Watch the full webinar replay at volarisgroup.com/from-uncertainty-to-opportunity.
Looking beyond the news headlines that swing between hype and fear, what does it realistically look like to lead a software business through an AI transition?
On June 16, 2026, Volaris Group brought together two General Managers who have been managing the day-to-day work of easing people’s resistance to change, making hard calls without certainty, and getting a team to move in a direction for which no one has a clear map.
In a conversation moderated by Volaris Group’s Chief of Staff Ryan Hill, attendees heard candid lessons learned and shared by the GM of AssetWorks Fleet, Greg Richards, and GM of eQuip, Crystal Germond. Below, we recap key takeaways.
The biggest threat isn’t the technology, but your competitors
The webinar opened with clear framing from both GMs. The biggest risk AI poses to vertical market software businesses isn’t coming from an LLM or a chatbot. It’s going to come from the competitor in your market who adopts faster than you do.
As AssetWorks Fleet’s GM Greg Richards stated plainly, “I’d rather disrupt my own market than let somebody else disrupt my market.” Crystal Germond, GM of eQuip, agreed: “I would rather be a first mover. If we don’t do anything and there’s inertia and inaction, we’re probably falling behind.”
Both leaders pushed back on the idea that AI will completely destroy the future of their businesses. They see vertical market software companies — businesses that develop and customize software for a specific industry, niche, or market — as having something that general AI market disruptors don’t. That advantage is years of customer data, a deep understanding of specific business processes, and hard-won trust built over decades.
For vertical market software companies, the opportunity is to deploy AI against those advantages, far before waiting to see if it erodes their business.
Richards illustrated this with a story. During a competitive RFP process, a customer asked what AssetWorks would do if someone called their support line speaking Swahili. Thinking on his feet, he pulled out his phone and messaged his support lead, asking him to query their AI-integrated case management system for an answer — in Swahili.
Two minutes later, he had a response to show the purchasing agent. “That’s not a capability we would have ever had before as a small company,” he said. “It really is a game changer.”
Overcoming resistance to change starts at the top
Crystal Germond encountered strong pushback when she initially advocated for AI-led changes at eQuip. It came from every direction. She concluded that any leader who is surprised by resistance to change isn’t paying close enough attention.
“If we sit with our own discomfort, our own fear about what AI could mean for us and our businesses, it’s not that far of a leap to think our teams are feeling the same thing,” she said.
Her approach has been to model the behavior she was asking of others — sharing hunches before she had proof, naming uncertainty openly, and making space for emotional reactions without letting them become reasons for inaction. “There is a comfort with being uncomfortable and a comfort with ambiguity that this AI transformation is forcing all of us to go through.”
Germond was careful to distinguish between productive skepticism and fear that could mask legitimate objections. The biggest gauge for her is whether the conversation changes over time.
“If the feeling in the room hasn’t moved after we’ve talked it through, that’s the indicator that we’re dealing with something else — which might be emotion.” Valid as it is to feel fear or anxiety, they aren’t valid reasons in a business context if they allow an organization to stay stuck in its ways.
Permission to experiment won’t move the needle on its own
Richards shared a lesson from an early misstep. Two years ago, he bought everyone at the company licenses for Microsoft Copilot and subscriptions to ChatGPT. He told them, “Go forth and be productive.” A year later, he estimates that only about 10% of the organization was using the tools at all — and mostly dabbling, with no measurable ROI that he could identify.
Looking back at what he learned, he said in his own words: “I really messed it up the first time.”
As an experienced GM, he knew it was time to pivot. Richards pulled three people out of their regular jobs and gave them a difficult problem to solve: a legacy module notorious for its dated UI. Then he set what many people thought was an impossible deadline — get it done before the user conference in three months. He assigned this to people who had no prior history with the product.
Having fresh eyes on the problem made a difference. Without the baggage of knowing why decisions were made in certain ways 10 years ago, the team rebuilt the module in about 60 days and surprised themselves by finishing early.
