Deep Dive:

  • According to a survey released last week by AI platform Publicis Sapienta survey, enterprises' AI adoption efforts are outpacing their readiness, resulting in a failure to fully reap AI's full rewards. The survey covered 1,550 enterprise technology decision-makers.
  • More than seven in ten (71%) U.S. respondents expect AI to expand significantly in the next year or two, but only 20% say their organizations are equipped to meet these expectations.
  • Nearly a quarter (24%) of respondents believe that the organization's operating approach is a major obstacle to AI success. Although AI is already used in most teams within enterprises, the report found that most organizations have not yet thoroughly reformed systems, workflows, and operating models to gain full benefits from the technology.

Deep Insight:

Enterprise spending on AI is expected tosurge significantlyin the coming year, although large enterprises face relatively fewer challenges in AI adoption, they still struggle to find measurable positive impact and business value from the tools they use.

In the survey, three-quarters (75%) of enterprises said they use AI in most business processes, but only 10% said the technology is core to their business operations. Slightly more than a third (about 34%) of enterprises said AI is fundamentally changing the way they operate their business.

Traditionally, enterprises operate more slowly than the high-speed iteration of most AI providers. Shubhradeep Guha, Global Chief Delivery Officer at Publicis Sapient, said in an email to CIO Dive that large enterprises need to establish appropriate governance mechanisms, clarify functional boundaries, and break down data silos to prepare for AI applications.

"The obstacles are rarely about the models themselves," Guha said, "but rather about legacy systems not built for AI, fragmented data, siloed teams, and governance structures that slow down decision-making."

Guha also noted that many enterprises will need to reorganize personnel and skill configurations to unlock AI value. A recentstudy by Randstad Digitalfound that some companies invest more in AI platforms than in training employees to implement the technology.

Enterprises can benefit by deploying human-machine collaborative teams, adjusting job roles, modernizing data foundations, and implementing different incentive mechanisms to promote employee and team collaboration.

The report points out that AI spending needs to be combined with system modernization, human-centric organizational adjustments, and operational-level adoption.

"AI can accelerate individual tasks, but if the surrounding systems remain slow and fragmented, enterprises will not see enterprise-scale impact," Guha said.