Your AI strategy is only as strong as the people who run it

A survey of senior leaders at large U.S. and U.K. professional services firms found 61% abandoned at least one AI project in the past year due to a lack of skills among their people. A Deloitte report based on more than 3,200 business and IT leaders across 24 countries identified insufficient worker skills as the single biggest barrier to integrating AI into business. There is no quick fix: hiring or contractors can provide short-term capability but is expensive and creates dependencies, while building skills in-house cannot be done overnight. Organizations can begin systematically building AI capabilities now. AI capabilities come from four mutually reinforcing layers, including technical depth, domain application, and additional layers that align AI strategy with business reality and execution.

"61% said they had abandoned at least one AI project in the past year because their people lacked the skills to deliver it. Deloitte's "2026 State of AI in the Enterprise" report, based on a survey of more than 3,200 business and IT leaders across 24 countries, found that insufficient worker skills are now the single "biggest barrier to integrating AI into the business.""

"There is no quick or easy solution to this problem. While it is possible to bring in new hires or contractors with the short-term capabilities you need, this approach is not sustainable in the long term as it is both expensive and creates critical dependencies. And it is equally impossible to flip a switch to develop these capabilities in-house overnight. But businesses can start the vital process of building those skills systematically."

"Organizations that get ahead of the pack in this critical area will build an advantage over their peers that will compound every quarter. The Capability Stack Organizational AI capabilities emerge from four mutually reinforcing layers of expertise. Technical depth. This is the specialized engineering capability that builds and maintains AI systems: machine learning engineering, data engineering, AI security, model evaluation, and related disciplines."

"Without sufficient technical depth, the wrong things get built and bought, and the organization creates risk that it doesn't understand. Domain application. This layer is where AI strategy meets business reality. It consists of the capability to apply AI within a specific business function. And it relies on people who understand not just what the technology can do, but where it"

Read at Fast Company