A third of all generative AI projects will be abandoned, says Gartner

Companies are “struggling” to find value in the generative artificial intelligence (Gen AI) projects they have undertaken and one-third of initiatives will end up getting abandoned, according to a recent report by analyst Gartner.

“After last year’s hype, executives are impatient to see returns on Gen AI investments, yet organizations are struggling to prove and realize value. As the scope of initiatives widen, the financial burden of developing and deploying Gen AI models is increasingly felt,” stated Gartner’s distinguished analyst Rita Sallam in a press release summarizing the research findings.

Also: There are many reasons why companies struggle to exploit Gen AI, says Deloitte survey

The report states at least 30% of Gen AI projects will be abandoned after the proof-of-concept stage by the end of 2025.

<!–>

Sallam cites the costs of projects as a big pressure on deployment, with upfront investments ranging from $5 million to $20 million. 

For example, at the low end of the scale, using a Gen AI API, which allows a user to consume the publicly-hosted Gen AI model, for things such as coding assistance, means a company might spend around $100,000 to $200,000 upfront, and up to an additional $550 per user per year, Gartner estimates. 

Also: Enterprises double their Gen AI deployment efforts, Bloomberg survey says

At the top end of the scale, spending to finetune “foundation” AI models or build custom models from scratch can cost $5 million to $20 million upfront, plus $8,000 to $21,000 per user per year.

While Gartner’s research identifies significant challenges, it’s not all bad news for Gen AI. Some companies report they’ve already seen benefits from the technology, such as revenue increases, cost savings, and productivity lifts. 

However, those upsides come with another warning: Gartner says the payoff can be hard to measure.

Also: Generative AI’s biggest challenge is showing the ROI – here’s why

“Gen AI requires a higher tolerance for indirect, future financial investment criteria versus immediate return on investment,” said Sallam. 

“Historically, many CFOs have not been comfortable with investing today for indirect value in the future. This reluctance can skew investment allocation to tactical versus strategic outcomes.”

Aside from costs, Gartner said factors that could doom AI projects include “inadequate risk controls” and “poor data”.

Also: 5 ways CIOs can manage the business demand for generative AI

The concerns about abandonment in the research contrast with other surveys that suggest Gen AI deployments are progressing.

For example, a recent Bloomberg Intelligence survey indicated the percentage of companies “working on” deploying Gen AI “co-pilot” programs doubled between December last year and July 2024.