Most HR leaders have lived through more “new tool rollouts” than they can count.
New platform. New login. New training. A few weeks of confusion. And then (eventually) it becomes part of how work gets done.
But AI adoption isn’t like that. Not really.
AI doesn’t just sit quietly in the background like a system upgrade. It interacts. It responds. It influences how people think, write, decide, and communicate.
So here’s the shift that makes AI adoption a whole lot easier:
Treat AI less like software… and more like a new coworker.
Not because it’s human (it’s not). But because it changes the human dynamics of the workplace in a way most software never has.
Why AI Adoption Feels Different
When teams adopt a new tool, say a project management platform, people might get frustrated with the change, but the tool isn’t shaping the tone of a difficult email or brainstorming strategy for a big meeting.
AI does.
It can draft messages, summarize conversations, suggest next steps, and create first versions of work that used to live only in someone’s brain.
And that’s why AI adoption triggers very real workplace questions like:
- “If AI can do this, what happens to my role?”
- “Am I allowed to use it for this?”
- “Is everyone else using it and I’m behind?”
- “Wait… are we trusting it too much?”
Those questions don’t pop up with most software launches but they will if that software starts acting like a collaborator and “talking” to you.
A Helpful Framework: Think “Forming,” Not “Launching”
At Darcy Luoma Coaching & Consulting, we talk a lot about how high-performing teams don’t just happen—they’re built intentionally, one interaction at a time.
That same truth applies to AI adoption.
Bruce Tuckman’s stages of team development begin with Forming.
It’s the “we’re polite, we’re curious, and we’re all trying to figure out what’s happening” phase. That’s where teams start with AI as well.
When AI is the newest presence on the team, and people are watching closely to see:
- how it’s used
- who’s “in charge” of it
- what’s considered acceptable
- what’s rewarded (or judged)
In other words… your culture is forming around AI whether you mean it to or not. So how can you be thoughtful during this forming stage with AI?
Step 1: Start With the Job, Not the Tool
AI is shiny. It’s fun. It’s everywhere.
And that makes it incredibly easy for organizations to start using AI tools without any idea of why.
That’s the workplace version of hiring someone and then saying, “We’ll figure out their role once they get here.”
Instead, start with one question: What are we trying to make easier, faster, or better?
For HR leaders, that might mean:
- speeding up first drafts of communication
- improving consistency in policies or messaging
- reducing time spent summarizing or documenting
- helping managers prep for employee conversations
- organizing feedback themes or engagement insights
Once the job is clear, then the tool choice becomes a lot easier.
Step 2: Define AI’s “Role” on the Team
If AI is a coworker, it needs a role.
Not a vague role like “helpful assistant,” but a real one, such as:
- Drafting machine (creates a strong first draft fast)
- Brainstorm buddy (generates options and fresh angles)
- Mess-to-message translator (summarizes notes into something usable)
- Theme detective (spots patterns across feedback)
- Process mapper (turns a messy workflow into clear steps)
- Template standardizer (keeps docs consistent in tone and format)
- Microlearning designer (breaks big topics into bite-size practice)
- Resume summarizer (pulls key experience into quick highlights)
And along with the role comes the boundaries.
AI is great at producing something. It’s not great at guaranteeing it’s accurate, aligned, or wise.
So part of the “job description” needs to include what it can’t do, like:
- replacing human judgment
- making final calls that impact people
- handling sensitive info without safeguards
- being the voice of the organization without review
When AI adoption goes sideways, it’s often because AI was brought in without a clearly defined role so it starts wandering all over the place. Kind of like new employees when not given clear directions…
Step 3: Assign Ownership (Yes, Even for AI)
A lot of organizations adopt AI in a way that’s basically:
“Everyone… go try it. Good luck.”
Which sounds empowering until you realize nobody knows:
- what “good use” looks like
- what’s allowed vs. not allowed
- where to ask questions
- how to improve usage over time
So here’s a simple question every HR leader should be able to answer: Who owns AI adoption in this organization?
