Generative AI Projects Fail Amid High Costs and Risks
High costs, data issues, and unclear goals are key reasons, new reports show.
Despite the promise of artificial intelligence transforming industries, rising costs and mounting risks are causing many AI projects to falter, as highlighted by several recent reports.
At least 30% of generative AI projects will be abandoned after the proof-of-concept stage by the end of 2025, according to a new Gartner report. Companies are “struggling to prove and realise value” in their endeavours, which are costing from $5 million to $20 million in upfront investments.
A separate report from Deloitte provided a similar result. Of the 2,770 companies surveyed, 70% said they have only moved 30% or fewer of their GenAI experiments into the production stage. Lack of preparation and data-related issues attributed to this low success rate.
The overall outlook for AI projects is not rosy. Research from the think tank RAND found that despite private-sector investments in AI increasing 18-fold from 2013 to 2022, over 80% of AI projects fail — twice the rate of failure in corporate IT projects that don’t involve AI.
The disparity in financial backing and completion is a likely contributor to the “Magnificent Seven” tech companies — NVIDIA, Meta, Alphabet, Microsoft, Amazon, Tesla, and Apple — all losing a combined $1.3 trillion in shares over five days last month.
High initial investments in GenAI projects are required before benefits are realised
Using a GenAI API — an interface that allows developers to integrate GenAI models into their applications — might cost up to $200,000 upfront and an additional $550 per user per year, Gartner estimates. Additionally, building or fine tuning a custom model can cost between $5 million and $20 million, plus $8,000 to $21,000 per user per year.
The average AI investment of global IT leaders was $879,000 in the last year, according to a report by automation software provider ABBYY. Almost all (96%) of respondents to that survey said they would increase these investments in the next year, despite a third claiming they have concerns about these high costs.
Gartner analysts wrote that GenAI “requires a higher tolerance for indirect, future financial investment criteria versus immediate return on investment,” which “many CFOs have not been comfortable with”.
But it’s not just the CFOs that have concerns about the ROI of AI endeavours. Investors in the world’s biggest tech companies have recently expressed doubt as to when, or if, their backing will pay off. Jim Covello, a Goldman Sachs stock analyst, wrote in a June report: “Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful.”
