Worried about AI at work? Avoid these 5 leadership mistakes with your team

Artificial intelligence may be transforming the workplace, but for many employees, it’s fueling uncertainty instead of excitement. According to a 2025 Pew Research Center study, 52% of U.S. workers worry AI could disrupt or replace their jobs. And an August 2024 SHRM survey found that nearly half feel unprepared for automation, while 95% say they don’t trust their organization to manage the shift in a way that benefits everyone.

How managers address these concerns can make or break team morale and productivity. Experts say clear, honest communication is critical, but the wrong message can backfire, fueling fear instead of trust. Whether you’re rolling out new tools or just starting the conversation, it’s important to engage your team with transparency, context and empathy.

Below, two human resources experts break down five common mistakes to avoid when discussing AI with your team and provide guidance on navigating the discussion more effectively.

1. Acting like it’s no big deal

According to the World Economic Forum, when managers dismiss or avoid discussing AI concerns, they often create bigger problems down the road.

“Business leaders can’t bury their heads in the sand and hope for the best,” says Eric Mochnacz, director of operations at Red Clover HR in New Jersey. “They must have up-front discussions about the benefits of AI in their business, the drawbacks, the potential impacts and the areas where they’ll not allow AI usage.”

Chad V. Sorenson, president of Florida-based Adaptive HR Solutions, agrees that direct communication is key. “Employees may feel AI threatens their jobs and may question leaders’ motives for introducing AI tools,” he explains. So, “address the fear and explore how AI can augment workflows and streamline repetitive tasks rather than replace workers.”

Takeaway: Don’t downplay concerns about AI. Acknowledge employee fears openly and explain how AI will support, not replace, their work.

2. Throwing around ‘AI’ without defining it

AI isn’t just one thing. Mochnacz explains that there’s a significant difference between using generative AI to enhance email communications and utilizing AI chatbots to manage all customer interactions. Without these distinctions, employees don't understand what to expect from their workplace changes or how they can remain relevant.

“AI is such a buzzword, and leaders haven’t taken the time to define it and understand the differences,” says Mochnacz. “I’ve been in meetings where people ask, ‘Can you do this with AI?’ or ‘Everyone’s talking about AI, so we have to do something with it.’”

He emphasizes the importance of clarifying the fundamentals:

• What types of AI are we using and why?
• What tasks will it/they replace or help with?
• How much do we trust the tools to handle those tasks?

Takeaway: Don’t use “AI” as a vague catchall. Clearly define what types of AI you’re using, what they do and why they matter to your team.

3. Failing to explain the why

“Any time leaders announce a new program or procedure without employee buy-in, there could be fear, skepticism or anger,” Sorenson cautions.

Instead of simply telling employees what’s changing, explain why the company needs AI. How does it fit into broader business goals? This context helps employees understand their role in the transition rather than viewing it as a threat.

“Ongoing two-way feedback is critical for continued refinement of how teams use AI to improve workflows, processes and results,” notes Sorenson.

Takeaway: Don’t skip the context. Explain why AI is being adopted and how it supports your team’s goals to build trust and buy-in.

4. Overhyping what AI can do

“Leaders promising that AI will handle everything don’t have a clear understanding of its possibilities and limitations,” Sorenson says. For instance, AI can help employees understand benefit plans. But it can’t handle nuanced harassment complaints or mental health concerns. “AI systems must be trained to understand when a human must intervene,” he adds.

Mochnacz says the problem gets worse when leaders promise capabilities that may never materialize. “We have no idea what AI is going to be able to do in a month, three months or a year,” he emphasizes. So, it’s better to focus on specific, tested use cases rather than grand predictions about AI replacing everything.

Takeaway: Avoid making big promises. Focus on what AI can realistically do today, not speculative future capabilities.

5. Leaving people out of the process

“Whenever there’s a business, industry or technology shift, involve those it may impact,” stresses Mochnacz. “Have up-front, direct conversations with your people about their roles and how they see AI helping them be more effective.”

A recent MIT Sloan working paper finds that the most successful generative AI deployments consistently involve frontline workers from the earliest stages through rollout. Drawing on over 50 in-depth interviews, MIT researchers demonstrate that when employees help define the problem, co-design workflows, experiment with tools, and shape fair transition policies, not only does adoption improve, but worker productivity and job quality also rise.

The key here is framing AI as a collaboration partner rather than a threat. Mochnacz explains that when leaders present AI as a good reality for everyone, employees will engage with the technology. But when the message becomes "prove AI can’t replace you," workers resist because it feels like an ultimatum.

Takeaway: Don’t make AI decisions in a vacuum. Engage employees early and frame AI as a tool to support their work, rather than compete with it.

What successful AI communication looks like

Sorenson says poor AI communication shows up in obvious ways. You might notice more pushback in meetings, higher employee turnover or a spike in anxious watercooler conversations. These signals suggest that employees feel excluded or uncertain and may be bracing for the worst.

In contrast, when communication is clear and inclusive, team engagement improves. “If your AI communication strategy is successful, employees should engage in the conversation,” Sorenson notes. “They’ll make suggestions to continue to refine its use, and demonstrate an increased productivity level.”

Look for those signs of healthy adoption: employees asking questions, suggesting improvements and using AI to work more efficiently. When teams feel empowered, not threatened, you know you’ve struck the right balance.

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