, motivations and behaviours, and designing digital experiences that consistently deliver value to them. When customers benefit, that value is translated into sustainable commercial outcomes for the business.
EO brings together the strategic disciplines that shape meaningful user experiences, including psychology, design thinking, brand consistency, content strategy, personalisation and experimentation. These disciplines are aligned around the customer journey and supported by the right technology, organisational structures, and product and business strategies. Clean data, connected systems and streamlined content workflows enable AI to enhance relevance, personalise intelligently and scale learning through experimentation.
When these elements work together, businesses create a customer-centred system for continuous, evidence-driven improvement. Crucially, EO shifts teams’ focus from simply delivering experiences to understanding how those experiences perform for customers, adapt over time and contribute to broader commercial goals, turning optimisation from a set of tactical improvements into a strategic engine for customer-led growth.
Securing buy-in
However, even the best tools and talent cannot compensate for an internal structure that slows decision-making or traps insight in departmental silos. That’s why EO won’t deliver if the organisation is not set up to support it.
In many businesses, brand teams chase awareness, content teams focus on delivery and CRO teams look at conversion in isolation, which can result in fragmented journeys and duplicated effort. EO, on the other hand, requires teams to work differently. Instead of relying on centralised, top-down decision-making, successful organisations decentralise decisions, pushing authority closer to the work.
When multidisciplinary teams can act quickly on data and insight without waiting weeks for sign-off, they can learn and adapt faster and work more efficiently. Governance then becomes a mechanism for alignment rather than control, providing clarity on roles, priorities and standards while preserving agility.
With these building blocks in place, future AI implementations are better primed to deliver on their promise and drive commercial impact and accelerate growth.
Look at Corinthia hotels, for example. The boutique hotel chain wanted to upgrade its digital experience and improve conversion from search to booking. But instead of simply looking for an AI fix to these challenges, it approached the project through EO.
Through journey mapping and careful experimentation, the digital experience was reconstructed around guest needs, refining UX and navigation, simplifying booking flows and adding personalisation to where it matters the most. As a result, the chain saw 32.5% YoY revenue growth and over 40% conversion lift for its flagship hotel in London.
Better digital experiences
Ultimately, AI cannot transform your digital experience on its own. It can automate, accelerate and augment great work, but it cannot fix systemic issues or create alignment where none exists.
If key elements are missing, AI can produce inconsistent, unreliable or irrelevant outputs. It should be seen as an enabler to support the delivery of a mature, insight-driven optimisation programme – not a shortcut to paper over structural challenges.
When organisations treat AI as a partner in continuous improvement rather than a replacement for strategic thinking, they unlock much greater value. The future of digital experience is integrated, AI-accelerated and outcome-focused.
And it begins with placing Experience Optimisation at the centre of the growth strategy, built around a deep understanding of customers.
