The middle market leads the way in (smart) AI investment

For AI to deliver on its promise, it has to work—and pay off—for companies that can't afford to fail slowly. That's the middle market, roughly defined as companies with revenue between $10 million and $1 billion that make up the majority of employment and GDP. These aren't startups with venture runway or enterprises with dedicated AI labs. They need technology that provides impact quickly. 

That’s what makes the middle market AI’s best proving ground.

Doug Farren is managing director of the National Center for the Middle Market, a research organization tracking this segment. The Works caught up with Farren about what the latest NCMM data reveals: AI investment is accelerating in the middle market, but so are the governance, integration, and ROI challenges that come with it. The following is the lightly edited conversation. 

When middle market leaders say they’re “investing in AI,” what does that actually look like in practice?

Doug Farren: Our research shows that middle market companies are primarily focused on investments that are operational and efficiency-driven, with AI being deployed to streamline existing processes rather than to pursue speculative or frontier use cases. 

AI is the leading destination for investment dollars, rebounding strongly in Q4 2025 and outpacing other uses of additional capital. Based on our data, this investment is concentrated on automation of routine tasks, advanced data analytics and predictive modeling, natural language processing and conversational AI, and machine learning applications.

Read also: The AI ROI roadmap

Revenue growth has rebounded while employment growth remains muted. Are we seeing AI‑driven productivity? Cautious hiring? Something else?

The data shows that revenue growth rebounded in Q4 2025 following a mid‑year dip, while employment growth remained lower than in 2024, with hiring activity staying relatively flat. Taken together, the evidence supports a pattern of cautious hiring combined with increased reliance on technology investment. While AI‑driven productivity gains are plausible, our organization does not directly measure productivity.

Are all middle-market companies growing equally—and what role is AI playing? 

The data clearly show that larger middle-market firms, with annual revenue between $100 million and $1 billion, are outperforming smaller middle-market firms on both revenue growth and employment growth. These larger firms also report higher levels of technology and AI investment and a stronger emphasis on digital transformation. However, NCMM cannot directly connect AI adoption by firm size to the observed growth differentials based on our Middle Market Indicator. 

Is AI simplifying work, or introducing a new layer of complexity and governance challenges that mid-market firms may not be fully prepared for?

The year‑end data indicates that AI is doing both. AI and technology investments are focused on improving efficiency through automation and digitization. However, adopting and integrating new technology is identified as a rising operational challenge, and cybersecurity, data privacy, and cloud security concerns are escalating. Firms also cite concerns related to data quality, system integration, uncertain ROI, and regulatory and compliance complexity. This shows that while AI is intended to simplify work, it is simultaneously introducing new layers of operational, governance, and risk‑management complexity.

What are you hearing from middle market companies about balancing enthusiasm for AI with discipline to ensure rollouts are planned and measurable? 

The playbook for middle market companies to this point has been varied, from looking at the repetitive, unappealing tasks that people don't like to do to considering industry or company-specific use cases for the technology. As we've seen with other new platforms, middle market businesses won't be early innovators or adopters, but tend to lag in realizing full-blown implementation benefits until they are more confident the investment will provide the ROI. Until then, expect smaller pilots and tests to prove feasibility.

What will success look like for AI adoption in the next 12-24 months for the middle market? 

Where the middle market stands to benefit is addressing their inherent resource constraints as fast-growing organizations trying to manage "big-company" problems with limited resources. AI will help them address costs, productivity, and constraints related to worker attraction and retention. It will likely level the playing field for businesses that may have been constrained by the sheer number of people to manage and scale growth.