Where AI is headed, and how the middle market can prepare

Middle market companies are betting heavily on artificial intelligence, and our data shows most of them are still in the early stages of what promises to be a much longer journey. Capital One’s recent Middle Market Strategic Investments Survey found that two-thirds of respondents are prioritizing AI, with 29% citing it as the investment most likely to deliver the biggest return over the next 12 months. But beneath the optimism, the survey also shows that most companies are still in the first phase of AI adoption, focused on productivity gains and workflow efficiency.

That’s a good start on AI transformation, but much of the journey still lies ahead. It’s a road Capital One is traveling, too. We’ve integrated  AI and machine learning into our operations for years, working through the same questions about implementation, talent, governance and scale that our clients are working through now. That shared experience shapes how we see what’s ahead.

For most middle market leaders, AI is currently doing what enterprise technology has long promised: making work faster and more efficient. The survey highlights where middle market companies are prioritizing AI applications for internal operations and communications (65%), productivity (63%) and insight generation (52%). AI is streamlining coordination, automating routine tasks and surfacing information faster than traditional processes allow.

About two-thirds of middle market companies are beyond the exploration stage. 51% report they are actively implementing or scaling AI, and 16% say they have completed integration¹. While 93% are actively investing, and 92% say leadership is supportive. Companies with revenue between $20 million and $2 billion are navigating inflation, economic uncertainty and rapid technological change. Amid these challenges, AI has become the most frequently planned technology investment because it can address two of their most pressing priorities at once: improving operational efficiency (53%) and increasing revenue or market share (48%).

Deploying AI at scale inside a large financial institution requires the same deliberate sequencing that middle market companies are now undertaking: identifying high-value use cases, building infrastructure, earning organizational trust and learning from early deployments before expanding. This is the foundation for growing with AI on which everything that follows is built. 

“What we’re seeing in the middle market reflects what we’ve experienced ourselves,” says Catherine Parker, head of digital banking for Capital One’s Commercial Bank. “The companies gaining the most traction aren’t the ones moving fastest, they’re the ones being most intentional. At Capital One, we've learned that AI delivers the greatest value when it's connected to modern infrastructure, centralized and standardized data and streamlined workflows that prepare its users for what's to come. That’s the same equation our clients are solving right now, and it’s one we’re well-positioned to help them navigate.”

The next evolution of AI adoption is using AI not only to respond to requests, but participate in how work gets done. Increasingly, business leaders are thinking about AI as “personal chief of staff”—someone who synthesizes information from across the organization, surfaces what matters most and helps move things forward without needing to be directed at every step.

In practice, this looks like AI systems that can manage workflows across functions, monitor for risks or opportunities in real time, refine communications and support decision-making at a pace and scale that amplify what human teams are able to accomplish together. This is a shift in how AI relates to an organization, transforming from a tool individuals use to a dependable capability that is part of a team’s workflow. 

Companies that have invested in well-managed data infrastructure, strong governance and modern tech stacks are beginning to see what is possible when those foundations are in place. The rest of the market is watching and building toward it. How quickly a company arrives at this end state will depend less on the technology—which is moving fast—and more on the organizational readiness.

Capital One places a priority on developing these capabilities, and our efforts help us think about our clients’ needs as they move into this phase. Beyond the technology itself, we understand the governance structures, change management and the trust an organization must build before it can confidently extend responsibility to an agentic system.

Further out lies the third phase in which AI is so deeply embedded in operations that it functions as a core driver of how the business runs, producing complex outputs and managing sophisticated processes with minimal handholding. The specific shape of that future will vary by industry, business model and competitive context.

What is less uncertain is the direction. The companies best positioned to reach this phase will be those that proactively adopted the technology before it matured. They will be the ones that treated the first phase of workflow optimization as preparation for something larger. 

To support their AI ambitions, middle market companies are looking beyond traditional bank financing. Half of the businesses surveyed have either successfully secured (26%) or are actively pursuing (24%) alternative or non-traditional financing. Private equity is the most commonly pursued type at 58%, followed by private credit at 50%.

The primary reason is to fund technology investments—cited by 68% of those using alternative financing. Among those who secured non-traditional financing, the largest share (18%) received between $50 million and $100 million in the past 12 months. These are not incremental budget decisions. For many companies, AI is central enough to the strategy that they are willing to tap new sources of capital and take on meaningful commitments to accelerate adoption. Understanding how to structure that capital efficiently—and how to align it with a technology roadmap that will continue to evolve—is one of the most consequential decisions middle market leaders will make in the years ahead.

Moving from workflow optimization to AI that functions as a genuine extension of the team requires more than capital. It requires people who know how to deploy AI responsibly and effectively—and an organization that is structured to support it. While 78% of leaders believe their workforce has the skills to maximize AI benefits¹, 58% also report a technical skills gap related to AI expertise, and 43% report a gap in cybersecurity skills.

Companies with these gaps are more likely to view external factors such as economic and cybersecurity threats, as major hurdles. Without sufficient internal capability, AI programs stall, fail to scale or fall short of ROI expectations. Building internal AI expertise at scale across the whole company is an ongoing effort; not a one-time investment. While the skills gap is not a barrier to starting, closing it is essential to advancing.

“The skills gap is the variable that will separate companies that scale AI successfully from those that plateau.” Parker says. “We’ve seen this in our own work—the technology moves faster than the organization unless you’re actively investing in people alongside it. For middle market companies, closing that gap isn’t just a talent strategy. It’s the thing that determines whether AI becomes a true operating advantage or stays a productivity tool.”

Rather than seeing AI as a technology upgrade, market leaders should view AI as a shift in operating models. The companies that will look back on this period as a turning point are not the ones that deployed the most tools or moved at the fastest pace. They are the ones that recognized what AI makes structurally possible and began reorganizing around it.

What that looks like in practice is still taking shape, but the focus is becoming clearer. Teams that once spent significant time gathering information, coordinating across functions and managing routine decisions will increasingly be freed to focus on judgment, relationships and the work that requires human thinking. AI will handle more of the connective tissue and, over time, more of the execution.  While AI provides data-driven insights, leadership’s judgment remains essential in navigating complexity, managing risk, and guiding the organization's strategic direction. 

The middle market companies building the right foundations today—investing in data infrastructure, closing skills gaps, establishing governance and aligning AI with clear strategic goals—are the ones that will be positioned to make this shift on their terms rather than in reaction to competitive pressure.

Capital One is on this path too. We are not observing this transformation from a distance and offering perspective. We are inside it—rethinking how our own teams operate, where AI can take on more, and what it means to deploy this technology with the discipline and accountability that the moment requires. That experience is central to how we serve middle market clients. 

The timeline for what comes next is uncertain, but the direction is not, and it is helpful to navigate these changes with a partner who understands the journey from the inside. 

For a full breakdown on where middle market companies are strategically investing their resources, check out our recent study.

 

 

Source:

¹ Capital One analysis of respondent data from the 2025 Middle Market Strategic Investments Survey Key Findings.