For leaders in the lower middle market (LMM) — companies generating roughly $10M–$100M in annual revenue — conversations about artificial intelligence often start with a healthy dose of skepticism: “Will this really move the needle for us financially?”

It’s a fair question. These firms run lean, with tight budgets and limited room for error. Unlike the Fortune 500, they don’t have the luxury of experimenting with $10M transformation projects. For AI to make sense in the LMM, it has to show a clear return on investment (ROI).

The good news? It does. In fact, evidence is mounting that AI delivers measurable improvements in revenue, margins, and enterprise value — often in a matter of months, not years.

Revenue Growth and Margin Expansion

A global survey of small and mid-sized businesses found that 91% of companies using AI report a lift in revenue, and 86% report improved profit margins. These aren’t theoretical gains — they come from practical improvements like faster quoting, smarter pricing, and higher sales conversion rates.

AI-enabled sales teams, for example, have achieved remarkable results: a Harvard Business Review study showed AI can increase leads by more than 50%, reduce call times by 60–70%, and cut costs by 40–60%. For a $25M services company, even modest improvements in sales productivity translate directly into hundreds of thousands of dollars in new revenue.

Payback Periods Measured in Months

One of the biggest myths about AI is that it requires massive upfront investment. The reality is that today’s tools are subscription-based, modular, and affordable.

Surveys show that many small and mid-sized businesses adopting AI are saving $500–$2,000 per month in operating costs and reclaiming 20+ hours of labor per employee per month. Those savings hit the P&L immediately.

When you factor in revenue lift and customer retention gains, the payback period on an AI pilot is often measured in months. In some cases, weeks.

Private Equity’s View: A Value Creation Lever

For private equity investors, AI adoption is more than an operational improvement — it’s a valuation driver. EBITDA improvements flow straight into enterprise value, and AI-driven efficiencies compound across a portfolio.

It’s telling that private equity and venture firms invested over $10 billion in AI by mid-2024, with Blackstone’s CEO Stephen Schwarzman stating: “The timeliness and effectiveness of AI implementation will determine who the winners and losers are.”

For PE-owned portfolio companies, incorporating AI into the value creation plan isn’t optional anymore — it’s expected.

Case in Point: Quoting Workflow Transformation

Consider a mid-market manufacturer where quoting new business was a two-day process. Employees had to dig through SKUs, check specs, and manually compile proposals. It was tedious, error-prone, and slow.

By introducing an AI-powered quoting assistant, the company cut turnaround time from two days to two hours. The impact? A higher win rate on new business, faster cash flow, and employees freed up for customer-facing work.

The cost of the tool? A few thousand dollars per year. The payback? Achieved in less than a month.

Real-World Example: Metal-Tech Industries & Paperless Parts

Metal-Tech Industries (MTI), a Brisbane-based sheet metal fabricator, faced exactly this challenge. Despite modernizing their shop floor with new equipment, their quoting process remained manual, inconsistent, and painfully slow. Estimators jumped between disconnected systems, producing different numbers for the same job.

After searching globally for a solution, MTI partnered with Paperless Parts, becoming the company’s first Australian customer. The impact was transformative:

• 30% increase in quote volume within just four months, even with a holiday shutdown.
  
  

• Dramatically reduced turnaround times — most RFQs answered in under 24 hours.
  
  

• 25% sales growth, driven by faster response times and the ability to compete on speed.
  
  

As MTI’s leadership put it, quoting went from bottleneck to competitive advantage. And importantly, the ROI was immediate — not measured in years, but in weeks and months.

Why LMM Firms Can’t Wait

Large competitors are already using AI to squeeze costs and offer faster service. In the LMM space, where margins are thinner and relationships are everything, standing still means falling behind.

But the opportunity isn’t just about keeping up. It’s about leapfrogging. By targeting high-ROI use cases and scaling thoughtfully, an LMM firm can actually move faster than a larger rival bogged down by bureaucracy.

A Pragmatic Path to ROI

So how do you unlock EBITDA impact without falling into “big-consulting” traps?

• Start with high-impact processes. Focus on quoting, reporting, forecasting, or customer service — areas where hours are wasted and errors are costly.
  
  

• Pilot, don’t overhaul. Run a contained project with clear KPIs and measure results within 30–60 days.
  
  

• Tie AI to the P&L. Translate every gain into dollars: hours saved, errors reduced, customers retained.
  
  

• Scale as you prove value. Expand to adjacent processes once ROI is established.
  
  

Where to Start

For lower middle market firms, the question isn’t whether AI pays off — it’s how soon you want to see those gains reflected in EBITDA.

Start with a focused project. Measure the results. Build momentum.

If you’d like to explore where AI can have the biggest financial impact in your business, we’d love to help. Reach out to schedule an AI Opportunity Assessment, and let’s map out how AI can boost your profitability in 90 days or less.

Because in this market, profitability isn’t just survival — it’s your competitive advantage.