The real problem with AI adoption
Most people who struggle with AI aren’t struggling because they can’t use it. They’re struggling because they don’t have a clear mental model for when to use it and when to stop. Without that model, every AI output feels like a gamble.
There’s a common assumption in AI adoption: the more you use it, the more confident you get. That’s partly true. But confident AI users aren’t defined by how often they use AI — they’re defined by how deliberately they use it. They know when to reach for it, when to put it away, and when to treat its output as a first draft rather than a final answer.
The goal of this course is not to make you use AI constantly. It’s to give you the frameworks, habits, and judgment to use it effectively — and to feel in control every time you do.
Key Insight
The most dangerous AI user isn’t the skeptic who refuses to engage. It’s the enthusiast who publishes AI output without reviewing it. Confidence is the middle ground: engaged, critical, and in control.
Every time you consider using AI, three questions should run in the background:
Is this a task where AI adds speed or volume without sacrificing quality? Writing first drafts, generating options, restructuring existing content, summarizing long documents — these are AI’s sweet spot. The output is a starting point, not a final answer, and editing is fast.
Does this task depend on information or judgment only I have? Knowing whether a story is newsworthy for your specific audience, understanding a relationship dynamic with a client, deciding whether a statement is safe given your organization’s legal situation — these require context AI doesn’t have and can’t acquire. Human judgment stays in the loop.
Is there a verification step before this goes anywhere? Any AI-generated content that contains facts, quotes, statistics, or external references needs a check before it leaves your desk. Build the habit of treating that check as part of the workflow, not an optional extra.
Most problems with AI in communications work come from one of two failure modes, not from AI itself.
The first is over-delegation: treating AI as an autonomous author rather than a capable but unreliable collaborator. This produces content that’s structurally fine but factually questionable, tonally off, or missing crucial organizational context. The communicator who publishes this output without review is not using AI confidently — they’re using it recklessly.
The second is under-delegation: doing manually what AI could do faster, or refusing to use AI at all because it feels risky. This is a real cost. Communicators who write every first draft from scratch, research every topic manually, and brainstorm alone are leaving significant time on the table.
Confident AI use lives between these two extremes. You use AI where it helps. You stay in the loop where it matters. You review before publishing. That’s it.
Build your personal AI decision framework — a simple set of rules you can apply to any task to decide how much to lean on AI.
Look back at the last five to seven communications tasks you completed — emails, drafts, research, announcements, whatever you worked on. Write them down as a simple list.
For each task, ask: where would AI have added speed or volume? Put a checkmark next to tasks where AI drafting would have saved meaningful time without requiring much additional review.
For each task, ask: where did the work depend on judgment, relationship context, or organizational knowledge AI doesn’t have? Put a different mark next to those. These are your human-in-the-loop moments.
Write three sentences that describe your personal AI use rule — the clearest version of when you will and won’t lean on AI based on what you just observed. This doesn’t need to be formal; it just needs to be honest.
Save your AI decision rule somewhere you’ll see it. You’ll refine it as you go through this course — this is your working version, not a finished document.
