Managing AI-driven change: Addressing teams’ concerns

Artificial intelligence is changing the way we work at a rapid pace. It promises greater efficiency, new opportunities, and more streamlined processes. But amid all the excitement surrounding these technologies, there’s another reality that deserves just as much attention: not everyone experiences this transformation in the same way.

For some, AI is an opportunity to learn and grow. For others, it brings very real concerns: losing their job, seeing their expertise lose value, having to constantly learn new skills, or losing control over how they work.

These reactions aren’t necessarily obstacles to overcome. Often, they’re signs that people need more clarity, reassurance, and support.

Managing change in the age of AI takes more than a technology rollout plan. It means understanding how people respond to change, building trust, and creating the right conditions for teams to grow alongside technology.

Why does AI raise concerns among team members?

Unlike many technological changes that came before it, artificial intelligence directly affects tasks traditionally associated with human expertise, such as analyzing information, writing, creating, solving problems, and making decisions. It’s no surprise, then, that its introduction can challenge people’s sense of professional identity.

According to Microsoft and LinkedIn’s 2024 Work Trend Index, 53% of people who use AI at work worry that using it for important tasks makes them look replaceable (1).

To help teams navigate AI-driven change, it’s important to recognize that these concerns can come from different places.

Fear of losing professional value

“If AI can do part of my job, will they still need me?”

This question gets to the heart of people’s sense of purpose and professional identity. Employees may worry that their expertise will become less valuable, even if no job cuts have been announced.

How to address this concern:

• Be clear about the organization’s intentions
• Explain how roles and responsibilities might evolve
• Recognize the value of human expertise

If certain decisions haven’t been made yet, it’s better to be upfront about the uncertainty than to make promises you can’t keep.

Fear of not being able to keep up

New tools can leave people feeling like they don’t have the skills to succeed, especially when expectations change faster than opportunities to learn. Some employees may be reluctant to experiment because they’re afraid of making mistakes or revealing what they don’t know.

How to address this concern:

• Introduce learning opportunities gradually
• Create safe, low-risk opportunities to experiment
• Encourage questions as much as you celebrate successes

Digital agility grows when people feel comfortable trying new things without the pressure to master everything right away.

Fear of losing autonomy

When technology changes how work gets done, employees may feel they’re losing control over their decisions or the way they do their jobs. These concerns can become even stronger when new tools are introduced without consultation or when it’s unclear which decisions remain in human hands.

How to address this concern:

• Involve teams in identifying where AI could be useful
• Clarify which responsibilities remain with employees
• Give people genuine flexibility and room to make decisions

Fear of heavier workloads and constant change

AI is supposed to save time. But learning to use it takes time, too. Employees need to understand the tools, adjust their routines, review AI-generated results, and figure out new ways of working together.

According to a 2026 Boostalab study, 73% of respondents identified a lack of time as a barrier to training (2).

How to address this concern:

• Set aside time for learning
• Adjust expectations where needed
• Avoid introducing too many changes at once

Of course, not everyone’s concerns are about how AI might affect their own job. Some people also question its environmental impact, ethical implications, or reliability.

Across a team, concerns might centre on the quality of deliverables, data privacy, or changing professional practices. Whether they’re personal or shared, these concerns deserve to be taken seriously.

Resistance to change: Something to understand, not fight

When AI is introduced, some teams may voice doubts, put off using new tools, or stick with their usual ways of working. It’s easy to label these behaviours as resistance to change. But doing so can overlook the very real reasons behind them.

A Gallup study published in 2025 found that 44% of people who don’t use AI at work say their main reason is that they don’t believe it can help them with their tasks. Only 11% point to a reluctance to change how they work (3).

That’s an important distinction. Low adoption doesn’t automatically mean people are unwilling to change. It may simply mean they don’t see the value, don’t know enough about the tools, or have legitimate concerns.

According to Prosci, organizations can better support change by understanding the underlying reasons for resistance, listening to employees’ concerns, and involving the people affected (4,5).

Instead of rushing to convince everyone, organizations should first try to understand what’s really getting in the way of technology adoption. Some concerns are personal, shaped by individual values, perceptions, or past experiences. Others are shared across a team and relate to work quality, collaboration, or how responsibilities are organized. Understanding these differences helps organizations respond to the concerns that actually exist, rather than treating every form of resistance the same way.

How can organizations support teams through AI-driven change?

Effective change management involves several things working together: helping people understand why change is happening, giving teams a voice, developing their skills, and supporting them as they adapt in their day-to-day work.

