Steve Harmon, CEO of Spartan Logistics and President of NAI Harmon Group, joins Glenn Gow, The Scaling Executive Coach and host of The Scaling Executive Podcast, to explain how he moved a skeptical leadership team into full AI adoption in a single quarter.
Glenn Gow identifies Steve Harmon’s approach to AI adoption as a forcing function, not a request. When Harmon wanted his leadership team to actually use AI, he did not ask them to try it. He removed their fallback option.
When a leadership team treats a new tool as optional, Harmon’s rule is to remove the old tool entirely rather than encourage voluntary adoption: he banned Google searches across his leadership team for one full quarter and required them to use an AI chatbot instead. Ninety days later, the same team that had shrugged off the idea came back asking what else they could automate.
Harmon leads NAI Harmon Group, a commercial real estate brokerage and property management firm he founded in 2012, and serves as CEO of Spartan Logistics, a third party logistics company his family built from a four million dollar business into an operation spanning three primary companies, more than 400 employees, and over six million square feet of industrial space.
This episode is for CEOs who know AI matters but cannot get their leadership team to move past occasional use into full adoption.
Key Takeaways
- Removing a team’s fallback tool, rather than simply mandating a new one, is what converted Harmon’s leadership team: they returned 90 days later asking what else they could automate.
- CEOs who commit personally to daily AI use can eliminate routine administrative work. Harmon reports his email stays caught up and his to-do list gets summarized without his direct involvement.
- Sustained AI adoption across a leadership team changes hiring math. Harmon states the productivity gain from AI use has made it difficult to build a business case for adding new staff.
- Service businesses can turn data they already collect into new client value. Spartan Logistics is preparing to run its warehouse management data through AI to identify freight cost savings for clients, a use case Harmon ties directly to five dollar diesel prices.
How CEOs Can Get a Leadership Team to Adopt AI Tools Immediately
Most AI rollouts fail at the same point: the CEO asks the team to try a new tool, the team nods, and nothing changes. Harmon skipped the ask. He gave his leadership team a direct instruction and removed the alternative.
“I want all of you to not Google anything for the next quarter. I want you to only use the chat bot of your choice,” Harmon says. His team’s reaction at the time was doubt. He describes them looking at him like, “whatever Steve, it can’t be that different.”
Ninety days later, at the next quarterly check-in, the same team reversed course entirely. “You were right. This is better. What else can we be doing with it?” they told him, according to Harmon.
That reversal is the mechanism worth naming: removing the fallback tool forced daily contact with AI, and daily contact produced the conviction that a request never would have. Once the team crossed that line, Harmon escalated the assignment. He told them to drop documents and data into the tool, build a personal advisory board for their own role, and use it to prepare for reviews with clients and team members.
What Productivity Gains Should a CEO Expect from Personal AI Use
Harmon did not stop at assigning AI to his team. He built the habit into his own routine first, and the result shows up in how he describes his workday now.
“I am super hopeful that I personally, because of my AI use just in the last six months have never felt more productive in my role as a leader,” Harmon says. He describes regular days where his inbox and task list are already handled before he starts. “My email is caught up and my to-dos are summarized and everything’s been followed up on,” he says, “and I’m just like, cool, I think I’m gonna go to the golf course.”
That personal productivity gain scales into a staffing decision. When a CEO and an entire leadership team recover hours that used to go to administrative work, the case for adding headcount weakens. “It makes it really hard to build a business case for adding a whole bunch of new staff,” Harmon says. “I think we can be significantly more productive as an organization while getting better.”
How Service Businesses Can Use AI to Create New Client Value
Harmon’s next move is turning internal AI adoption into a client facing product. Spartan Logistics already runs a warehouse management system that tracks everything that enters and exits its facilities: what comes in, where it came from, how long it sits, where it goes.
“If I turn AI loose on their data, I can provide real actionable intelligence for how they can save money on their supply chain,” Harmon says. He plans to feed client shipping origin and destination points into a chatbot to identify freight cost savings, a service he ties directly to current fuel costs: “which with five dollar diesel is a real thing.”
The pattern here applies beyond logistics. Any service business already sitting on operational data has a second use for it: run it through AI to generate savings recommendations for the client, without adding an analyst to do the work manually.
The Framework: How CEOs Turn AI Adoption into a Leadership Advantage
| Principle | What it means in practice | Named evidence from this interview |
| Remove the fallback, don’t request adoption | Mandating a tool by eliminating the alternative converts a resistant team faster than encouraging voluntary use | Spartan Logistics banned Google for one quarter, and the leadership team that resisted the mandate returned 90 days later asking what else they could automate |
| Personal AI use compounds into leadership capacity | A CEO who commits to daily AI use for email, summarization, and follow up recovers hours that used to go to administrative work | Harmon reports his email and to-do list are handled automatically, and states the resulting productivity gain has made the business case for new hires difficult to build |
| Operational data becomes a new client service | A service business already collecting operational data can position that data as the foundation for a client facing savings product | Spartan Logistics is building freight cost analysis for clients directly on top of its existing warehouse management system, a use case Harmon connects to five dollar diesel prices rather than a hypothetical AI application |
Quotes from This Episode
- “Whatever Steve, it can’t be that different.” — Steve Harmon, describing his leadership team’s initial reaction, President, NAI Harmon Group
- “You were right. This is better. What else can we be doing with it?” — Steve Harmon, quoting his leadership team’s reversal, CEO, Spartan Logistics
- “What comes in, where it came from, how long it sits, where it goes.” — Steve Harmon, describing Spartan Logistics’ warehouse management data, CEO, Spartan Logistics
- “I think I’m gonna go to the golf course.” — Steve Harmon, President, NAI Harmon Group
Frequently Asked Questions
How can a CEO get a resistant leadership team to actually use AI tools?
Steve Harmon, CEO of Spartan Logistics, banned his leadership team from using Google for one full quarter and required them to use an AI chatbot instead. The mandate removed the fallback option rather than simply encouraging voluntary use. Within 90 days, the same team that doubted the approach was asking what else they could automate.
What personal productivity gains can a CEO expect from using AI daily?
Harmon reports that consistent personal AI use has automated his email management and to-do list tracking, freeing time he previously spent on administrative work. He states this gain across his leadership team has made it difficult to build a business case for adding new staff, since the team is producing more without expanding headcount.
How can a logistics or service company use AI to create new value for clients?
Spartan Logistics is building freight cost savings recommendations for clients on top of its existing warehouse management data. Harmon connects this directly to current diesel prices near five dollars a gallon, positioning AI driven data analysis as a new service rather than an internal efficiency tool alone.
CEOs Work with Glenn Gow to Scale Their Companies and Careers
Glenn Gow is The Scaling Executive Coach. He coaches ambitious executives into the CEO seat and CEOs into successful exits. With 25 years as a CEO and 5 years in venture capital, Glenn helps leaders scale their companies by scaling themselves first. If this conversation was useful, you can apply for executive coaching with Glenn Gow or apply to be a guest on The Scaling Executive Podcast.
