AI anxiety is real. And if you’re an HR leader or people manager, you’ve probably felt it ripple through your organisation.
One day, your team is excited about ChatGPT’s potential. The next, someone’s quietly worrying whether their role will exist in two years. This goes beyond technology adoption. We’re watching human beings navigate profound uncertainty.
We recently brought together Pascal Struijk from Lepaya and Ryan Westley, psychologist at OpenUp, to explore how leaders can guide their teams through AI transformation without sacrificing trust, well-being, or innovation. What emerged was a roadmap for turning fear of AI into collective momentum.
🎥 Want the full conversation? Watch the complete webinar recording where Pascal and Ryan dive deeper into practical strategies, answer live questions from HR leaders, and share real examples from organisations navigating AI transformation.
Why AI Anxiety Hits Differently
“A stressed brain can’t learn,” Pascal notes during the conversation. And that’s the challenge facing organisations today. You’re investing millions in AI infrastructure whilst your people are mentally stuck, unable to move forward because they’re overwhelmed.
Ryan sees this playing out in his sessions with employees. “There’s definitely trepidation about what it means for people’s jobs and job security, how they’re going to keep up with how rapidly it’s evolving,” he shares. But here’s what’s interesting: alongside that anxiety sits genuine excitement about new possibilities.
The question isn’t whether AI will reshape work. It’s whether you’ll create the psychological safety your teams need to navigate that change together.
💡 Explore more on how AI impacts jobs and what builds resilience.
The Leadership Blind Spot Nobody’s Talking About
Here’s what’s happening in most organisations right now: executive teams have AI as priority number one. Task forces are working on compliance and use cases. Generative AI tools are generally available.
But there’s a gap. A big one.
“Where is general leadership in the equation?” Pascal asks. “How do we make sure teams or domains or departments start benefiting from this beyond individual productivity gains?”
Most AI leadership focuses on executive teams and dedicated task forces. Meanwhile, middle managers (the ones who actually enable day-to-day work) feel sidelined. They’re watching decisions happen elsewhere, wondering what their role even is. Pascal calls this “the drama triangle,” where becoming a victim feels easier than taking charge.
This is how AI leadership fails before it even begins. You can’t delegate transformation to a task force alone. Your middle managers are the multipliers. Without them, adoption stops at the team level.
From AI-Aware to AI-Enabled: The Role Leaders Play
So what does taking charge actually look like?
It starts with what Pascal calls “product thinking,” which means understanding which AI use cases will drive real impact versus which ones look impressive but deliver no return. “There’s fifteen to twenty potential use cases per team,” he explains, “but what are the ones we’re going to invest in?”
This isn’t something you can hand off. It requires analytical skills, business judgment, and the ability to work with multiple stakeholders. It means mapping your team’s activities, spotting patterns, and making strategic choices about where AI creates genuine value.
But here’s the psychological element: when leaders take ownership of AI strategy for their teams, they move from feeling powerless to feeling in control. And that shift matters. As Ryan points out, “We don’t like uncertainty, we don’t like unpredictability. Increasing that agency, that autonomy, that psychological safety, is crucial.”
The Communication Challenge You’re Getting Wrong
Most AI communication in organisations flows one way: from executives to employees, from task forces to teams. Leaders end up selling AI to their people.
Pascal’s advice? Stop selling. Start talking with your teams, not to them.
“There should be way more dialogue where there is a place for vulnerability, doubt, and silence,” he says. This happens in your existing rhythms: team weeklies, one-on-ones. You don’t need special town halls. You need genuine conversation.
Ryan adds a crucial point: “If you want your team to feel honest and open and safe to come forward with concerns, you also have to show that vulnerability to your team.”
Think about it. When you admit you don’t have all the answers, when you acknowledge the uncertainty alongside your team, you’re modelling the behaviour that makes psychological safety possible rather than weakening your position.
Three Foundations for Psychological Safety During AI Change
Ryan identifies three non-negotiables for creating environments where people can experiment without fear:
Clear communication and modelling behaviour. Your team watches what you do more than what you say. If you want them to experiment with AI tools, they need to see you trying, making mistakes, and learning openly.
