A few years into enterprises’ AI deployment efforts, many tech chiefs are still searching for the value, cost savings or productivity boosts they sought out through AI investments that continue to grow by the year. 

Although satisfaction with AI ROI slowly rose this year, according to an SAP and Oxford Economics report, C-suite executives said they’re not convinced that the technology they’re deploying is delivering its full potential. 

Folding in a new technology throughout the enterprise comes with its own technical challenges, CIOs have said, but it’s often non-technical factors that are keeping enterprises from finding success. AI infrastructure limitations, inflated IT budgets, poor data foundations and an uneven risk-to-value relationship are holding many back.

There’s also the human element: AI deployment calls for enterprisewide change management for employees, systems and processes, Ismail Amla, SVP of Kyndryl Consult, said during a briefing with reporters earlier this week. The classic categories of people, process and technology have become much more complex as human change gets overlayed atop each component, Amla said.

CIO Dive has compiled a series of stories on the roadblocks many enterprises are facing — and how some tech leaders are navigating them to success.