Surfing the AI tsunami: Lessons from mid-market leaders

Artificial intelligence has gone from buzzword to boardroom agenda in record time. Mid-market companies are intrigued, but many remain stuck in “pilot mode.”

Panelists at Wipfli’s recent “AI in the real world” webinar agreed: The promise of AI is clear, but the transition from experiments to enterprise requires deliberate strategy.

Michael Simon Bodner, CIO of AWC Technology, offered a striking metaphor: “AI is like a tsunami. Right now, the water is pulling away from the shore. Many people don’t realize what’s coming next — but the wave is building.”

His point was simple: You can’t outrun a tsunami. You need to be ready to surf it.

That theme carried through the discussion, where mid-market leaders from logistics, construction and financial services shared how they’re preparing their organizations.

The webinar also included Jacob Ollman (Moltin AI at Schneider) and Todd Adams (Alloya Corporate Federal Credit Union). Here are the key lessons they offered:

Lesson 1: Start with data, not hype

Every panelist underscored the same reality: AI is only as strong as your data.

• Clean up your infrastructure. Bodner stressed that “you can’t lie to AI and expect it to tell you the truth.” Legacy silos, duplicate records and poor governance must be addressed first.
• Think of data as currency. In industries like construction, logistics and finance, information isn’t just a support function — it’s the lifeblood of operations.
• Invest in readiness. Adams described pausing before rolling out Microsoft Copilot firmwide: “We ran a readiness assessment and discovered we weren’t fully prepared. So, we invested in upgrading our data environment first, then gave early licenses to a small pilot group to explore use cases.”

For mid-market firms, that readiness step may feel like extra work. But it’s a safeguard against false starts — and it builds credibility with skeptical employees.

Lesson 2: Culture is the real barrier

Technology is often easier than people. Resistance to change, fear of replacement and lack of understanding are the true obstacles to AI adoption.

• Educate with patience. Ollman, a leader of an AI-native initiative with Schneider, said his team built a two-week curriculum to train middle managers and senior leaders on AI basics. He called early champions “pollinators” who spread enthusiasm across the organization.
• Position AI as a coworker. “The promise of AI is to give every employee a Jarvis,” Ollman said. By framing AI as a partner that supports, rather than replaces, human work, organizations reduce anxiety and increase buy-in.
• Set the tone from the top. Adams noted that his board created an “innovation fund,” so resources were already earmarked for AI experiments. That visible commitment empowered employees to test innovative ideas without fear of failure.

Culture change takes time. But without it, even the best technology will sit unused.

Lesson 3: Look for low-hanging fruit

The most successful AI initiatives started with repetitive, time-consuming work — the kind of tasks that are dull, dirty, or dangerous.

• Meeting notes and transcription. AI-generated summaries saved hours of follow-up work for the project team, Adams said.
• Contract compliance. AI agents at Ollman’s startup automatically scan new regulations, review contracts for compliance and assign tasks to staff — transforming what was once a labor-intensive process.
• Legacy system integration. Automating QuickBooks entries at a manufacturing subsidiary reduced a two-hour process to a minute, Bodner said.

These small wins build momentum. They free employees from tedious work and create tangible ROI, even before large-scale transformation.

Lesson 4: Protect your IP and set guardrails

Security and governance aren’t optional. As Jacob put it, “Agents should be treated like employees” — governed by the same roles, permissions and access rights.

• Avoid public tools for sensitive data. All three panelists warned against using ChatGPT or other open platforms for company information. Instead, they recommended secure enterprise solutions, such as Microsoft Copilot.
• Use guardrails. Companies are experimenting with “small language models” (SLMs) trained on internal processes, with strict boundaries on what data they can access.
• Rethink cybersecurity. AI can crawl across every document in your environment. Firms must adapt policies and controls accordingly.

Without trust in AI’s guardrails, adoption will stall — especially in regulated industries like finance and healthcare.

Lesson 5: Redesign processes, don’t just automate

Perhaps the most important takeaway: AI isn’t about dropping automation into existing workflows. It’s about rethinking those workflows altogether.

“Adding AI to your current process rarely works,” Ollman said. “You have to step back and consider how AI capabilities enable entirely new approaches.”

That mindset shift is where mid-market firms can gain real competitive advantage. Instead of incremental efficiency, they can leapfrog into new business models, faster customer service, and more resilient operations.

Advice for leaders just starting out

The panelists left attendees with practical guidance:

• Assess yourself honestly. Where are your data gaps? What skills do you lack?
• Invest in people. Create new roles like “information engineers” who specialize in making AI usable.
• Frame AI as an enabler. Employees should see it as a tool that removes drudgery, not a threat to their jobs.
• Budget intentionally. Set aside funds for experimentation, pilots, and early wins.
• Act now. As Bodner warned, “AI will never be dumber than it is today.” Waiting only increases the gap between leaders and laggards.

The bottom line: Don’t stand on the beach

The wave is coming. Mid-market leaders don’t need to fear it — but they do need to prepare.

Whether it’s a pilot in your call center, a compliance agent in your procurement team or Copilot in your CRM, the time to start is now.

Because when the AI tsunami arrives, the safest place won’t be on the shore. It will be on the surfboard.

Want to go deeper?

Watch our “AI in the real world” webinar on-demand or explore Wipfli’s resource hub for mid-market leaders navigating uncertainty for webinars, tools and practical guides on AI adoption.

You can also check out these additional AI resources:

Automation vs. augmentation — making the right AI move

Why AI strategy is the most exciting part

What misaligned data is really costing you

How Wipfli can help

Scaling AI isn’t just about technology — it’s about strategy, governance and change management. Wipfli helps mid-market leaders move beyond pilots with practical AI roadmaps, readiness assessments and implementation support. Explore how we can help your organization turn AI into a competitive advantage on our AI services page.