Blockers on the path toward greater automation use include fragmentation of tools and access to skills.
Published Aug. 10, 2022
Adoption of AI, long a bold promise for enterprise IT, will accelerate as a component of other products, services and solutions, Gartner’s Hype Cycle for Emerging Technologies 2022 projects.
As the technology evolves, advances in AI lead to faster development of models and thus faster arrival at the benefits, said Melissa Davis, VP analyst at Gartner.
“AI is moving beyond the hype and the cool, shiny object,” said Davis.
“AI is moving beyond the hype and the cool, shiny object,”
The report, released Wednesday, signals ample opportunity for executives to leverage emerging technologies.
Other, more experience-geared technologies — such as the metaverse, non-fungible tokens, super apps and Web3 — also stand out among tools generating corporate interest, even at a nascent stage of maturity.
But there are roadblocks to adoption:
- a lack of resources and
- the fragmentation of AI tools
require executives to create more cohesive adoption strategies.
The incentives are clear for businesses that can succeed at adoption.
AI-savvy companies earn up to 30% of their revenue through AI-based technologies and products, according to an Accenture survey published in June.
AI-savvy companies earn up to 30% of their revenue through AI-based technologies and products …
AI holds the promise to overhaul how companies operate, so long as companies don’t over promise and under deliver in AI pilot projects.
Now, there are clear examples of AI’s value delivery.
One technology mentioned in the Gartner report is machine learning code generation, which for Microsoft’s GitHub — maker of AI pair programming tool Copilot — has already leveraged hundreds of thousands of paid subscribers.
But the benefits aren’t guaranteed. Part of the problem is fragmentation, as AI gets embedded onto more products and services.
“It really comes down to having a clear vision and strategy and then pushing that on down to the various business units,” said Davis.
“Once that’s understood … then you can start looking at rationalizing the various tools.”
Another recurring issue for AI adopters is the lack of qualified skills to get the most out of tools.
Talent demand in emerging tech roles consistently make up around one-third of overall job postings in the past 18 months, according to CompTIA data.
As a potential fix for the talent woes, Davis proposes the use of mixed teams to tackle problems by combining skills.
“Fusion teams,” as Davis referred to them, bring in business, IT and other skills together around a specific problem.
As a potential fix for the talent woes, Davis proposes the use of mixed teams to tackle problems by combining skills. “Fusion teams,” as Davis referred to them, bring in business, IT and other skills together around a specific problem.
“Look within your own organization,” Davis said. “We’ve seen for many organizations that there’s a lot of talent there that can be leveraged.”
Originally published at: https://www.ciodive.com
Melissa Davis, VP analyst at Gartner.