A Recipe for AI in the Mid-Market

By Richard B. Price who started the MBA-JD program at the University of Pennsylvania and was its first graduate in 1973. He is a former McKinsey consultant, served as president of what is now Aqua, is an AM&AA member and the founder of the middle market capital transaction platforms of PQ Suite and AdvisorPQ. He has spent 40 years working in middle-market M&A.

Big companies are devoting millions – even billions – of dollars to experiment with alternative AI applications to achieve competitive advantages over their behemoth competitors. But what can your average Mid-size company do? They have neither the time nor money to “experiment” with Artificial Intelligence (AI). As a result, smaller companies have focused on the low hanging fruit of AI. The most common uses of AI are to speed customer support, sharpen promotional pieces for clients, and improve internal processes – write better memos and position papers.

How Can a Mid-Market Company Unleash AI’s Transformative Potential?

AI has often been hailed as the next revolution in business, promising unmatched eDiciency and innovation. Yet, despite its potential, skepticism persists. Many company managers question whether the promised benefits justify the investment, with concerns about excessive costs and uncertain returns. At the same time, companies are entangled in a web of complex technologies, relying on numerous software systems and Application Protocol Interfaces (APIs) — ranging from customer relationship management (CRM) tools to accounting packages, payroll services, and supply chain logistics platforms. Each system has its own AI solutions, contributing to an already intricate technological landscape. On the bright side, “middle market companies view AI as a pivotal catalyst for growth, capable of enhancing operational eDiciency, lowering costs, improving product and service oDerings and fostering further innovation.” [Special Report by the National Center for the Middle Market and Aon, page13.] However, to navigate the complexity of AI use alternatives and fully realize AI’s potential, Mid-size businesses must overcome significant challenges. Here is a roadmap for AI integration, helping organizations harness the technology’s full capabilities. This approach cuts through the noise, providing a clear path toward integrating AI into business operations in meaningful, cost-eDective ways.

Understanding Today’s AI Challenges

Let’s start with comparing the current state of AI to welcoming a brilliant college graduate into your company. While this individual has exceptional knowledge and the ability to learn quickly, they arrive without any understanding of the specific processes, systems, or culture unique to your organization. In the same way, Large Language Models (LLMs), despite their impressive capabilities, initially lack the contextual understanding needed to function eDectively within a company’s operations. This analogy highlights a key challenge: while AI has vast general knowledge, it requires training to understand the unique nuances of a company’s workflows, data, and objectives. Simply installing an AI system does not guarantee immediate value; it must be tailored and integrated thoughtfully to deliver meaningful results. As a result, many businesses only scratch the surface of what AI can do, using it for basic tasks such as drafting emails or generating reports without tapping into its full potential.

Stages of AI Integration in Business

Here are the stages that businesses can follow to integrate AI into their operations. This roadmap moves from basic AI adoption to a more sophisticated, fully integrated system that fundamentally reshapes how a company functions.

Stage 1: Basic Assistance

At this initial stage, AI serves as a general-purpose assistant. It can answer customer inquiries, draft emails, summarize documents, and provide basic information. However, its contributions are limited because it operates without access to the company’s internal knowledge or systems. While useful for alleviating administrative burdens, its overall impact is superficial due to its lack of context.

Stage 2: Retrieval Augmented Generation (RAG)

In this next phase, the AI gains access to the company’s document repositories—policies, communications, and procedures. With this influx of unstructured data, the AI becomes better equipped to generate outputs that align with the company’s specific needs. This stage represents a significant leap in capability, as the AI begins to understand the company’s voice and history. However, it still lacks access to structured data, such as databases or spreadsheets, which limits its potential for deeper insights.

Stage 3: Hybrid Search and Structured Data Access

To unlock even greater value, AI systems must be able to navigate structured data, such as customer information or sales figures, alongside unstructured data. By integrating hybrid search capabilities, AI can access databases and spreadsheets, providing a much more comprehensive understanding of the business. This advancement enables AI to handle complex queries and conduct analyses that would otherwise require significant human eDort.

Stage 4: “Talk to Your Company” – Enhanced AI Assistance

At this stage, the AI becomes fully integrated into the company’s operational fabric. It can interact with both structured and unstructured data while executing functions through API integrations. The AI now serves as a proactive contributor, able to provide cross-functional support and strategic insights. For example, it can analyze customer feedback, track sales trends, or recommend operational changes, significantly improving decision-making processes.

Stage 5: Orchestrating AI to Act

The final stage of AI integration involves giving the AI autonomy to perform actions based on predefined parameters. Let’s refer to this as “Orchestrate Your Company,” where the AI not only analyzes data but also takes action to improve business outcomes. Using a regional restaurant chain as an example, AI can track reservations, optimize food inventories, identify lulls in bookings, adjusts waitstaD, and suggest oDering a free drink or discounts to encourage customer visits. Once the top management approves the idea, the AI autonomously manages inventory, schedules waitstaD, generates the freebies or discounts, emails customers, and updates the reservation calendar. This level of integration transforms AI from a passive tool into an active participant in running the business, handling marketing, customer engagement, and operational tasks without requiring manual intervention. The implications for more complex enterprises are even more profound, with AI managing everything from supply chains to customer service, drastically improving operating eDiciency and agility.

The Near Future: Breaking Down Silos and Building an AI Business Operating System

The future of AI in business is more than just integration. As discussed earlier, today’s companies rely on multiple, isolated systems, creating data silos that fragment information and impede eDiciency. These are your CRM tools, accounting systems, payroll, even legal constraints for regulated businesses. AI tools now exist for breaking down these silos, flattening the business landscape so that all data flows freely across the organization. In this model, AI acts as a conductor, orchestrating every aspect of the business by analyzing data and executing tasks across previously siloed management functions, APIs and other automated systems. The result is an AI Business Operating System, where AI not only optimizes operations but drives innovation, reshaping how Mid-sized companies function and compete.

The Human Element in AI-Driven Organizations

Despite the transformative power of AI, there remains the irreplaceable role of human workers. AI excels in processing and analyzing information, but it lacks the creativity, intuition, and emotional intelligence that only humans can provide. AI should complement human eDort by taking over routine tasks, allowing management to focus on creative and strategic endeavors. By working together, humans and AI can drive unprecedented innovation and eDiciency. Employees are empowered to make informed decisions with the help of AI, while focusing their energies on high-level tasks that AI cannot perform, such as building relationships and developing new ideas.

Seizing the Opportunity

Mid-sized businesses should embrace AI now rather than waiting for future advancements. Early adopters will gain a significant competitive advantage by improving eDiciency, gaining insights, and responding to market changes faster than their rivals. High growth companies have been the most active in integrating AI across all business functions. Those who delay risk falling behind in a rapidly evolving landscape. With the tools and technologies available today, companies can revolutionize their operations and unlock new levels of innovation and productivity. By following a clear roadmap for AI integration, organizations can position themselves for success in an AI-driven future.

AM&AA members SAVE $2000 on PQ for Advisors. For discount code and access, contact Richard Price directly at rprice@pq-suite.com.