As we close out 2025, it's time for mid-market leaders to take an honest look at where AI stands in their organizations and what it means for the year ahead.

The hype cycle has been relentless. Every vendor promises transformation. Every conference declares this the year of AI. And yet, most mid-market companies I speak with share a common experience: they've invested in AI initiatives, seen some wins, but haven't achieved the revolutionary change the headlines promised.

That's not failure. That's reality.

The Gap Between Promise and Practice

Here's what I've observed across dozens of mid-market organizations this year:

  • Pilot purgatory is real. Many companies have successful AI pilots that never make it to production. The technical proof-of-concept worked, but the governance, change management, and operational readiness weren't there.
  • Shadow AI is everywhere. While official AI initiatives moved slowly through approval processes, employees adopted ChatGPT and other tools on their own. This created real productivity gains—and real governance gaps.
  • The skills gap widened. Companies that thought they could hire their way to AI capability found the talent market brutal. Those that invested in upskilling existing teams made more progress.

What Actually Worked

The mid-market companies that made real progress in 2025 shared some common characteristics:

They started with governance, not technology. Instead of asking "what AI can we buy?", they asked "what decisions do we need to make about AI?" This governance-first approach meant that when they did deploy AI, they could move faster because the guardrails were already in place.

They focused on augmentation over automation. The successful implementations I saw treated AI as a tool to make employees more effective, not a replacement for them. This approach reduced resistance and produced better outcomes.

They were honest about their data. AI is only as good as the data it runs on. Companies that invested in data quality and governance before AI deployment saw dramatically better results than those that tried to skip that step.

What This Means for 2026

For mid-market leaders planning their 2026 AI strategy, here's my advice:

Accept that AI governance is a competitive advantage. The companies that can deploy AI quickly and safely will win. That speed comes from having governance frameworks in place, not from cutting corners.

Budget for the boring stuff. Data cleanup, process documentation, change management, training—these aren't exciting line items, but they're what separates successful AI initiatives from expensive experiments.

Bring in regulatory awareness now. AI regulation is coming. The EU AI Act is already here. US regulations are forming. Companies that build compliance into their AI programs now will have a significant advantage over those scrambling to retrofit later.

The Bottom Line

2025 wasn't the year of AI transformation for most mid-market companies. But it was the year many laid the groundwork for real transformation. The pilots, the lessons learned, the governance debates, the data quality investments—all of it matters.

The question for 2026 isn't whether to adopt AI. That ship has sailed. The question is whether you'll do it in a way that's sustainable, compliant, and actually delivers value.

That's what governance is for. Not to slow you down, but to ensure that when you move, you move in the right direction.

The companies that win with AI won't be the ones that moved fastest. They'll be the ones that moved smartly—with governance frameworks that enabled speed without sacrificing safety.