There is no lack of ambition around AI in UK businesses. The board is on the agenda, investor deck and product roadmap. And yet, for all discussion, not every organization is looking at meaningful values. According to our research, three of the four UK business leaders say they are lagging behind on AI.
This is not due to lack of vision. In fact, most businesses really know what AI can do – automatic manual work, insight, rapid scale. The challenge often comes down for execution.
Because success with AI is not about a tool, an use case or a budget cycle. It is about those systems, behaviors and product options that give the shape of how work is done. And when those foundations are not installed for speed, even the smartest AI strategy can stall.
From the perspective of a product, three recurring patterns emerge: infrastructure that is not placed above, working methods that oppose changes and equipment that overcomplicates rather than competent. None of these are permanent blockers – but they need to be designed, not worked around.
Vice President of Sales and Managing Director for EMEA in Hubspot.
Change inheritance systems in launchpad
Most businesses are not working with broken systems – just those that were created for a different time. And in years of development and expansion, those systems can be more complicated than intentionally.
45% of UK business leaders say Legacy Tech Stack is a major obstacle to obtain real value from AI – often because the systems below them cannot be placed. This is where friction makes: data stored in various formats, equipment that do not integrate, instead teams working around technology. When the AI enters the picture, they matter the gaps. It does not only require data – it requires the data that moves.
The good news is that you do not need to start with scratches. Strategic simplification – consolidated system, integrating platforms, removing repetition – breathing room needs to be functioned. It is about align what you have to work hard already.
This is why businesses are moving towards platforms that unite the core tools. We see the most progression when customers focus more on unlocking the lower on overhalling and unlocking single sources of truth. When the systems are connected and the data flows independently, AI decreases with a bolt-on and more multiplier.
Designing changes want to be part of people
Our research found that one -third of the UK experienced pushback when updating the legacy system or introducing new procedures. That hesitation is often labeled as resistance – but more often, it is a call for clarity. People want to understand how AI fits into his day-to-day work.
When AI is introduced without reference – or without input from the expected people to use it – it may feel more disrupted than progression. And this is the place where adoption often stumbles.
The real change occurs when leaders change like a product rollout – with transparency and response. This means that early inclusion of teams, implicating AI as an ambassador and showing a clear victory for employees: time saved, tasks were simple, better decisions made rapidly. It also requires commitment from leadership to effective change management and AI empowerment.
Equally important teams are giving confidence to use. AI is a developed capacity. Employees need to feel safe to give testing, question and shape on how these tools work in practice.
It does not always take a huge change program to move culture. In many teams, the change begins with a small, disappointing problem solving better – and to share how it is done.
Keep it simple enough for the scale
Even with modern systems and engaged teams, there is another obstacle that can slow down AI adoption: complexity. Not only in the concept of AI, but how it appears in people’s work.
According to our research, 35% UK trading leaders say they are struggling to bridge this skill gap and give their teams the confidence to use new AI devices effectively. And often, it comes down how those devices are made – not using everyday, keeping in mind technical users.
They sit outside the installed workflows or feel disconnected from the work that people are really trying to do. In resource-conscious organizations, such friction can prevent adoption completely.
Simplicity is about reducing the time between all intentions and results. The more comfortable a device is, the faster it distributes the value. A well-designed AI system does not only speed up tasks-it helps the teams to reach clarity, with minimal and low dependence. This is also better in a better way. The equipment that are simple to use are easy to roll out, train and maintain-especially in cross-functional teams.
Creating the right position to give AI to AI
The UK businesses looking at the AI are not moving forward. They are making conditions for progress.
This means designing processes that develop, cultures that are open to recurrence and products that actually learn with people using them. The fact is that AI does not require a right environment. This is just a responsible one requirement – both are designed to apply and maintain it.
Whatever matters is not on the first day’s scale, but has the ability to maintain improvement.
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