Leaders overestimate UK organisations’ AI readiness gap

Sopra Steria research suggests senior leaders in UK organisations view their AI readiness far more positively than mid-level and junior managers closer to delivery teams.

A survey of 200 UK business professionals found 65% of senior leaders rated their organisation's AI governance, infrastructure and strategy highly, compared with 44% of mid-level and junior managers. The report suggests this gap could slow AI roll-outs and increase risk for projects that rely on consistent operating practices across a business.

Responses came from public and private sector organisations across multiple industries. Participants assessed AI maturity across six areas: governance, technology and infrastructure, expertise, data, culture, and strategy. They used a 1-to-5 scale, where 1 meant basic practices and 5 meant full incorporation.

The results showed differences in every category. Strategy produced one of the widest splits: 64% of senior leaders said their AI strategy aligned with strategic goals, integrated with business objectives and evolved based on internal feedback, compared with 35% of mid-level and junior managers.

Gaps across pillars

Governance also showed a marked perception gap. Among senior leaders, 67% scored their organisation highly for AI governance, versus 46% of mid-level and junior managers.

Views of in-house expertise differed even more. Some 59% of senior leaders rated their organisation's AI expertise highly, compared with 34% of mid-level and junior managers.

Culture was another area of divergence. Asked about engagement, how change is communicated, and how feedback on AI is incorporated, 61% of senior leaders described their organisation as having a positive AI culture. The figure was 41% among mid-level and junior managers, which the summary described as a 20% perception gap.

These splits matter because many AI programmes require changes to workflows, decision rights and accountability. They also depend on staff confidence in data use and governance controls. If senior leadership expects rapid deployment while delivery teams see weak foundations, it can create friction over priorities and resourcing.

Becky Davis, Director of AI at Sopra Steria Next UK, linked the findings to uneven understanding of what it takes to run AI initiatives at scale.

"For many senior leaders there's already an expectation that when it comes to AI, they're able to confidently set direction, manage risk, and make the right calls. But this is often without a clear understanding of the fundamentals of AI. It's perhaps no surprise, therefore, that those in leadership positions can often misunderstand and sometimes overstate their organisation's level of maturity," Davis said.

Davis said the same dynamic can leave managers with targets they cannot meet if practical enablers do not keep pace.

"Equally, when senior leaders set bold strategies, but managers lack the infrastructure or cultural support to execute, progress stalls. Bridging this gap means turning vision into reality: ensuring governance, technology, and talent evolve together so AI moves beyond pilots and delivers measurable business value," she said.

Operational risk

The research also argues that uneven perceptions of readiness can translate into operational risk. Misalignment can set unrealistic expectations for delivery timelines and outcomes. It can also complicate controls around data access, model use and accountability, since governance processes often span multiple business functions.

In practice, AI adoption depends on a shared understanding of what "ready" looks like. Senior leaders may interpret maturity as a documented strategy and set of policies, while managers may focus on whether teams have the tools, skills and data quality needed for day-to-day delivery.

Fiz Yazdi, Managing Director at Sopra Steria Next UK, said leadership behaviour and organisational learning sit behind many stalled AI projects.

"Our findings shine a light on the gap between how AI maturity is perceived at senior leadership level and how it's experienced by those in frontline delivery roles. This disparity is not about technology, it's about leadership. AI doesn't fail because organisations lack tools, it fails because leaders haven't yet learned how to lead with AI," Yazdi said.

Yazdi also linked stronger leadership understanding to decisions about spending and governance trade-offs, as well as service delivery outcomes.

"From our experience, we know that AI success comes when employees at all levels are empowered to learn and grow. And it stands to reason that this begins at the top. Increasing AI maturity across an organisation's senior leadership team leads to better investment decisions, improved understanding of risk, and ultimately improved business performance, and services that citizens and customers increasingly expect," he said.

The research was conducted through Sopra Steria's business transformation consultancy, Sopra Steria Next UK. Sopra Steria also offers an online training course called "AI for Leaders".

Sopra Steria operates across consulting, digital services and solutions. It reported revenue of €5.8 billion in 2024 and employs 50,000 people in nearly 30 countries.