Internal Communications and Change Management: AI Champions? Choose Wisely
A recent survey of senior leaders by MIT’s NANDA stated that 95% of Generative AI projects are failing to deliver any notable ROI. Not surprisingly, it got a lot of attention, because most organizations are at this point in their journey. It’s also thought to be overblown.
Whatever the case with the study results, implementing AI projects and promoting widespread adoption is proving more difficult than anticipated and senior leaders are growing frustrated. Early assumptions were that the models were simple enough for people to pick up on the fly. That hasn’t proven true. Resistance to technology, confusion over policies, 'shadow' AI use of non-approved tools, and overly ambitious projects are getting in the way. Companies are having to rethink how they position, message, train, and select use cases AI in their organizations.
How Should Organizations Respond?
It begins with an understanding that a people strategy for AI implementation is every bit as necessary as a technology strategy. Without it, the anticipated increase in productivity and the ever-evasive ROI will be undermined. That means messaging for a supportive culture, offering dedicated learning opportunities, clarifying use policies, and promoting quick wins around 'drudgery reduction' (e.g., email) are all part of the effort.
And so too is identifying 'AI Champions' (the new version of change champions) but there are some specific things to keep in mind. Let’s look at three issues:
1. Choosing for Attitude vs. Aptitude
Focus on finding people who enjoy AI, use it regularly, have tried lots of different types of work (multimedia, iterative prompting, thought partnering) and are naturally approachable, encouraging, and good teachers. Bonus points if they can make it fun, as it takes away the intimidation factor. These may not always be the most advanced AI users in the organization, but they’ll help bring others along on the journey.
2. Start with Stuff People Hate
Going through e-mails, building spreadsheets, or redundant work isn’t fun for anyone. By starting with a simple use to take out the drudgery of an everyday part of work, people will see an immediate benefit, feel a sense of accomplishment, and begin to wonder how else they can use tools. In addition, by starting with current work, it immediately embeds AI use into the employee’s workflow, so it feels natural rather than forced.
3. Embed AI Champions into a Larger Strategy
AI Champions on their own won’t accomplish much. The effort needs to be part of a larger plan that includes consistent messaging, dedicated training, available feedback loops, online resources, and senior leadership sponsorship and encouragement. Many companies have opted to make online self-training available, but that’s proving to have limited effectiveness. Combining self-training with dedicated learning time, in-person or virtual events, and visible senior leader participation significantly improves completion.
What Will Success Look Like?
Beyond metrics such as training access and completion rates, tool usage across the organization, and changing workflows, there are some qualitative success indicators to look for as well. When the culture supports and encourages adoption, you’ll start hearing examples of people using it unprompted in different contexts. Also, you’ll see AI become a foundational part of workflows and AI Champions being pulled into strategic discussions. These are signs that you have built an adaptive culture.
For executives, the message is clear: AI transformation won’t be driven solely by your technology or data investments. It will be driven by people inside the organization who model new behaviors, embed AI into critical workflows, and build trust across teams.
The best Champions act like internal consultants—surfacing constraints, experimenting in real contexts, and bringing others along. Their influence shows up in adoption curves, workflow redesign, team norms, and—most importantly—the quality of output your customers and stakeholders experience.