Most enterprise AI projects fail because ‘nobody defines’ what success looks like

According to USEReady CEO Uday Hegde, successful AI deployments depend less on model selection and more on architecture, accountability and execution discipline.

Enterprise AI failures are rarely caused by models alone. More often, they stem from organisations launching initiatives without clearly defining desired outcomes, governance frameworks, cost controls, or success criteria.

“Enterprises continue to approach AI through a technology-first lens, focusing on models and tools before establishing what success should actually look like,” USEReady’s co-founder and CEO, Uday Hegde, told CRN India.

According to him, that disconnect is emerging as one of the biggest reasons why AI initiatives struggle to “move beyond pilots and generate measurable business value”.

“What does good look like? If you don’t understand that upfront, the project will eventually fail,” Hegde said.

Read more at CRN Asia