The lesson: simply experimenting isn’t a strategy. Real progress came when he created focused mandates, installed internal champions, and set up AI initiatives to report directly to him.
Your best AI champion might not be in R&D
One surprising insight from the session was who ended up driving AI innovation inside AssetWorks. It wasn’t a senior engineer or a data scientist, but a customer service manager.
The manager had joined AssetWorks three years earlier in a customer-facing case management role — not a technology role by any traditional definition. But he brought something engineers often lack: daily exposure to real customer pain points. And having never written software himself, he was unencumbered by what couldn’t be done.
Surrounded by colleagues with product and engineering knowledge, the support manager used that fresh perspective to drive key product features forward and is now building an entirely new product for AssetWorks customers.
“It’s not necessarily the technology leaders in your organization, and it’s not even your best programmers in a lot of cases,” Richards said. “It’s the people who have that curious nature.”
AI is changing work, and leaders have to manage the transition
Both GMs acknowledged that making the shift from doing work to managing AI agents presents a genuine identity challenge for many individual contributors, especially those who’ve built careers around mastering a craft.
Richards described an employee who came to him directly and said: “If my job becomes managing agents, I don’t want to do it anymore.” That person left voluntarily, and the situation was handled with empathy, but AssetWorks Fleet also put in place metrics to track the transition, including measuring what percentage of code was generated by AI versus written manually every month.
Germond shared her expectation that people at her company should be open to letting AI change how they work. She also emphasized the role that leaders play in the AI transition. “We cannot delegate this… As GMs, we have to be personally inside the work, not just reviewing it. The leaders who are seeing real results figured that out early.”
Outside perspective accelerates internal efforts
Looking outside your own business can fuel change, according to Germond, who took inspiration from others inside the larger Volaris network and the startup community in Austin, Texas.
She described collaborating with the Volaris Business Transformation team, who joined eQuip’s replatforming effort early on. They saw her vision immediately and pushed her further. “They said, ‘You’re not thinking big enough. There’s even more potential than you’re realizing right now,'” she recalls.
That external credibility and clarity gave Germond the conviction to make a bold call: the whole company was moving to a new platform, across the board, starting immediately. “I was able to do that not just because of that team, but the conviction that it had to be done came from the insight and support they brought me.”
Richards found similar value in Volaris Group’s AI Accelerator program, where his team took part in intensive, week-long sessions where individual contributors from any function are challenged to solve a real customer problem. In his case, the team came back from an AI Accelerator session, went straight to the AssetWorks user conference, and demonstrated the product they’d built. Customers lined up on the spot to buy a product built in 60 days using AI.
Competitive moats must be defended
Both GMs spoke about competitive moats in the current environment and how they need to be protected.
Germond shared a cautionary story about a segment of eQuip’s market where they thought they had a comfortable position. A small firm, which consisted of only a few people who had figured out AI early, delivered solutions faster than they could, taking that segment away from eQuip.
“At the end of the day, our customers are buying our solutions to fulfill a goal or a need,” she reiterated. “If we can’t deliver on that promise, how can we say the relationship will endure no matter what?”
Richards shared his simple test. When a customer has a new need, do they call you first? That instinct to reach for the phone only exists where trust has been genuinely earned and consistently maintained.
Both also emphasized that feedback is the signal to watch. Customers who are talking, even if only to complain, are customers the business can still work with. “It’s the silence I fear,” she said.
Advice for leaders in the hardest stretch
When asked what founders who are currently struggling should do right away, Germond said they should find help.
“One of the loneliest things is to see something no one else sees and not have the help to get there. I think that takes community, and it takes collaboration.”
She pointed to the Volaris network as her secret weapon and an asset that’s easy to underestimate. With a peer group of leaders on speed dial, who have developed enough trust between each other to speak candidly, she has found a lot of value in speaking with other leaders.
In the current environment within Volaris, she said, “It’s okay to ask for help, and this is a time when we all should be doing that.”
Watch the full webinar replay at volarisgroup.com/from-uncertainty-to-opportunity.
