UK firms see responsible AI as key competitive edge

Most UK business leaders expect responsible approaches to artificial intelligence to become a strategic advantage within the next two years, according to new research from Experian.

The study, published in a report titled "Responsible AI - Moving from principles to practice", surveyed 500 senior decision-makers in large organisations across the UK and Ireland that already use or oversee AI systems.

Experian found that 87% of respondents believe responsible AI practices will become a key differentiator within the next two to three years. The findings suggest that governance, transparency and accountability are moving from ethical considerations into areas of commercial competition and brand positioning.

AI impact and trust

The research indicates that AI is already influencing business performance. Some 89% of business leaders reported a positive impact from AI on organisational performance.

Trust in AI systems now appears central to future adoption. Experian's data shows that 84% of respondents say their customers increasingly want to know how AI is governed and who is accountable. Executives face rising scrutiny from users, regulators and internal stakeholders over how automated decisions are made and monitored.

Christine Foster, General Manager for AI and Automation at Experian UK&I, said businesses are moving from experimentation towards embedding AI at scale.

"AI is already delivering real value for businesses and customers. The focus now is on ensuring it drives meaningful outcomes in a responsible way. That means putting the right foundations in place including high-quality data as well as clear accountability, and tools that support AI adoption across its lifecycle. As AI evolves, especially with autonomous systems on the rise, getting this right will be critical to building trust, enabling better business decisions, and staying competitive," said Foster.

Implementation gaps

Despite broad agreement on the importance of responsible AI, most leaders say they struggle with execution. Some 76% of respondents view putting responsible AI into practice as one of their biggest challenges.

Common barriers include limited technical expertise, which 32% cited. A further 31% highlighted difficulty in applying high-level principles to real-world use cases. Another 30% pointed to the challenge of balancing innovation and speed with effective governance frameworks.

The figures indicate that many organisations are moving ahead with AI deployments while still working through how to operationalise risk controls and oversight. That tension is particularly acute in sectors such as telecoms, where AI is already embedded in network optimisation, customer service automation and predictive maintenance.

Data quality concerns

The study underlines concerns about the underlying data that feeds AI systems. While 90% of leaders agree that high-quality data is essential for responsible AI, only 43% feel confident that their data is strong enough to support such practices.

This gap suggests that many companies recognise data integrity as a critical factor in fair and reliable AI, yet have not fully addressed issues such as data completeness, accuracy, bias and ongoing maintenance.

Skills shortages compound the problem. Just 48% of respondents believe their teams are well prepared to drive responsible AI forward. Leaders identified the need for stronger data governance, more hands-on training, and closer collaboration between technical, legal, compliance and business functions.

Practical frameworks

Experian has set out guidance in the report for organisations working on responsible AI. The recommendations include regular assessment of AI model performance across their lifecycle. The company also highlights the need to apply security best practice to every AI use case.

These guidelines draw on principles created by Experian's AI and data science specialists. The organisation says these principles have influenced how its internal teams approach training, innovation and deployment of AI systems under a responsible framework.

Industry groups are also emphasising the need for operational frameworks. Sue Daley, Director of Technology and Innovation at techUK, said there is a shift from pilots to broad-based AI adoption.

"As AI continues to transition from pilots to widespread adoption, its critical organisations establish and operationalise clear frameworks for accountability, transparency, and fairness. This report is a vital contribution to the ongoing conversation about achieving Responsible AI. As this research shows, there's still work ahead to ensure organisations have in place the technical foundations and human capabilities to deploy AI responsibly. The seven principles offer an actionable roadmap, providing practical guidance that can support leaders in the building and deployment of AI systems while maintaining customer trust," said Daley.

Experian's findings suggest that UK organisations will allocate more effort and resources to responsible AI over the next few years as they react to customer expectations, regulatory focus and competitive pressure.