Ownership doesn’t mean one person does all the work but rather who is responsible for providing clarity. Who is defining what success looks like in the first 30, 60, and 90 days?
Step 4: Set Expectations Out Loud So People Don’t Guess
When a new coworker starts, you don’t just onboard them. You’re onboarding them onto the team.
You let the team know what this person is here to do, how (or if) they’ll work together, and what the handoffs will look like. Even people who won’t work with the new hire day-to-day still need context, because nobody wants a new hire ignored or people wondering why they are in a meeting.
AI adoption works the same way.
Your team needs clarity on:
- What AI is here to help with (and what it shouldn’t touch)
- When to use it (and when not to)
- Who will be using it directly (and what support roles others might play)
- How AI-created work should be reviewed (so nothing gets treated as “done” just because it looks polished)
- What to do when it’s wrong (because AI can be confidently wrong, especially at the start)
The goal here isn’t perfection but rather making sure nobody’s ignoring it, guessing about it, or quietly working around it.
Step 5: Make Space for Mixed Feelings
One of the most overlooked parts of AI adoption is that it’s not just operational—it’s emotional.
People can be excited, skeptical, nervous or likely a combination of all three.
If you skip that reality, you don’t eliminate resistance… you just drive it underground.
Instead, emphasize compassion and normalize the full range of reactions:
- “It’s okay if this feels weird at first.”
- “We’re learning together.”
- “We want to be asking all the questions.”
More discussions at the start will create the foundation for the tougher conversations that will inevitably come as the team moves to the next stage: Storming.
The Bottom Line: AI Is Human-Adjacent, Not Human-Equivalent
AI doesn’t need onboarding snacks or a welcome lunch.
But it does need thoughtful integration, because it affects how humans:
- communicate with each other
- solve problems
- share credit
- make decisions
- trust the work
That’s why AI adoption shouldn’t be treated as “just another system launch.” It’s a new hire.
And when you treat it that way, with a clear role and expectations, you get something most organizations are actually hoping for: AI that supports the team instead of disrupting it.
Want help forming the right AI strategy for your team?
Download our free guide: Making AI Part of the Team: Your Guide to Smart Integration.
Or book a 20-minute consult with Jill to talk it through.
FAQs: AI Adoption + Team Forming
What is AI adoption?
AI adoption is the process of introducing and using AI tools in daily work to improve speed, quality, or consistency while also building the norms, skills, and trust needed for teams to use them responsibly.
Why does AI adoption feel different than rolling out other software?
Most software supports tasks in the background. AI supports thinking work, like writing, summarizing, and decision support, so it affects communication, confidence, and team dynamics in a way traditional tools usually don’t.
How can HR leaders support successful AI adoption?
HR leaders support AI adoption by setting clear goals, defining appropriate use, creating guidance for managers, building training into workflows, and making space for questions and concerns early.
How do you introduce AI to a team without disrupting culture?
Treat AI like a new coworker: define its role, set boundaries, assign ownership, and communicate expectations clearly so teams don’t default to confusion, avoidance, or inconsistent use.
What are common mistakes organizations make during AI adoption?
Common mistakes include adopting tools without a clear purpose, skipping communication, assuming everyone will “figure it out,” lacking review standards, and ignoring employee concerns about trust, privacy, and job impact.
What are the best ways to set expectations for AI use at work?
Start by clarifying what AI is for (and not for), where it can be used, who reviews AI output, what data should never be entered, and what to do when AI gets it wrong.
How can teams measure success in AI adoption?
Successful AI adoption can be measured through time saved on routine work, improved consistency in communication, increased manager confidence, reduced rework, and clearer workflows—along with healthy norms around review and accountability.
Want to grow a strong team? Our Leader’s Guide to Building Stronger Teams was created to help you do exactly that!
