Why the AI skills gap is an HR problem

Twenty years in internal communications and employee engagement teach you to spot the difference between a trend and a tipping point. AI is indeed the latter, and the HR sector is dangerously close to missing it.
 
Here's the thing about HR being such a female-dominated profession: the group most likely to be left behind as AI reshapes the workplace is the very same group responsible for looking after everyone else in it. In three to five years, the people who can confidently build with AI will be shaping products, influencing decisions and earning a place at the leadership table. Everyone else will be playing catch-up.
 
That's what this International Women's Day should really be about. We should be celebrating how far we've come, yes. But we also need to be honest about the gap that is widening every single day.
 
The panel problem
 
After attending a major HR conference last year, I sadly noticed that every single panellist was male, speaking to a room that was almost entirely women. The conference was a precise representation of a much larger structural failure. When engineers, who also happen to be predominantly men, lead every AI conversation in every room, they frame the technology in engineering terms. The audience who might not have the same technical background hit a wall immediately, and most may walk away, concluding that AI belongs to someone else.
 
You can't be what you can't see. Women in HR need to see other women in HR building GPTs, automating workflows, deploying AI agents to reduce manual load and solving the exact operational problems they face every day. Without that visibility, the technology feels complicated, but with it, it's a tool that allows HR professionals to cook with gas.
 
Risk aversion is a feature, until it becomes a trap
 
HR professionals are risk-averse by design. They are the custodians of personal data, workforce wellbeing and employment law compliance. But that same caution can lead to teams being resistant to change overall. And resistance to AI in 2026 has real consequences.
 
Every major employee engagement platform has embedded AI into its core workflows. HR teams open these tools every morning and interact with AI-driven features, whether they realise it or not. When the people running these systems don't understand what the AI layer does or why, they lose the ability to advocate for their workforce or make better decisions for the department. Instead, they become passengers in their own stack.
 
Building the infrastructure for women to learn
 
Training modules or a mandatory e-learning course may have their place. But what actually works is a peer-led technical community. For example, at Perkbox, we built a women-with-AI group where we run monthly sessions to share what we've been building. We run hackathons where we build custom GPTs together, automate processes end-to-end and deploy AI agents to handle repetitive operational work. The point is to build enough exposure that the tools stop feeling alien.
 
What's amazing is that most organisations already have women building with AI, but not everyone is aware of it. By creating a structured space, the multiplier effect kicks in. One day, it will be someone showing a prompt chain they built to automate onboarding communications, the next someone adapts it for performance review cycles. A third person spots a use case in employee relations that neither of the first two had considered. The more we share knowledge, the more we breed confidence.
 
Think of it as a technical skill transfer operating through social infrastructure. The learning mechanism is peer observation: watching someone who faces the same constraints as you successfully use a tool, then immediately trying it yourself. That's a faster and stickier learning pathway than any classroom model.
 
The innovation gap is a leadership opportunity
 
Unfortunately, the HR tech sector feels very stagnant at the moment. Most organisations benchmark their reward and engagement strategies against what competitors are doing, and competitors are doing broadly the same thing, albeit presented slightly differently. There is very little that is genuinely new.
 
AI has real power to break that pattern, but only if HR teams approach it as AI practitioners. The opportunity is to productise HR the way technology teams productise software: define the user problem, build the system, test it, review and iterate again. That requires HR professionals who are technically fluent enough to have an opinion on what the AI layer should and should not be doing inside their tools.
 
Women in HR are, right now, sitting at the intersection of the fastest-moving technology shift in a generation and the function that will determine how that technology affects working lives. So, a simple celebration is not enough. This IWD, business leaders should be asking themselves a more productive question: which women in our organisation are already building with AI, and does anyone know about it? If the answer is 'no idea', you need to fix it, and you need to fix it fast.
 
We need to create a recurring, peer-led technical community where women share what they've built, what didn't work, what did and what they want to try next. Make it low-stakes enough that early experiments are welcome, but making sure it creates new skills. Talk about AI in terms of workflow or about the specific manual tasks it cuts. Show the before and after. Let the time saved speak. And put women who are solving HR problems with AI in front of other women who are solving HR problems.
 
I don't think the skills gap can be closed fast enough. The question is whether HR - the function that looks after everyone else in an organisation - will close it from the inside, or wait for someone else to do it for them.