Most software tools aim to improve how users accomplish tasks, making things easier or more efficient. But then there’s AI systems, which often do more than that and they can disrupt workflows entirely, requiring users to change how they operate. This disruption happens because AI doesn’t just assist it also often automates parts or entire activities, reshaping how work gets done. It can be seen as scary to some, and fantastic to others, so how do we communicate this so that everyone is happy?

Let’s break this down with some examples. If we think about unlocking your phone with facial recognition, you no longer manually type in a password. While it’s faster & more secure, it changes the simple habit of entering a PIN, requiring users to adjust to this new way of interacting with their device. This may seem simple, but it’s still requiring a change of habit.

Or maybe consider customer service departments adopting AI agents. In some cases, these systems don’t just assist human agents; they replace entire teams workloads, completely transforming workflows around customer support. While this can streamline operations, it demands a thoughtful approach to change management to ensure successful adoption so that the user is happy and also the worker who may now transition to an escalation role is also happy.

Making AI Work for Users

Disruption doesn’t have to mean resistance. A thoughtful change management strategy can turn hesitation into adoption. The first step is proactive user education. Early in the rollout, communicate why users should embrace the system & more importantly, how it benefits them personally. Avoid vague claims like “it’ll help the company.” Instead, focus on specific, tangible advantages like saving time, reducing repetitive tasks or improving results.

For example, with Copilot Studio, organizations have introduced internal agents (previously called Copilots) to help employees with complex tasks like generating reports or gathering information from technical documents. While some workers initially worried these tools might replace their roles, proactive communication & demonstrations focused on how Copilot Studio enhances their work, making tedious tasks faster & giving them more time for strategic, impactful work. The result? Employees adopted the system, recognizing it as a partner rather than a competitor.

Deploy Gradually, Train Thoroughly

Next, when deploying the system, take it step by step. Start with early adopters, those comfortable trying out new technologies & gather feedback. Use their insights to refine the system before rolling it out to the broader user base. This approach builds trust and confidence within the organization, especially for those less comfortable with change.

Training is essential for everyone, not just early adopters. A popular method is the train-the-trainer model, where a small group of early adopters becomes the go-to resource for training others. This peer-to-peer approach makes the learning curve easier, especially in large organizations.

Monitor & Adjust

Finally, after deployment, monitor how the system is being used. Compare the adoption rate to your initial expectations. If usage is below targets, this could indicate a need for additional training or further communication about the system’s value. For example, if employees using Copilot Studio aren’t engaging with it as expected, it might mean they need more guidance on how to integrate it into their workflows or adjusting it to meet the users needs.