There’s a pattern playing out in organizations right now, and it’s frustrating to watch. Leadership gets on stage, calls AI mission-critical, and then hands it off to IT or spins up a small task force to “figure it out.” Six months later, everyone’s surprised that nothing really changed. In episode six of the AI Agent and Copilot Podcast, host Shawn Dorward, COO at Innovia Consulting, gets direct about why this keeps happening and what leaders actually need to do differently.

The Podcast is hosted by Dynamic Communities, the home of Summit NA!

Click here for the full video or the audio file from Spotify.

Key Takeaways

• You can delegate tasks. You can’t delegate transformation. There is a huge difference between asking employees to try Copilot and asking them to lead the organization’s AI transformation. Telling people to experiment, find some use cases, and report back may sound like empowerment, but it can also be a very convenient way for leadership to make AI optional. And as I’ve said before, AI adoption isn’t a choice anymore for organizations that want to remain competitive.
• AI isn’t just another software rollout. If AI is changing how work gets done, how decisions get made, how customers are served, and how value is created, then we’re not talking about a technology implementation anymore. We’re talking about an operating model change. That’s why I believe AI adoption is a leadership problem, not a technology problem. This isn’t something you hand to a task force and check back on in six months. It belongs with leadership.
• Leadership has to own the narrative. If AI only comes up in IT meetings, innovation meetings, or a special steering committee, you’ve already sent a message that it’s a side project. AI should be showing up in strategy discussions, leadership meetings, performance conversations, planning, and priorities. The people talking about AI in your organization cannot only be the technical people. The business has to own it too. That requires the same kind of fundamental mindset shift we’re asking employees to make.
• Connect AI to real work, not just experiments. Experimentation absolutely has a place, especially when you’re helping individuals get comfortable with the technology. But organizationally, AI has to move beyond experiments pretty quickly. It needs to connect directly to real processes, real customer experiences, real decisions, and real business outcomes. Otherwise, it stays interesting instead of becoming important. Moving toward true AI maturity means making that transition from experimentation to the way the business actually operates.
• Leaders have to model the behavior. You don’t need to become the company’s AI expert. But you do need to visibly use it, talk about where you’re using it, share what’s working, and be honest about what you’re still figuring out. That behavior matters. When leaders are actively learning and using AI themselves, it signals that this isn’t just another initiative being pushed down into the organization.
• Performance expectations eventually have to change too. If AI is going to change the way work gets done, then at some point it also has to change what we expect from people. Employees need to understand what that means for their role, their priorities, and how success is measured. If we introduce AI but leave every expectation exactly the same, people are naturally going to protect the way they’ve always worked.

The big takeaway for me: AI transformation has to be owned from the top. If leadership treats it like an experiment, employees will too. The level of adoption you get will usually reflect the level of ownership leadership was willing to take.

Click below to listen to the Spotify audio version

Thanks for reading!

Shawn Dorward

Microsoft MVP, Business Applications

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