Most organizations building an AI strategy spend serious time on the right things: governance frameworks, security policies, and responsible AI guidelines. While this groundwork matters, there is a language problem. Shawn Dorward, COO Innovia Consulting explores why it might be the most underrated reason AI adoption fails.

In this episode, Shawn makes the case that every word a leader uses around AI is signaling one of three things to their team: this is optional, this is risky, or this is expected. Soft, vague, or overly cautious messaging signals the first two. Clear, direct language signals the third. The difference between those signals is often the difference between a successful rollout and a slow fade.

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

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Key Takeaways

• “Encouraging” and “experimenting” can quietly kill adoption. When leaders tell people to “experiment with AI” or say they’re “encouraging” employees to use it, what many employees actually hear is optional. And optional things tend to disappear pretty quickly when calendars get full and deadlines start piling up. If AI matters to the organization, leadership has to communicate it that way. An invitation will usually get treated like an invitation.
• Stop making the conversation only about efficiency. Telling people AI will make them more efficient can easily sound like, “Great, now you can do even more work.” That’s probably not the message we intend, but it may absolutely be the message people hear. I think the better conversation is about value. How can AI help someone produce better work, make better decisions, serve customers better, or spend more time on the things that actually matter? People care about doing good work. Start there.
• Be clear about what you actually expect. There is a huge difference between saying, “We encourage you to use AI” and saying, “We expect AI to become part of your daily workflow, and here are three places you can start this week.” One is vague. One gives people direction. If you want different behavior, you have to be specific about what different behavior looks like. Navigating the AI landscape toward true AI maturity starts with that kind of clarity from leadership.
• Audit the language you’re already using. Go back and look at your AI communications—emails, kickoff decks, Teams posts, town halls, whatever you’ve used. Then ask AI itself: “If you were an employee reading this, what would you think leadership expects you to do?” If the answer sounds optional, vague, or overly cautious, that’s probably exactly how your employees are interpreting it too. Fix the message before you blame adoption.
• Soft language feels safer to leaders, but it slows everyone else down. I understand why leaders hedge. Nobody wants to overpromise, sound like they have all the answers, or make a statement today that looks wrong six months from now. But there’s a difference between being realistic and being vague. You can acknowledge that AI is changing quickly while still being very clear about what you expect today. Clarity isn’t arrogance.
• The communication matters because AI adoption is no longer optional strategically. I’ve said before that AI adoption isn’t a choice anymore for organizations that intend to remain competitive. That makes leadership communication even more important. You don’t need a communications degree or a perfectly crafted AI manifesto. You need to be intentional, specific, and willing to say what you actually mean.

The big takeaway for me: If leadership talks about AI like it’s optional, employees will treat it like it’s optional. Your words are setting the pace of adoption long before the technology does.

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Thanks for reading!

Shawn Dorward

Microsoft MVP, Business Applications

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