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Lead Boldly Through AI Disruption
Transform uncertainty into a competitive advantage and be prepared to lead your team into the future. The business world has entered what Weidenhammer’s Chief Revenue Officer Jody Pillard calls an inflection period—a sustained stretch of transformation rather than a single turning point. Artificial intelligence is reshaping how organizations operate, compete, and think. For mid-market companies, that volatility can feel intimidating, but it’s also the opportunity of a generation.
“We’re used to technology shifts that hit once, then stabilize,” Pillard says. “AI isn’t like that. It’s a period of constant evolution. What was true six months ago—or six weeks ago—can be completely outdated today.”
That ongoing disruption has made adaptability the defining skill of modern leadership. To explore what that really looks like in practice, we sat down with Pillard, Anthony Cartolaro, Vice President of Cloud and Infrastructure Services, and Bill McGarry, Managing Director of Business Platforms and Integrations. Their collective view: Real progress with AI doesn’t come from chasing tools—it comes from aligning people, systems, and purpose.
Where AI Is Delivering Value (And Where It’s Not)
Across Weidenhammer’s client base, AI is already producing tangible wins: faster documentation, more responsive customer communications, improved sales intelligence, and a tighter security posture. Pillard sees the real work happening after the technology is in place, when teams try to fit it into how people work.
“Many companies know AI could help,” he explains, “but they’re still figuring out how to integrate it into existing workflows or open the door to entirely new ones. Systems change more slowly than technology.”
That lag shows up in missed opportunities: disconnected data, over-stretched teams, and uncertainty about where to begin. McGarry notes that this disconnect often traces back to strategy. “Leaders feel pressure to do something with AI before they fall behind,” he says.
“But when adoption happens without a clear purpose, you get fragmented tools that don’t scale or integrate. Efficiency gains evaporate.”
Cartolaro sees a similar pattern on the infrastructure side. “Tool sprawl and orphaned systems have always been a challenge,” he says. “In the AI era, those problems multiply. Every disconnected tool creates inconsistent data flows and governance gaps that make it harder to build a scalable AI foundation.”
What actually works, he says, is the unexciting part—discipline. “Start with consolidation, standardized data practices, and lifecycle planning. AI runs on trust and structure as much as it runs on compute power.”
The Case Against Waiting for the Dust to Settle
If uncertainty tempts leaders to delay, Pillard cautions that hesitation is the riskiest move of all.
“Waiting for the smoke to clear will leave businesses behind,” he says. “Your competitors—and bad actors—are already using AI. The risk of inaction is greater than the risk of learning as you go.”
That doesn’t mean charging ahead blindly. The trio emphasizes guardrails over prohibition: secure experimentation guided by transparency, training, and communication. “Banning AI doesn’t work,” Pillard adds. “Employees will use it anyway. The smarter path is to give them the right frameworks and tools so innovation happens safely.”
McGarry frames it as a leadership test. “Speed without alignment is chaos,” he says. “But alignment without momentum is paralysis. The sweet spot is giving teams permission to explore, with clear boundaries that protect the business.”
People, Not Just Platforms
Despite AI’s technical complexity, the most successful adopters are rarely the most technical teams. Pillard has observed that people with strong communication and management skills often outperform those with purely technical expertise.
“AI behaves more like a person than a machine,” he explains. “It needs context, clear direction, and feedback. If you’re good at managing people, you’re probably good at managing AI.”
That observation mirrors Weidenhammer’s long-standing “business-to-human” philosophy. “Technology should enhance human experience, not replace it,” McGarry notes. “AI’s real power is in freeing people to do higher-value work—creative problem-solving, relationship-building, strategy. Efficiency is just the starting point.”
For Cartolaro, success also depends on culture. “We talk about governance a lot, but governance doesn’t have to be a bottleneck,” he says. “When you bake guardrails into the process and empower cross-functional teams to test ideas safely, you build a culture where optimization becomes continuous.”
A Framework for Moving Forward
At Weidenhammer, that philosophy comes to life through the company’s Spark/Ignite/Shield model—a three-phase cycle designed to help clients adopt AI securely and sustainably.
“It’s the difference between handing someone a map and giving them the full climbing gear,” Pillard says. “Our clients need a guide, but they also need the equipment, the training, and the confidence to make the climb themselves.”
Leading Through the Inflection Period
The three leaders converge on one point: AI should be developed like a skill, continuously refined over time. Mid-market organizations, with their agility and customer proximity, are uniquely positioned to lead if they start now.
“AI won’t slow down for you,” McGarry says. “The only question is whether you’ll slow yourself down by waiting.”
Pillard agrees. “This moment favors the prepared,” he says. “With the right balance of readiness, experimentation, and human insight, mid-market leaders can turn uncertainty into advantage.”
Weidenhammer helps organizations pair strategic vision with practical execution, bringing the full set of climbing gear needed to scale AI safely and confidently.
