AI isn't relevant to my role: why 26% of UK leaders are wrong

About one in four UK business decision-makers currently believes that AI is not relevant to their work. That is a reasonable position to hold when most AI coverage focuses on software engineers, data scientists, and technology departments. But polling of UK decision-makers, published in September 2026, puts a precise number on that view, and sector data tells a very different story. If you are a CEO, COO, or Finance Director who has quietly concluded that AI is someone else's concern, the evidence is worth a look before that assumption shapes your next planning cycle.

Why so many senior leaders feel AI does not apply to them

The myth has a sensible origin. Early business AI coverage concentrated on technical applications: coding assistants, data pipelines, machine-learning models. None of that language maps to a Finance Director's month-end close or a COO's capacity planning meeting. So the instinct to file AI under 'technology department' is understandable.

There is also a trust dimension. Many leaders have watched colleagues deploy tools that created more admin than they removed. Scepticism built on that experience is not irrational; it is informed. The problem is that it generalises from bad implementations to an incorrect conclusion about relevance.

A YouGov survey of UK business decision-makers, published in 2026, found that 26% say they are not contemplating using AI or that it is not relevant to their role. That is a meaningful minority. And it sits in tension with what the sector data shows is happening around them.

What the evidence says about relevance in mainstream business roles

Adoption figures from UK government and sector sources tell a different story from the one many leaders have internalised.

AI use in professional and business services has risen from 31.4% of firms in December 2024 to 43.4% in December 2025. That is a twelve-percentage-point shift in a single year. These are not technology companies. They are accountancy practices, law firms, consultancies, membership bodies and professional service firms staffed by people with the same functional responsibilities as the leaders who say AI is not relevant to them.

What are those firms actually using AI for? The evidence points to tasks that sit inside the day-to-day remit of senior non-technical leaders.

For Finance Directors: routine document analysis, variance commentary drafts, forecast scenario modelling, and compliance log summarisation. These are structured, repeatable tasks where AI Assistants can reduce the time a team spends on assembly, freeing analysts for interpretation.

For Chief Operating Officers: process mapping, ticket triage, supplier communication drafts, and capacity reports. The common thread is that AI handles the structured input and output, while the COO retains ownership of the decision.

For Chief Executive Officers: board report synthesis, market briefings, scenario planning documents, and meeting preparation. The CEO does not need to operate the tool. They need to understand what it can reliably produce and where it requires human review.

The regulatory position is also directly relevant to board-level leaders. As AI-enabled processes enter mainstream business operations, directors assume accountability for ensuring those processes meet UK governance standards, including directors' duties, fair treatment of customers, and proper handling of personal data. That is not a technology team responsibility. It is a leadership responsibility. Leaders who have opted out of the AI conversation may find themselves accountable for decisions they were not present to shape.

The cost of disengagement for SMEs

The 26% who feel AI is irrelevant are not just missing productivity gains. They are creating a structural problem inside their organisations.

When decision-makers disengage, experimentation does not stop. It fragments. Individual team members adopt tools informally, without governance frameworks, without data handling standards, and without any connection to business priorities. Security researchers have documented this pattern under the label 'shadow AI', and the evidence from UK adoption surveys suggests it is widespread in SMEs.

The result is a situation where the people with the authority to set standards are absent from the conversation, and the people without that authority are making consequential decisions by default.

For SMEs with 20 to 500 team members, the stakes are proportionally higher than in large enterprises. A large organisation can absorb inconsistent AI use across a handful of teams. An SME cannot absorb a data handling failure, a reputational incident from an unsanctioned tool, or a productivity initiative that runs counter to its operational model. Strategic alignment on AI starts with senior leaders deciding it is relevant to them.

There is also a competitive argument. Peers and competitors who have already closed the relevance gap are compounding an advantage. Twelve percentage points of adoption growth in one year across professional and business services is not a slow-moving trend. SMEs that delay sponsor-level engagement are not standing still. They are falling behind organisations that are already on their second or third AI implementation cycle.

A realistic approach for non-technical leaders

The evidence points toward a specific intervention: short, role-specific pilots with clear metrics and human review at every stage. This is not an IT project. It is a management decision about which structured, repeatable process to test first.

A useful starting frame is to list the five tasks in your current week that involve assembling information from multiple sources before making a judgement call. Variance analysis, board pack preparation, compliance log review, supplier performance summaries, customer feedback synthesis. These are the tasks where AI assistance is most likely to reduce assembly time without compromising the judgement at the end.

The pilot approach works best when the leader in question participates directly, even briefly. Understanding what an AI Assistant produces, where it is reliable, and where it requires correction is knowledge that cannot be delegated. It is also the knowledge that allows a Finance Director or COO to set sensible governance expectations for their team.

Board-level leaders should also ensure any AI-enabled process is risk-assessed and documented in the same way as other material system changes. That is not an additional burden. It is the same governance discipline that applies to any process carrying business or regulatory risk.

gecco's Training and consultancy programme is designed for this starting point. The Essentials tier covers AI fundamentals and the GRAFT methodology, with practical workshops where participants build their own assistants. The Complete tier adds autonomous tools and an applied session. gecco has trained 1,000+ professionals across UK organisations, with delivery available online, in-person, or hybrid. The programme is built to develop internal capability, not dependency, so Finance Directors, COOs, and CEOs leave with working knowledge they can apply to their own responsibilities directly.

What this myth gets wrong, and what leaders should do instead

The 'not relevant to my role' position rests on a definition of AI that is already out of date. The version of AI that was genuinely not relevant to most senior leaders, the technical infrastructure layer, is not what most business AI tools now are. The tools that have driven the adoption surge in professional services are prompt-based, conversational, and designed to handle the structured text tasks that fill senior leaders' weeks.

The honest caveat is that relevance varies. A CEO in a highly regulated sector with complex data handling requirements faces a more cautious path than one in a sector with simpler compliance obligations. Not every process is a good candidate for AI assistance in the near term. The goal of a pilot is not to deploy AI everywhere. It is to identify the two or three tasks where the evidence of value is clear enough to justify structured implementation.

What the evidence does not support is the blanket conclusion that AI has nothing to offer a Finance Director, COO, or CEO. The sector data, the adoption trajectory, and the nature of the tasks these roles perform all point in the opposite direction.

Your next step

If you are a Finance Director, COO, or CEO who has been treating AI as someone else's responsibility, the AI Readiness survey is a practical way to find out where your organisation actually stands. Take the AI Readiness survey. You will get access to 65+ free resources and a custom AI Readiness report. We then offer a free 30-minute showcase to walk through your results.

The gap between perceived irrelevance and actual capability is widest in roles that handle structured, repeatable data. If you want help identifying which processes to start with and building the knowledge to lead that conversation, gecco's AI Assistants and Training and consultancy programme are designed for exactly that.

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