Involving stakeholders in decisions. People need to feel they’re shaping the future, not having it forced upon them. Pascal puts it brilliantly: “It’s much safer to co-shape the future than to wait and see.”
Incremental exposure. You can’t throw everything at people at once. Slow and steady reduces overwhelm whilst building that crucial sense of agency and control.
And here’s something many leaders miss: psychological safety and productivity expectations are two different things. You can approach them separately. You can ask for more whilst also building the skills people need to deliver.
As Pascal notes, asking someone to experiment without upskilling them first is like asking a student to rewrite your company strategy. It’s psychologically unsafe by design.
The Skills That Matter Now (and Those That Don’t)
Let’s talk about what changes when AI becomes embedded in your work.
Skills gaining value:
- Judgment (interpreting AI outputs, deciding what outcomes matter)
- Agility and resilience (your job will keep evolving)
- Human skills: collaboration, creativity, empathy, communication
“I don’t think AI is going to replace those,” Ryan emphasises. These so-called soft skills are actually your most future-proof investment.
Skills losing value:
- Simple production and writing
- Repetitive operational work
- Basic data compilation
Ryan shares something important here: research shows excessive use of large language models can reduce critical thinking and attention. But balanced, collaborative use actually increases these skills. The key is finding that balance.
Here’s a practical exercise Pascal recommends: create an effort-impact matrix with your team. Map all your activities on it. The tasks that are low effort and low impact? Those are prime candidates for automation. When teams identify these patterns themselves through workshops, the insight clicks in a way that top-down communication never achieves.
How to Actually Support Your Team Through This
For individuals feeling anxious: Ryan suggests starting with awareness. Notice your thoughts. Can you reframe them from negative to positive? Write them down or speak them through with someone. Maintain routines that protect your well-being. Take small steps and focus on what you can control in the next five minutes, not everything all at once.
For leaders supporting teams: Reframe AI adoption as curiosity and opportunity. Create spaces for coffee chats where people realise they’re not alone in their concerns. Remember that humans have a negativity bias. We fill information gaps with worst-case scenarios. Your transparency prevents that.
“If you receive bad news but you’re told why and prepared beforehand, you tend to manage it better,” Ryan explains. Don’t leave blanks for people to fill with fear.
For HR teams: You’re the orchestrators here. Develop workshop formats that teams can use to map their work and identify AI opportunities together. Consider train-the-facilitator programmes that bring this to team level rather than trying to reach whole organisations at once.
And crucially: work with your AI task forces, not around them. They have critical knowledge and authority. Your role is bridging executive strategy and people reality. Leaders connect with teams and individuals. All three are essential.
💡 Learn more about supporting mental well-being during AI transformation.
The Path Forward Starts Small
One question from the webinar stood out: “How do you balance day-to-day work with AI upskilling?”
Pascal’s answer is pragmatic: “Free up people who have natural desire to invest here. For domains with repetitive work, start dedicating at least twenty percent of time to this. If you don’t, others will.”
But Ryan balances this with patience: “Learning a new skill takes time. Adoption takes time. If you rush and it doesn’t implement well, you’ll increase stress and anxiety in the future.”
The sweet spot? Work with your team, not at them. Don’t talk to them but talk with them. Run workshops where they discover which activities AI can transform. Equip them with functional AI knowledge before asking them to experiment. Celebrate small wins.
Most importantly: remember that you’re all learning together. The only certainty is uncertainty. But when you create space for people to navigate that together, something powerful happens.
Your Next Step
AI transformation isn’t a technical challenge with a human element. Think of it as a human challenge with a technical element. The organisations that thrive won’t be the ones with the best AI tools. They’ll be the ones where people feel safe enough to experiment, make mistakes, and shape what comes next.
Start where you are. Pick one team meeting this week. Instead of presenting an AI update, ask what concerns people have. Instead of selling benefits, explore possibilities together. Model the vulnerability you want to see.
Because AI anxiety doesn’t disappear through reassurance. It transforms through action, connection, and the knowledge that you’re not facing the future alone.