1. Be clear about the reasons for change and its impact

Before asking employees to adopt AI, organizations need to explain why they’re introducing it and what they hope to achieve.

• What problems are we trying to solve?
• Which tasks could change?
• How might AI benefit teams beyond improving productivity?

The answers need to be specific enough for employees to understand what the change could mean for their everyday work.

Communicating transparently about change also means being clear about what’s already been decided, what’s still being considered, and which questions remain unanswered.

2. Give teams a voice in the transformation

Technology adoption shouldn’t be something leadership decides on its own and employees are simply expected to carry out. The people doing the work every day understand the processes, know where frustrations arise, and can often spot opportunities where AI could make a real difference.

Bringing them into the conversation early helps identify useful applications, uncover potential risks, and fine-tune practices before rolling out new tools more broadly. This involvement could take the form of workshops, pilot projects, or hands-on experimentation groups.

One simple question can also spark a valuable team discussion: “Which of your concerns are about your own relationship with AI, and which are about your team’s ways of working, responsibilities, or results?”

The key is to give employees a real opportunity to contribute, not just ask for their input once all the decisions have already been made.

3. Build both human and digital skills

Training is an essential part of navigating change. But knowing how to use an interface or write effective prompts is only part of the picture. Teams also need to strengthen their critical thinking, their ability to keep learning, and their capacity to work alongside AI without setting aside their own judgment.

Boostalab’s 2026 report, based on responses from 663 people in Quebec, highlights just how important these skills are. Among non-management employees, human-AI collaboration ranks third among the skills considered most important to develop (32%).

These findings are a reminder that human skills in the age of AI need to develop alongside technical skills.

4. Give managers the tools to support their teams

Managers play a key role in any transformation. They’re often the first people employees turn to when they have questions, want to raise concerns, or need help understanding new expectations.

But these conversations don’t always come naturally. They call for specific skills, including active listening, emotional intelligence, relational courage, and the ability to communicate through uncertainty.

In Boostalab’s study, the three skills most frequently identified as priorities for managers were effective communication (50%), relational courage (46%), and emotional intelligence (45%).

These findings show why leadership development needs to be part of any AI initiative. Managers need guidance, training, and support, not just a list of messages to pass along.

5. Make learning part of everyday work

People don’t become confident using new technology just by sitting through a presentation. They need opportunities to try it, compare results, ask questions, and learn from mistakes. A good place to start is with practical, low-risk situations, along with clear guidelines for protecting confidential information and checking AI-generated results.

To encourage lasting adoption, organizations can build short learning sessions, peer discussions, and opportunities to share experiences into existing work routines. They also need to be mindful of employees’ mental workload and respect their right to disconnect.

The goal isn’t to keep adding training on top of everything employees already have to do. It’s to make learning manageable and sustainable.

How can you tell if AI adoption is successful?

The number of activated accounts or how often employees use a tool doesn’t tell the whole story.

Successful, long-term adoption also depends on how people use AI in their everyday work:

• Do employees know when it makes sense to use AI?
• Can they recognize its limitations?
• Do they feel comfortable speaking up about concerns and suggesting improvements?

Looking at these questions helps organizations assess more than tool usage. It also reveals how employees are developing their autonomy, judgment, and ability to learn together. Organizations should also pay attention to how these changes affect workloads and collaboration between colleagues.

Successful AI adoption isn’t just about how quickly teams start using the technology. It’s about whether they can work with it effectively over the long term.

Empower teams to shape change

Artificial intelligence will keep changing how we work. But successfully navigating that transition takes more than asking employees to adapt faster.

Fears, doubts, and resistance can all help organizations understand what teams need to make lasting change possible.

The real challenge is finding the right balance between technological ambition and people’s ability to adapt. That means communicating openly, supporting managers, creating opportunities to learn, and continuing to invest in strong workplace relationships.

Managing AI-driven change successfully isn’t about getting everyone on board at all costs. It’s about giving people the tools, confidence, and freedom they need to play an active role in shaping how their work evolves.

What if the best way to prepare teams for the future was to give them a chance to help shape it?

References

1. Microsoft & LinkedIn. (2024). 2024 Work Trend Index Annual Report: AI at work is here. Now comes the hard part. Microsoft.
2. Boostalab. (2026). Compétences humaines 2030. Ce que les organisations québécoises doivent développer à l’ère de l’IA. Boostalab.
3. Kemp, A. (2025). Manager support drives employee AI adoption. Gallup.
4. Prosci. (s. d.). The complete guide to managing resistance to change. Prosci.
5. Jamieson, J. (2026). Prosci’s top 10 tactics for managing resistance to change. Prosci.