About the Blog
Leading a team to adopt AI can feel intimidating. It’s a new tool that is unfamiliar. As leaders we often feel pressure to have all the answers. With AI, chances are we don’t, and that’s okay.
The truth is, implementing AI isn’t a leadership challenge. It’s a change management challenge. That’s really good news because leaders have been navigating change for decades and have many strategies to help teams navigate change. Reframing AI integration as change management turns something that feels unfamiliar into something leaders are already equipped to lead.
One of my favorite change management strategies is the 2% rule. It works with internal teams but also works well with campus partners. In this model, change happens through subtle iterations over time, as opposed to trying to make multiple changes at one time.
I first saw the value of this approach when working with a campus partner nearly a decade ago on a viewbook. The MarComm team wanted to make lots of updates to the content, the tone, the images, and the design. When they suggested this to the partners in Admissions, they were met with resistance because it was too much change. After realizing this, I changed the approach to a slower more iterative process. In year one we focused on updating the copy, and in year two we worked on new photos.
Then in year three we focused on an entire new design that integrated the reworked copy and photos. This approach worked well for this project. The reason is that small, incremental changes felt palatable and didn’t overwhelm anyone. However, over time the overall change was significant. After seeing this approach work so well, I’ve used it dozens of times since and find that it is a great strategy for significant changes because it makes the change feel manageable by making it incremental.
Utilizing the 2% rule also helps team members gain confidence and develop new skills. Instead of trying to overhaul an entire project or learn several new tools at once, team members can focus on adjusting just one part of the work. This helps people to focus their effort on a single area, rather than trying to manage everything changing at once. Creating a clear, singularly focused priority, whether it’s adjusting a process or honing a new skill, team members are far more likely to succeed.
One caveat: For the 2% rule to work, there needs to be a strong leader helping to drive the direction. If the desire is to iterate over time, that only works well if the leader can see the full picture of where to go and help develop a plan to get the team there. Even if it’s a long-game strategy, there should be a strategy so that shifts that are happening are moving the team and the work in an overall direction. If there’s not an overall plan or end goal, iterating over time won’t have the same outcome. Instead, it will feel like change without a specific purpose.
Four ways to use the 2% Rule to implement AI
Project kickoffs and debriefs – One way to employ the 2% rule is by focusing on where AI can be implemented in projects. By using a kickoff meeting to brainstorm how AI could save time or resources on the project or could make the overall project stronger helps everyone involved understand use cases where AI may make sense. Then, the team can talk through whether this AI use case makes sense and how to try it. Trying a couple of small ways during the project likely doesn’t feel overwhelming and helps the team get comfortable considering AI, without overwhelming them. If the project is already in motion, this same strategy can be utilized in a debrief meeting. There, the conversation would shift to focus on how the project might iterate next time to include AI.
Skill development – Another way to use the 2% rule is in skill development. If the team is hesitant to use AI, chances are that is partly because they are not familiar with the tools available and how to use them. Instead of expecting everyone to become a master, focus on a few key skills, and as people on the team become more comfortable incorporate other skills. For example, start with how to write a good prompt. Then, focus on how to check content. Helping the team learn foundation skills and then build on them helps increase their comfort level with AI. If the entire team is working on learning these skills, a great strategy is to coordinate time to talk about it as a full group, which helps everyone learn from one another and builds confidence that no one is behind and everyone is learning together.
Consistent implementation – Another way to use the 2% rule is asking the team to use AI in some capacity on every project they take on. Given the wide range of projects that MarComm teams see in a year, this approach will likely naturally create multiple opportunities to experiment with AI. For example, a writing project might be a great place to test content development, while a magazine might be a great way to explore project management. Because most projects are different, that creates multiple scenarios for the team to practice using AI and get comfortable with the technology.
Quality review – For teams that are naturally hesitant about AI, using the tool for quality review is a great 2% strategy. Instead of using AI to help with the work itself, the team can use the tool to provide feedback. This keeps the team, at least for now, as the content generator and has the AI tools helping look for holes in the team’s work, missed opportunities or ways to make the work stronger. This analytical approach can help the team see the quality of work that AI tools can provide and may help teams more fully consider AI in the future.
Purposeful Approach
Leading with AI adoption doesn’t have to be a massive shift that requires heavy workload adjustments. Instead, using the 2% rule leaders can build confidence, start small, and help hesitant teams become comfortable using AI. It’s all about being purposeful in the approach. By making small shifts to projects leaders can help teams gradually incorporate AI in ways that strengthen their work without overwhelming the people doing it. After all, adopting AI isn’t really about the technology. It’s about leading people through change.
.svg)
.svg)
