From Headcount to Skill Sets: Rethinking Hiring, Roles and Career Paths in an AI-Driven World

Insights From Marie Shaw at LHH, Nicole Knott at PwC & Ian Wallis at HMRC

AI is changing more than the tools we use at work. It's changing who organisations hire, how roles are designed and what a career looks like. That was the starting point for a panel at the Engage Employee Summit: From headcount to skill sets: rethinking hiring, roles and career paths in an AI-driven world.

The panel brought together three people facing these questions from very different angles:

• Marie Shaw, who leads LHH's advisory business in Europe and also shapes its internal HR strategy
• Nicole Knott, a Partner at PwC who leads its workforce technology and analytics programme and is also chief people officer for her team of around 400
• Ian Wallis, People Analytics and Insight Director at HMRC, who joined from a data and analytics background six years ago

Marie called AI "the biggest reimagination of work" we're likely to see in our careers. She described it as a real turning point for HR leaders. Organisations can join an AI race to the bottom focused purely on cost, or they can build a working world that balances human and artificial intelligence.

Hiring for curiosity, not just technical skills

For Nicole, AI is the biggest disruption to hiring right now. PwC still needs STEM skills, but AI is changing how many people it hires. It's also putting more weight on a different set of qualities: curiosity, the ability to relearn, and the drive and creativity to adapt to changes no one can predict yet.

She admitted that even she can't say which jobs will exist in a few years. When a group of 16-year-olds asked her what job they should work towards for 2030, she told them she'd need a crystal ball. What will matter, she said, is how people approach work: whether they can adapt, do the job well and be good to work with.

At HMRC, Ian sees a "double whammy". AI is changing the tools his people analytics team uses, and it's also changing the 70,000-strong workforce they analyse. His aim is to use AI to take on the basic work, such as data preparation, so that scarce specialist skills can be used where they add most value.

Growing talent from within

One of the biggest shifts the panel described is a move away from hiring externally and towards developing people already in the business. At LHH, internal mobility has risen by around 50% in the last 12 months. Marie explained that this used to be a number HR simply recorded. Now the executive team asks what's being done about it. "This myth that all this great AI-enabled talent is sitting outside of the organisation is proving to be quite a myth," she said. Much of it has to be grown internally.

AI skills are also becoming a factor in who gets promoted, and employees expect their employers to help them build those skills. LHH has invested heavily in upskilling, with help from its sister company General Assembly.

Nicole made the case for making internal moves easy. Data often says people leave their manager, but often it's because finding a new role internally is harder than finding one elsewhere. PwC is working to get a clearer view of the skills its people have, so it can suggest opportunities they might not have thought of. As Nicole put it: "You do these three things. Did you know you could potentially go and do this in this new line of business?"

HMRC faces a different challenge. Public sector pay makes it easier to attract people into junior roles than senior ones, so the focus is on keeping and developing people. Ian's directorate has:

• Introduced structured mentoring, so training its own people is planned rather than left to chance
• Built a skills matrix tracking 50–60 skills across the team, mapped to how it expects work to change
• Built AI into training from the start, as part of the standard offer rather than an add-on

Ian believes learning on the job with real, messy data works better than a training course with a perfect dataset. Being open with colleagues matters too. "We're preparing them for the future and not preparing them for today," he said. That includes skills they may not need now but will in 6, 12 or 24 months.

Making AI an everyday habit

With several generations in today's workforce, people's comfort with AI varies widely. Nicole sees it with the young people who do work experience at PwC. They go straight to AI tools on their phones, the way her generation used Google. She still has to remind herself to use them. Her answer is reverse mentoring, so younger colleagues can share what they know.

She also borrowed an idea from safety culture: starting meetings with an "AI moment". Teams share the latest thing they've learned, a top tip or their biggest realisation of the week. When AI comes up in everyday conversation, it starts to feel normal.

LHH does something similar with weekly team huddles, where people share which AI tools they've used and how they've changed a task. Marie stressed that employers mustn't create "haves and have-nots" across generations or leave people behind as change speeds up. Habits alone aren't enough, either. Organisations need to look at the bigger picture:

• What are we measuring?
• Where are leaders putting their focus?
• What permission are we giving people to experiment?

Many organisations roll out AI tools and make their use mandatory, with "quite a bit of stick" and not enough carrot. Marie suggested a different incentive: if AI saves you three hours on a Friday afternoon, those hours are yours.

An audience member asked whether an AI moment might replace the wellbeing moment at the start of meetings. Nicole said it doesn't have to be either-or. Using AI well should give people time back, which supports wellbeing. But she warned that you can't just trust what AI produces. On a big analysis, she might use six prompts to check it has covered all the data.

Getting the first mile right

Much has been written about the "last mile" of AI adoption, keeping momentum going after a big rollout. Marie, a long-distance runner, argued that the first mile matters just as much. That's when you settle your nerves and find your pace. She pointed to countries that are ahead of Europe on AI adoption and investing heavily at the start, through leadership, communication and engagement.

That early effort is vital for tackling fear. When asked how organisations can reduce it, Marie said fear grows when change feels like it's being done to people and they lose a sense of control. Her advice:

• Get leaders talking about AI regularly, through big company-wide messages and in team meetings, huddles and one-to-ones
• Get people's fears out in the open
• Give a balanced view: be honest about what nobody knows yet, and show the benefits for individuals, not just the organisation

Nicole has seen how much this depends on leaders setting the example. Early data at PwC showed that the C-suite and the level below were using AI and talking about it, but that wasn't spreading through the rest of the firm. The focus has since shifted to getting everyone trained and using AI day to day. "You can't just build it and they'll come," she said. People need to feel that AI makes their current role easier.

Ian shared a lesson from HMRC: sometimes you have to slow down. In a traditional organisation of 70,000 people, his team has learned that some changes moved too fast and had to be scaled back. Change sticks when it happens step by step. He also learned to choose his moments. Senior leaders can back a bold idea a couple of times a year, not every week. He sees failure as part of learning: "As an analyst, it's terrific. You've got a whole lot of new data points."

Change from the middle, and the "Great Eight"

Asked for one takeaway each, Marie and Ian made the same point: don't treat this only as a top-down effort. Support from the top matters, but the biggest difference happens where the work actually gets done. "Two or three percent across 20,000 people is huge," said Ian. Small improvements across a whole workforce add up to far more than anything 20 people at the top can achieve alone.

Nicole's takeaway was more personal. Her goal is to use AI to help people get back to the "Great Eight": eight hours of work, eight hours of sleep and eight hours of life outside work. Many people now spend two to four hours a day just commuting. As a parent of a four-year-old, she sees this as a chance for HR to reset how work is designed. If organisations get that right, people will be healthier, happier and have more time to learn the skills that move their careers forward.

The message from the panel was clear: AI will change roles, skills and careers, but how people experience that change is still up to leaders. Organisations that invest in their own people, make AI part of everyday habits and talk openly about the fears will be best placed to bring their whole workforce with them.

To register your interest for the 2027 Engage Employee Summit click here.