Bridging the AI trust gap: Why UK businesses struggle to turn confidence into impact

Artificial intelligence (AI) is now embedded in the foundations of modern business. Across sectors, it powers decision-making, drives automation and helps organisations uncover new efficiencies and new revenue streams. Yet, while its influence continues to grow, trust in AI, and the systems that govern it, remains complicated. 

In the UK, businesses are confident in the potential of AI, but that confidence isn’t always backed by the investment, governance and ethical safeguards needed to make it trustworthy.

According to a new report, around a third (32%) of UK organisations sit in the ‘danger zone’ meaning they have complete trust in AI, but invest little in making it genuinely trustworthy. Only 8% of businesses are truly “aligned”, where trust is underpinned by strong governance and accountability.

The result is an imbalance between aspiration and assurance, leading to a trust dilemma which is slowing the full realisation of AI’s benefits.

A nationwide trust problem

Overall, the UK’s relationship with AI is cautious and complex. Organisations are more likely than their global peers to see privacy, security and compliance as barriers to progress. This sensitivity reflects a culture shaped by strong regulation, data protection laws and public awareness of digital ethics.

While this caution ensures a higher baseline of accountability, it also creates friction. Many UK enterprises struggle to access and integrate the data required to train and scale AI systems effectively. Without secure and timely access to relevant data, even the most ambitious AI projects can stall before achieving impact.

This challenge is compounded by perception. Forms of AI, such as generative and agentic systems, are often seen as more trustworthy than traditional machine learning, despite being newer, less transparent and harder to explain. This inversion of trust suggests that many organisations are guided more by excitement (or experience of using tools such as ChatGPT) than by evidence.

However, the UK’s regulatory rigour can also be its competitive advantage if used strategically. It can help build AI systems that are not only compliant but demonstrably reliable and resilient. The opportunity lies in viewing regulation as a framework for innovation, rather than a set of constraints to navigate.

The gap between trust and impact

Trust alone does not guarantee business impact and across Europe, countries vary widely in how successfully they translate responsible AI practices into results.

Ireland delivers significantly higher business impact from AI relative to other countries, whereas Danish organisations struggle significantly to deliver business impact and create trustworthy AI. The UK, though, sits in the middle as organisations tend to invest in governance but often fail to make full use of it in their AI systems.

This reflects what analysts are calling the trust–impact gap – a disconnect between the frameworks designed to ensure AI reliability and the tangible value those frameworks deliver. Many organisations can create robust principles and policies, but then fail to operationalise them within their AI lifecycles.

Globally, very few businesses achieve full alignment between their stated trust in AI and the actions they take to secure it.

This imbalance can lead to two types of risk. The first is underutilisation, when reliable, proven systems are ignored because confidence is low, and the second is overreliance, when unproven systems are deployed based on misplaced trust. Both of which limit AI’s potential and expose organisations to avoidable failures.

Overcoming this second, more dangerous risk demands more than compliance. It requires embedding trustworthiness into the core of how AI is designed, developed and deployed.

Turning confidence into impact

Organisations need to move from confidence as a statement of belief, to confidence as a product of design. That begins with reframing governance as an enabler rather than a hindrance.

When governance is integrated from the outset, shaping data access, model transparency and responsible use, it strengthens innovation by providing clarity and predictability. This alignment helps ensure that AI systems meet both regulatory expectations and customer standards, reducing the risk of costly course corrections later.

Investment in data quality is equally essential. AI models are only as reliable as the information that trains them, yet poor data management remains one of the most persistent barriers to trustworthy systems. Developing unified, high-integrity data environments allows organisations to scale AI responsibly while maintaining confidence in its outputs.

Transparency and explainability also play a decisive role. Stakeholders, from customers to regulators to employees, need to understand how AI decisions are made and on what basis. The more visible and interpretable AI becomes, the stronger its legitimacy and long-term adoption will be.

Finally, trust must be treated as a collective responsibility. It cannot be left solely to data scientists or compliance officers. Business leaders, policymakers and technical experts must work together to establish frameworks that balance innovation with integrity, as when trust is shared, it becomes durable. And, when it’s durable, it drives impact.

A look ahead

Looking ahead, the UK is well-positioned to lead on trustworthy AI as a result of its regulatory environment, ethical standards and research ecosystem offering the foundations for sustainable innovation. But leadership depends on alignment, between trust and truth, confidence and credibility.

As generative and agentic AI continue to capture public and commercial attention, the question is no longer whether AI can be trusted, but whether organisations are willing to invest in making that trust real.

The future of AI in the UK will not be defined by how many systems are deployed, but by how effectively they are governed. Those who treat trustworthy AI as a source of strategic strength, grounded in transparency, governance and data integrity, will turn confidence into lasting impact.

Because in the end, trust cannot be assumed. It must be earned and built, piece by piece, into the technology that is reshaping how the UK does business.