Enterprises continue to hit generative AI roadblocks

Dive Brief:

• Almost three years into the enterprise generative AI craze, enterprises report adoption roadblocks that are difficult to sidestep, according to a September ABBYY report. Opinium Research conducted the survey of 1,200 senior managers and other top leaders from the U.S., UK, Germany, France, Australia and Singapore.
• About 1 in 3 businesses say training generative AI models is harder than expected, and slightly fewer respondents said staff members don’t have the necessary skills to deploy the technology. Companies are also having a hard time integrating generative AI into business processes and creating proper governance structures. 
• Even after implementing generative AI, success isn’t guaranteed. More than 1 in 5 survey takers say employees are misusing the tools, and the same percentage of respondents say employees bring generative AI tools outside IT’s purview for personal productivity, raising security concerns.   

Dive Insight:

While the conversation has shifted to other AI technologies, such as agents, enterprises continue to struggle to overcome integration, training and governance challenges tied to generative AI.

“Businesses spent money on Gen AI tools that promised more than they can provide,” Maxime Vermeir, senior director of AI at ABBYY, said in a blog post. “In some cases, they didn’t even need it.”

One of the tasks CIOs have taken up is sifting through vendor hype and determining where generative AI fits into enterprise workflows. Businesses are motivated by the potential for productivity benefits, according to the ABBYY survey, but they’re also spending more conservatively. More than 2 in 5 survey takers plan to increase their spending by up to only 15% in the next 12 months, the report found.

“A lot of enterprises are more mindful and are taking a harder look at AI investments,” said Eden Zoller, chief analyst of applied AI at Omdia. “You’ve really got to get quite strategic and quite disciplined with the approach.”

Enterprises have had success with generative AI by honing project prioritization processes and addressing other kinks head-on. 

Marriott Global CIO Naveen Manga characterized the hotel giant’s approach to generative AI as building on its foundation of “ruthless” prioritization. Kraft Heinz has put an emphasis on pressure testing use cases before going all-in to prevent dead-end generative AI projects. PepsiCo has also improved processes to better enable generative AI projects to move into production by culling priorities.