AI project failure rates are on the rise: report

Dive Brief

The share of businesses scrapping most of their AI initiatives increased to 42% this year, up from 17% last year, according to S&P Global Market Intelligence.

Published March 19, 2025

First published on

Dive Brief:

• More enterprises reported AI project failures this year compared to 2024, according to analysis from S&P Global Market Intelligence. The findings are based on a survey of more than 1,000 respondents in North America and Europe.
• The share of companies abandoning most of their AI initiatives jumped to 42%, up from 17% last year. The average organization scrapped 46% of AI proof-of-concepts before they reached production. 
• Companies cited cost, data privacy and security risks as the top obstacles, S&P found. So far, AI adoption is predominantly found in IT operations, followed by customer experience workflows and marketing processes. 

Dive Insight:

Enterprises are grappling with a long list of persistent roadblocks and speed bumps related to their AI initiatives. 

CIOs thought their organization’s progress with generative AI wasn’t up to par in 2023, and experiments continued to fail last year. This year will likely bring more scrapped projects.

Nearly all enterprises are increasing generative AI investments, even as two-thirds admit to being unable to transition pilots into production, according to an Informatica report published last month.

Successful organizations have made efforts to prioritize and customize use cases. After all, decision-makers who chase every AI opportunity are likely to have more projects fail. Knowing when AI is the right tool — and when it isn’t — is critical to avoid wasting time on a losing hand.

Failed projects, however, shouldn’t always send a negative signal to business leaders, according to analysts. 

“Celebrating failures on some of this matters,” Amanda Luther, managing director and partner at Boston Consulting Group, said during a CIO Dive virtual event Wednesday. Allowing employees to surface and pilot use cases they are interested in promotes a culture of experimentation, whether or not the idea makes it to production, she added. 

The exercise can also lead to iterative experimentation and better results down the line. 

“When people hear the word failure, they freak out about it,” Htike Htike Kyaw Soe, managing director, advisory digital at KPMG U.S., said during the panel. “There’s a lot of trial and error to this because it’s a new technology… Embracing that is okay.”