This blog series is the collaborative work of the Udemy Learning team, which includes Melissa Daimler, Chief Learning Officer; Justin Mass, Sr. Director Enterprise Learning; Joshua Ehrenreich, Senior Learning Program Manager; John O’Neill, Senior Learning Partner; Lauren Hauser, Learning Program Manager; and Vicki Lang, Learning Designer.

Getting teams on board and using Generative AI in the flow of work is mission-critical. Without those skills, teams and their companies will struggle to keep pace with technological change. They will miss out on an increasingly necessary ingredient for innovation and to maintain a competitive edge. 

Our first post in this series explored a model learning program for upskilling teams using new generative AI technologies. In this post, we will consider how to make change management a focus during the learning process to improve outcomes.

Change management guide: Driving better learning outcomes 

As you introduce your team to Generative AI, integrate the following approaches to engage learners more effectively and help them succeed. 

Note that while planning how to implement these tools with your team, it’s important to consider how to do so responsibly. Confidential and sensitive information is at particular risk when introduced into AI tools. Whether you are enabling a team or a company, we suggest you consult with your legal advisor for guidance on how to properly protect your company’s information. 

Approach #1: Commit the time to learn generative AI skills — as a team

For leaders of teams, declaring a focus on learning is not enough. Teams easily see through the rhetoric when leaders declare a focus but offer no follow-up. An authentic focus on learning requires space and time carved out of busy work days to acquire new skills. Often, the leader of a team is best positioned to ensure this takes place. 

Set aside time that you already have, like a team meeting. For example, commit half of a meeting, three times a quarter, to learn together.

Kick off each meeting with an agenda and include an asynchronous assignment following your time together. Identify a few team members to bring this to life rather than relying solely on a team manager or leader.

Approach #2: Prepare people to succeed

Generative AI technology is a new tool requiring new skills. While learning that builds upon prior knowledge and previous learning is effective, additional measures can help people become more skilled more quickly.

In the first meeting, begin with small group practice time in the tool on a non-work-related prompt. The small group reduces the pressure of solo efforts, and because the practice is non-work-related, people feel more at ease to experiment. Consider using it to plan an upcoming vacation or meal planning.

Generative AI tools are not the same as traditional search tools. Providing pre-work that helps teams understand how to engineer prompts and talking as a team about this topic early on is key. 

Approach #3: Celebrate wins

As people use these tools more and more often and with greater efficacy, they will discover ever more ways to get real-world value from them. Don’t mandate this process, but celebrate it when it happens.

When your team seems comfortable using the tool, shift the focus from general experimentation to experimenting with sample use cases that are meaningful to their specific roles and responsibilities. Allow your team to take the lead on generating these ideas to encourage ownership and creative experimentation, making them more likely to continue using Generative AI.

Create a space for the team to share wins with Generative AI, and follow up each with a short discussion of what was learned, how work quality improved, whether time or dollars were saved, or how individual team members saw benefit. 

Approach #4: Expect varied levels of enthusiasm

With all new forms of technology, people fall on a curve when it comes to early acceptance — or the absence thereof. Generative AI is no exception. Don’t seek to persuade your team that they should be using the tool; seek instead to familiarize them with how to do it. As people become more comfortable with its usage and aware of its capabilities, check in and see if their opinion is evolving.

The goal here is to become familiar and experiment with a new technology, not to mandate how it will be used. Encourage constructive debate within your team to arrive at a collective point of view. If you want to share your long-term vision for Generative AI, focus on communicating it later once the team is comfortable using it.

Approach #5: Ensure consistent and responsible usage

While learning about this tool, use the opportunity to discuss any emerging norms and expectations for use. Norms are most effective when surfaced bottom-up rather than top-down, so don’t shy away from discussing tough questions with team members. 

For example: What is our policy for attributing usage? How do we ensure the correct use of information and avoid plagiarism? How can we maintain business and customer confidentiality, if necessary? Are there scenarios where we feel that usage of Generative AI is not appropriate? It is likely that your organization will generate official policies around these points; you can share the norms and guiding principles that your team has documented to add to organizational thinking on these points. 

By integrating these approaches into your learning process, you will guide your team more effectively through acquiring the generative AI skills they need to perform their jobs more productively, strategically, and effectively. In our final post in this series, we will examine a use case from Udemy’s internal Learning team. We will discuss how our team acquired generative AI skills, the challenges we addressed through that process, and how that led us to meaningful outcomes. 

Read all the articles in this series: