For many employees, AI raises uncomfortable questions: Will this change my job? Am I expected to know how to use it already? Can I admit I am confused? What happens if I use it incorrectly? Will this tool make work better—or just faster and more demanding?
The problem is that when these questions remain unanswered, they can start to shape how employees engage with AI. Already, research shows that about half of U.S. workers say they’re worried about the future impact of AI use in the workplace, and 32% think it will lead to fewer job opportunities for them in the long run.
When people feel uncertain, exposed, or afraid of making mistakes, they are less likely to ask questions, challenge assumptions, admit what they do not know, or experiment openly. In a moment when companies are asking employees to learn and use AI quickly, those are exactly the behaviors organizations need most.
That is why AI adoption has become a psychological safety issue at work and why inclusion leaders have an important role to play.
Psychological Safety and AI
A recent survey found that 76% of executives believed employees were enthusiastic and optimistic about AI adoption, while just 31% of individual contributors said the same. This disconnect can lead organizations to build AI strategies on a faulty understanding of the employee experience.
This is where psychological safety becomes critical. Long familiar to inclusion leaders, psychological safety is what allows employees to speak up, ask questions, take interpersonal risks, and contribute without fear of embarrassment or punishment. In the context of AI, those behaviors are essential. After all, successful AI adoption depends on people being willing to experiment.
Research is beginning to show that connection: A recent study found that psychological safety was a significant predictor of whether employees adopted AI tools, suggesting that psychological safety may be especially important in the early stages of AI engagement.
However, not everyone experiences “trying” in the same way. Employees who already feel pressure to prove their competence, avoid mistakes, or manage how they are perceived may be less likely to experiment openly with tools they do not yet understand. Without psychological safety, the very behaviors organizations need for responsible AI adoption become harder to sustain.
Three Ways to Build Psychological Safety Around AI
The good news is that inclusion leaders do not have to start from scratch. The same practices that help build psychological safety in other moments of change, such as transparency, trust, and listening, also apply to AI. The difference is that those practices now need to be applied to the specific concerns AI is introducing into the workplace.
1. Communicate clearly and consistently about the “why”
If leaders talk about AI only in terms of productivity or efficiency, employees may hear a different message: that they are expected to keep up, figure it out, and avoid asking too many questions. Organizations can help reduce that uncertainty by being explicit about why they are adopting AI, how they expect employees to use it, and where the guardrails are. That includes naming what AI will and will not be used for, how it may affect roles or workflows, and what support employees can expect along the way.
For inclusion leaders, this is a place to push for communication that does more than announce new tools. The goal is to build transparency, invite questions, and make it safe for employees to say, “I do not understand this yet.”
2. Equip managers to model psychological safety
Managers play an outsized role in how employees experience AI adoption. A company can communicate that experimentation is encouraged, but if a manager treats confusion as incompetence or questions as resistance, employees will quickly learn to stay quiet.
To prevent that, managers need guidance on how to create space for learning, normalize uneven levels of AI fluency, and respond productively when employees raise concerns. Simple behaviors, such as admitting what they are still learning, inviting questions, discussing risks openly, and recognizing responsible experimentation rather than rewarding only polished outcomes, can go a long way.
Inclusion leaders can help by giving managers language, conversation guides, and team practices that reinforce psychological safety in the day-to-day moments when AI adoption actually happens.
3. Make AI training a safe place to learn
AI training should reduce uncertainty, not reinforce it. When training assumes everyone has the same starting point, employees who are less familiar with the tools may feel behind before they have even had a chance to learn.
That is why AI training needs to provide relevant examples, role-specific guidance, opportunities to practice, and clear expectations for responsible use. Just as important, it should create space for employees to ask questions, make mistakes, and build confidence over time.
For inclusion leaders, the opportunity is to make sure training does not work solely for early adopters. Training should account for different starting points, learning needs, access barriers, and levels of technical confidence so that more employees can participate in AI adoption in a meaningful way.
The Bottom Line
Companies are making big bets on AI, but they will not realize the full value of those investments if employees are afraid to use the tools, question the outputs, or experiment. A recent survey found that employers see adaptability, leadership, and change management as critical to success in the age of AI; none of those capabilities can be developed in a culture where people do not feel safe to learn, speak up, and try.
That is why inclusion leaders have an important role to play. They understand how trust is built, how employee voice is encouraged, and how workplace experiences differ across employee populations. As AI reshapes work, inclusion leaders’ expertise can help organizations move beyond implementation and toward adoption that is more effective, responsible, and inclusive.
Kayla Haskins is an Associate Director, Product Marketing at Seramount. In this role, she supports DEI Practitioners and Talent Leaders in creating more inclusive workplaces by providing valuable insights and resources through webinars, blog posts, guides, infographics, and more.
With nearly a decade of experience in the technology and non-profit sectors,
Kayla Haskins is an Associate Director, Product Marketing at Seramount. In this role, she supports DEI Practitioners and Talent Leaders in creating more inclusive workplaces by providing valuable insights and resources through webinars, blog posts, guides, infographics, and more.
With nearly a decade of experience in the technology and non-profit sectors, Kayla excels in translating complex ideas into clear, actionable concepts. She is passionate about storytelling and is dedicated to addressing today’s most pressing workplace issues to drive meaningful impact.
Kayla holds a degree in English and Creative Writing from Dickinson College. She lives in Silver Spring, MD with her partner, Nick, and their dog, Zero. In her free time, she enjoys hiking, reading, and spending time with family and friends.
