Many businesses are moving beyond experimenting with AI and starting to buy ChatGPT, Copilot, Gemini, Claude, or AI features in software they already use. Buying licenses isn't the same as actually deploying AI inside your business. The more useful question is:
“How do we help our people actually use AI well?”
Your team probably isn't starting from the same place. One person may barely use AI and still think of it like a better Google search. Another may use it daily for research, writing, analysis, or meetings. Someone else may already be experimenting with agents, automations, or connected company systems. Giving all three the same license and saying “go use AI” isn't much of a deployment strategy.
Good AI deployment needs more than software
It usually means combining:
Clear expectations about where AI should help.
Training tied to real work, rather than generic prompting.
Policies and guardrails around tools, data, review, and accountability.
Internal champions and mentors who can help other employees learn.
Shared learning so useful discoveries become organizational knowledge rather than staying with one employee.
You don't want novice users left behind, but you also don't want your advanced users operating completely rogue. The goal isn't to slow them down. It's to turn individual experimentation into something the organization can learn from and build upon.
Give your team a reason to experiment
One approach I particularly like is creating an internal AI hackathon, challenge, or contest. Ask employees to find one real part of their work they could improve with AI. Give them some time and reasonable guardrails, let them experiment, then have people demonstrate what they built or learned.
The winners don't necessarily need to create the fanciest agent. Reward things like time saved, a better customer experience, fewer repetitive steps, or a smarter way to complete existing work.
Then champion those examples internally.
Peer evidence can be much more convincing than leadership simply announcing that everyone should use AI. A coworker saying, “Here's what I tried, here's what it saved me, and here's what I get to spend more time doing now,” can also help address one of the biggest fears around AI: using it doesn't automatically mean eliminating someone's job; it means career growth.
Done well, AI can let people explore new responsibilities, develop new skills, improve their value to the organization, and grow alongside the technology.
What to do this week
Take a quick inventory:
Who has access to AI?
Who is actually using it?
Who is getting meaningful value?
Who needs help getting started?
Who is doing advanced things the rest of the organization could learn from?
Then choose one small adoption activity: pair two employees, hold a short show-and-tell, document one successful workflow, launch a small AI challenge, or create the first version of your AI-use policy.
Deployment means more than everyone having an account. It means your people understand how AI fits their work, how to use it responsibly, and how lessons learned by one employee can benefit the organization.
I've spent a lot of time studying how leading-edge organizations are approaching AI adoption, while also drawing on decades of experience helping businesses manage technology change. If you're wondering how to structure this within your own company, reply or reach out. I can help you think through practical approaches for your team, culture, and AI maturity level. If interested, I could also offer to help you directly.
Your Tech Pal,
--Joshua
Disclaimer: I use AI to help write emails like these. I originate, review & edit all AI-assisted work I publish.
0 comments