After extensive research and business calculations, Gartner has predicted that at least 30% of GenAI projects will be abandoned after proof of concept by the end of 2025. The business experts estimate this will be the result due to poor data quality, inadequate risk controls, escalating costs or unclear business value.
“After last year’s hype, executives are impatient to see returns on GenAI investments,” says Rita Sallam, distinguished VP analyst at Gartner. “Yet organisations are struggling to prove and realise value. As the scope of initiatives widen, the financial burden of developing and deploying GenAI models is increasingly felt.”
A major challenge for organisations arises in justifying the substantial investment in GenAI for productivity enhancement, which can be difficult to directly translate into financial benefit. The upfront deployment costs of GenAI projects can range from $5 million to $20 million.
Regardless of AI ambition, Gartner research indicates GenAI requires a higher tolerance for indirect, future financial investment criteria versus immediate return on investment (ROI).
This prediction has been reached after realising that GenAI projects are costing more than they are worth for businesses. A 2023 Gartner survey saw only a 15.8% revenue increase, 15.2% cost savings and 22.6% productivity improvement on average.
“Unfortunately, there is no one size fits all with GenAI, and costs aren’t as predictable as other technologies,” said Sallam.
“What you spend, the use cases you invest in and the deployment approaches you take, all determine the costs. Whether you’re a market disruptor and want to infuse AI everywhere, or you have a more conservative focus on productivity gains or extending existing processes, each has different levels of cost, risk, variability and strategic impact.”
Over the last few years, particularly since the popularity of large language model (LLM) ChatGPT, we have seen GenAI dominate business conversatons and strategies. Many organisations sought to enter the AI race and stay ahead of the curve, as well as appealing to consumer demands.
However, this new prediction suggests that businesses may have rushed to join the AI trend, and can not establish a direct ROI and future value impact.