Why Mid-Market Companies Struggle to Move AI Pilots Forward

Mid-market companies can often move faster than large enterprises when adopting new technology, but many have yet to turn artificial intelligence pilots into full deployments. Research cited in a TechRadar Pro Perspectives article found that 90% of mid-market companies that have explored AI remain at an early stage or have experienced stalled pilots.

TechRadar contributor Alper Gunaydin identifies three obstacles: gaps in expertise, weak data and technology foundations, and insufficient governance safeguards. Teams may understand AI in theory but lack practical skills in areas such as integration or change management. Companies may also face legacy enterprise software, poor data quality, and outdated data models.

The article says data readiness—including accuracy, ownership, and accessibility—should be built into projects from the outset. It also argues that governance, ethics, security, and privacy controls need to be in place for AI to scale beyond pilots. Some companies, it notes, have frameworks but have not put formal policies or controls into practice.

Gunaydin writes that foundational work can happen alongside deployments if it is planned and integrated early. The article presents these challenges as solvable and says targeted investment in skills, systems, data, and controls could help mid-market companies move AI projects toward measurable, sustainable value. The views are the author's and are not necessarily those of TechRadar Pro or Future plc.