In the lower middle market (LMM) — companies generating $10M–$100M in annual revenue — leaders often face a paradox with artificial intelligence. On one hand, the potential is obvious: more efficiency, faster decisions, higher margins. On the other hand, the path forward feels murky.

Too many companies get stuck in what experts call “pilot purgatory”: small experiments that never scale, or flashy tools that don’t tie back to the business. For AI to be more than a side project, you need a clear roadmap.

Here’s a five-step framework designed for LMM companies to move from pilot to platform — from one-off wins to a systematic capability that drives growth and profitability.

Step 1: Identify High-Impact Opportunities

AI can theoretically touch every part of your business. But in practice, success comes from focus.

Start by asking: Where are we losing the most time or margin today? Is it quoting? Reporting? Customer service? Forecasting?

This is the essence of an AI Opportunity Assessment — mapping your processes, bottlenecks, and data flows to pinpoint the 2–3 use cases with the clearest ROI. In LMM firms, these usually fall into repetitive, measurable tasks where automation frees people for higher-value work.

Step 2: Start with Quick-Win Pilots

Don’t try to boil the ocean. Instead, launch a pilot that can demonstrate value within 30–60 days.

For example:

• Automating board reports to save 40 hours a month
  
  

• Using AI for quoting to cut turnaround time from two days to two hours
  
  

• Deploying a chatbot to handle 50% of service inquiries
  
  

The key is to set measurable KPIs upfront — hours saved, errors reduced, customers retained. Quick wins prove the concept, build credibility, and generate momentum.

Step 3: Build Cross-Functional Governance

AI is not an IT project. It touches operations, finance, compliance, and people.

Create a small working group with representatives from each area to oversee pilots and expansions. Their job is to:

• Ensure alignment with business goals
  
  

• Manage data quality and privacy
  
  

• Set guidelines for responsible AI use (e.g., human review of outputs)
  
  

• Track ROI consistently
  
  

In an LMM company, this might be as simple as a monthly working session with the CEO, CFO, ops lead, and IT manager. The point is to break silos and keep AI tied to strategy.

Step 4: Invest in Training and Change Management

Even the best tool fails if people don’t use it. Employees need confidence, not fear.

That means training is non-negotiable. Run workshops that show employees how AI will make their work easier, not obsolete. Empower a few “AI champions” across departments to coach their peers. Celebrate success stories: “This tool saved our finance team 20 hours last month — here’s what they did with the extra time.”

Surveys show nearly half of employees want more AI training, and nine out of ten who use AI say it makes them more productive. Training isn’t a cost; it’s an investment in adoption and morale.

Step 5: Scale and Integrate into Strategy

Once you’ve proven ROI in a few areas, it’s time to expand.

This is where LMM companies can outpace larger rivals. You can scale quickly across functions without bureaucracy slowing you down. Build a 12–24 month roadmap that aligns AI with your strategic goals: more revenue, better margins, stronger customer experience.

At this stage, track ROI like any other investment. Show how AI is contributing to EBITDA. Communicate results internally and, for PE-backed companies, to investors. Over time, AI should become part of the DNA of your business — as routine as financial reporting or sales reviews.

Why This Matters

AI adoption in the lower middle market is no longer a “nice to have.” A global survey found 72% of companies now use AI in at least one function, up from ~50% a year prior. Meanwhile, 91% of SMBs using AI report revenue growth and 86% report improved margins.

The firms that act now will capture these gains. Those that wait risk watching competitors pull away.

Call to Action

If you’re ready to move beyond experimentation and build a scalable AI strategy, the first step is simple: run an AI Opportunity Assessment.

We’ll help you identify the use cases that matter, launch quick-win pilots, and chart a roadmap to turn AI into a platform capability for your business.

Because in the lower middle market, the winners won’t be the firms that tried AI. They’ll be the ones that made it core to their growth strategy.