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. 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. 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.
Full study : The high upfront cost of deployment and the low ROI is one of the challenges that can doom generative AI projects.
