The meeting starts the way these meetings usually start. Someone in leadership asks, “What’s our AI plan?” And every head in the room turns toward the IT director.
It feels logical. AI is technology, IT handles technology, so AI must be IT’s job.
Here’s the problem: it’s only half true. And the half that gets missed is the half that determines whether your AI investment pays off.
The two sides of AI readiness
Every organization that adopts AI well is solving two different problems at the same time.
The business side is about people and work. Can your loan officers, your marketers, your paralegals, your member services team use AI in their daily workflows? Do they know what to delegate to it, how to describe what they need, how to judge what comes back, and how to stay diligent about quality and accuracy? That’s adoption, training, and judgment. It’s a people problem, and it lives in every department.
The technical side is about infrastructure and trust. What tools are approved? Where does your data go? Who sets the usage policy? How do you govern AI so it meets the standards your regulators, clients, and board expect? That’s governance, security, and IT strategy. It’s a systems problem, and it lives with your technical leadership.
Most companies staff one side and hope the other takes care of itself. It doesn’t.
Train your people without governance, and you get enthusiastic employees pasting client data into free tools nobody vetted. Build governance without training, and you get a beautiful policy document sitting on top of a workforce that never changed how it works. Buy the tools without either, and you get licenses on the books that nobody logs into. Either way, the investment stalls.
The market has already priced this in
If you want proof that both sides matter, look at what companies are paying for them.
Robert Half’s 2026 Salary Guide found that 87% of technology and IT leaders now offer higher salaries to candidates with specialized skills. The skill commanding the biggest premium? AI, machine learning, and data science, cited by 59% of leaders, with cybersecurity close behind at 52%.
Read that again from a business owner’s chair. The market is telling you that people who combine AI capability with security judgment are scarce and expensive. You have two options: pay the premium to hire them, or build those capabilities in the team you already have.
For most organizations, especially in professional services and financial services where trust is the product, the answer is both practical and encouraging: your existing team already knows your clients, your compliance environment, and your business. They don’t need to be replaced. They need to be trained, and they need a framework for using AI responsibly.
How we built our practice around both sides
This is why our work at Daystar New Media covers two lanes on purpose.
I lead the business side: hands-on AI training and implementation for teams, built around practical frameworks like the 4Ds (Delegation, Description, Discernment, Diligence). My focus is turning nervous or curious professionals into confident, capable AI users, because AI education isn’t an event, it’s a process.
Gerald Cullison, my business partner and co-owner, anchors the technical side. Gerald spent more than 15 years at Hewlett-Packard as an enterprise solutions architect, designing and supporting infrastructure for organizations where reliability and security were non-negotiable. Today he brings that enterprise discipline to AI governance and usage policy, using the NIST AI Risk Management Framework to help organizations put guardrails in place before problems show up.
One conversation, both sides covered. Your team learns to work with AI, and your leadership gets a governance foundation your board and regulators can stand behind.
The question worth asking your leadership team
Not “should we do something about AI.” You already know the answer to that one.
The better question: which side of AI readiness have we actually staffed, and which side are we hoping takes care of itself?
If the honest answer is “we’ve got a policy but no training,” or “our people are experimenting but nobody’s governing it,” or “neither, if we’re being real,” that’s not a crisis. It’s a starting point.
Ready to cover both sides? We deliver custom AI team training and governance foundations your leadership can stand behind. Start a conversation about training for your team →
Michelle Cullison is an AI speaker, consultant, and trainer who equips professionals and teams to put AI to work. She is the creator of AI Bootcamp for Busy Professionals and co-owner of Cullison AI with her husband and business partner, Gerald Cullison.
Source for salary data: Robert Half 2026 Salary Guide, technology section (roberthalf.com/us/en/insights/salary-guide/technology)
This article was drafted with AI assistance and edited, fact-checked, and finalized by me.