- One-third of technology and service provider companies plan to pump $1 million or more into AI technologies over the next two years, a Gartner survey released Wednesday shows. The company surveyed 268 decision makers in high tech companies with revenues of $10 million or more.
- Nearly nine in 10 respondents expect funding for AI to increase at a moderate or fast pace through the next year.
- Despite provider enthusiasm, adoption challenges persist, and are partly driven by the immaturity of the technology. Forty-one percent of respondents said emerging AI applications were either still in development or in the early adoption stages.
Companies commit to AI for its operational advantages or cost-cutting potential. But maturity is still a work in progress as providers plan investments to solve for adoption gaps in the enterprise.
"We've got a long journey to go on to continue to develop use cases," said Errol Rasit, managing vice president at Gartner. Bringing early AI use cases to a more mature phase could lead hesitant customers to embrace AI adoption.
Following a brief pullback in emerging technologies last year, 39% companies are currently using or plan to use AI in the next two years, according to Spiceworks Ziff Davis' 2022 State of IT report. That number is up from 33% in the previous year.
Businesses that seek AI solutions are usually hoping to get "advanced insight that they would otherwise be unable to achieve," either because of human or systems limitations, said Rasit. For example, retail companies leveraging computer vision to understand buyer behavior or for security purposes.
"This is insight that otherwise would take you many, many people hours to replicate by looking through that data, or understanding which data to look at, in order to process in an analytics engine," Rasit said.
But the big puzzle the provider market is trying to solve is related to adoption. Just one in five enterprises are leaders in AI adoption according to a Cognizant report that measured the importance of AI and the number of areas where companies use the technology.
AI adoption is hardest for solutions that target a complex problem or a very specific use case, according to Rasit.
"There is still refinement and training that needs to occur in some of the AI models to be reliable, effective, to make confident business decisions or transactional decisions on," Rasit said.