By Vaishali Sahajpal, Senior Director Human Resources, ADP UK,
The UK is entering an AI‑intensive decade with a visible knowledge gap and a growing skills gap. Many workers still lack foundational understanding of what AI can do and how it can be used. While a smaller but growing group has basic awareness, majority struggle to apply AI confidently in real‑work settings. The UK Government’s AI Labour Market Survey report reveals that 57% of businesses report a direct technical skills gap, while many workers (30%) recognise the need for greater AI literacy across workforces.
As AI handles more process-driven work, the premium shifts to people who can interrogate outputs, spot what’s missing, and apply context. AI can generate options, but it can’t define problems or navigate ambiguity the way people can yet. Truly embracing AI in the workplace means not accepting outputs at face value – challenging assumptions and making decisions where there’s no clear precedent.
For business owners, this means creating space for experimentation and decision-making, rather than over-optimising for speed alone.
How employees really feel about AI in their roles
AI has become inescapable at work, and employees everywhere are thinking about what it means for their jobs. ADP Research study suggests that 88% of UK workers have already formed views on how AI will affect work, but those views are far from uniformly negative. Just 9% say they fear outright job replacement, while 14% strongly believe AI will improve their work, putting the UK ahead of other major European economies on AI readiness.
This nuanced view is reflected in how organisations are deploying AI coaching and support tools. When these tools simplify work, provide immediate insights that help clarify decisions and prioritise a people-centered approach, adoption tends to be stronger. The underlying principle applies to businesses of every size: AI is most effective when it enhances human judgement, not when it replaces the relationship between managers and their teams.
At the same time, there is growing anxiety around job security, the speed of change, and data privacy – especially as UK’s narrative on AI’s impact has recently taken a negative turn. The pace feels different this time: it took around 20 years for the internet to reach mass global adoption, yet major LLMs have achieved comparable reach in under three years. That acceleration explains why even employees who accept that change is constant can still feel unsettled. However, this sentiment can improve when employers invest in skills, transparency, and trust alongside AI deployment.
How businesses can support staff through AI-driven change
Businesses of all sizes need to treat AI-driven change as a people challenge, not just a technology rollout. Whether you’re leading a team of five or fifty, the fundamentals are the same: explain why change is happening and what it means for each person in your business. Critically, you cannot bring people along on a change journey if you cannot explain what’s in it for them as individuals, not just the business case. Equally, it’s important to demonstrate that AI will augment roles rather than replace them – with concrete support focused on building skills and confidence.
In practical terms, this means combining structured learning with on-the-job experimentation, regular check-ins on workload and wellbeing, and clear guidelines on responsible use. For smaller businesses without dedicated training functions, this can be as simple as setting aside time to learn together and sharing what’s working.
Redesign entry-level roles for augmentation, not elimination
If junior roles in your business are centred on tasks AI can already perform – basic research, first-draft creation, or routine data processing – they need to be redesigned. Early-career staff should use AI to enhance and accelerate these tasks, enabling them to progress quickly into work requiring deeper thinking and contextual judgement.
ADP’s research with Stanford Digital Economy Lab, covering 26 million workers, shows employment for 22-25 year olds in AI-exposed roles has fallen significantly since 2022, while experienced workers in those same roles have seen employment grow. AI isn’t eliminating jobs wholesale, but it is restructuring who gets hired for them. The real risk is a lockout at the bottom of the career ladder, where young people can’t get the foothold they need to become the experienced workers AI makes more productive.
The goal isn’t fewer junior hires: it’s faster progression into higher-value work. For small business owners building teams, this is an opportunity to develop talent more quickly than competitors who treat AI as a shortcut to cut headcount.
What AI means for different career stages
Business owners and leaders are facing a new kind of management challenge: AI-readiness varies significantly by career stage. The emerging pattern isn’t that AI eliminates jobs wholesale – it’s restructuring who gets hired. The real risk is a growing gap where young people can’t gain the experience needed to become the workers AI makes more productive.
Early-career professionals are building their identities with AI as a given, yet often lack the judgement to know when outputs need questioning. Mid-career employees are deciding how far to lean into new tools while balancing delivery pressures – when that tension goes unaddressed, they don’t resist; they disengage quietly. Senior professionals are expected to champion AI technologies they may not use day-to-day; when they endorse transformation only symbolically, adoption loses momentum across the business.
The organisations that overcome this invest in their people alongside the technology. Training built for “everyone” serves no one – the support must match the career stage. Junior staff need structured guidance that builds critical thinking alongside tool proficiency. Mid-career professionals need to see how AI amplifies their expertise rather than eroding it. Senior team members need space to learn visibly, including sharing mistakes, to signal that it’s safe for everyone to experiment.
Our research shows 85% of employees expect AI to impact their jobs – and younger workers are both the most convinced of this and the most anxious about what it means. Those who fear replacement are twice as likely to report high stress – a retention problem waiting to happen.
Business leaders need to match that urgency, moving beyond experimentation to practical, role-relevant skills that help people work with AI, not around it.
