A new report highlights how mid-market CEOs see a lot of potential in artificial intelligence. They believe AI can bring real value to their businesses. But despite this optimism, many are still stuck in pilot projects or isolated experiments. The challenge now is turning AI enthusiasm into actual, scalable results.

High Belief, Limited Strategy

The survey shows that nearly all mid-market CEOs agree AI is important. About 98.5 percent say it has value for their business. However, only a small fraction have a company-wide AI plan. Most are running quick pilot programs focused on efficiency, not on integrating AI across the entire organization.

Many companies are exploring AI but haven’t yet made it a core part of their strategy. Over half of the CEOs are still testing AI in small pilots. Only 7 percent have a comprehensive plan with multiple initiatives. This gap shows a strong belief in AI’s potential but a lag in execution.

The Main Barriers and Opportunities

The biggest hurdles are a lack of AI expertise, difficulty connecting AI tools with existing systems, and poor data quality. About 86 percent of CEOs say they lack the necessary skills, and 81 percent struggle with system integration. Data issues also slow down progress, with 65 percent citing data accessibility as a challenge.

Despite these obstacles, many companies are actively working on AI projects. Six out of ten CEOs report having ongoing AI initiatives, even without a formal strategy. This indicates a desire to experiment and learn, even if scaling remains a challenge.

Real-World Example: Mugsy’s AI Journey

Mugsy, a fast-growing men’s apparel brand, is a good example of how mid-market companies are approaching AI. The company faced inventory problems and lots of fragmented data across different systems. They added numerous website plugins, each providing different performance data, which made decision-making difficult.

CEO Leo Tropeano explains that simple questions like “What was our return on ad spend yesterday?” could yield four different answers. Rather than buying another forecasting tool, Mugsy decided to focus on better inventory management. Their goal was to use AI to improve data accuracy and make smarter business decisions.

Early tests include an AI-driven inventory planning model that’s reaching about 90 percent accuracy. Mugsy’s approach shows how mid-market companies can move from enthusiasm to tangible results by addressing data issues and focusing on specific outcomes.

This case study highlights the broader challenge for mid-market CEOs: turning AI ideas into scalable, impactful solutions. It’s not just about experimenting anymore; it’s about operationalizing AI to deliver measurable business value.

Inspired by

• https://ai-techpark.com/virtuousai-mid-market-ceos-see-ai-value-but-stay-in-pilot-mode/