Nearly a third of GenAI projects to be dropped after PoC

At least 30% of generative AI (GenAI) projects will be dropped after the proof-of-concept (PoC) stage by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs or unclear business value, according to Gartner.

Speaking at the Gartner Data and Analytics Summit in Sydney this week, Rita Sallam, distinguished vice-president analyst at Gartner, said that after last year’s hype, executives are impatient to see returns on GenAI investments, yet organisations are struggling to prove and realise the value of the technology.

“As the scope of initiatives widen, the financial burden of developing and deploying GenAI models is increasingly felt,” she noted, adding that organisations can find it hard to translate investments in GenAI into financial benefits.

According to Gartner, many organisations are leveraging GenAI to transform their business models and create new business opportunities. However, these deployment approaches come with significant costs. For example, fine-tuning GenAI models to support virtual assistant use cases could incur upfront costs of up to $6.5m, along with recurring costs of up to $11,000 per user per year.

“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,” she added.

Regardless of AI ambition, Gartner research indicates GenAI requires a higher tolerance for indirect, future financial investment versus immediate return on investment (ROI).

Historically, many chief financial officers have not been comfortable with investing today for indirect value in the future. This reluctance can skew investment allocation to tactical versus strategic outcomes, the research firm noted.

Still, Gartner said early adopters of GenAI are reporting business improvements that vary by use case, job type and skill level of workers. According to a survey of 822 business leaders it conducted late last year, respondents reported 15.8% revenue increase, 15.2% cost savings and 22.6% productivity improvement on average.

“This data serves as a valuable reference point for assessing the business value derived from GenAI business model innovation,” said Sallam. “But it’s important to acknowledge the challenges in estimating that value, as benefits are very company, use case, role and workforce specific. Often, the impact may not be immediately evident and may materialise over time. However, this delay doesn’t diminish the potential benefits.”

Gartner advised organisations that are making decisions about GenAI to analyse the business value and the total costs of implementing and supporting the technology so they can establish direct ROI and future impact.

“If the business outcomes meet or exceed expectations, it presents an opportunity to expand investments by scaling GenAI innovation and usage across a broader user base, or implementing it in additional business divisions,” said Sallam.

“However, if they fall short, it may be necessary to explore alternative innovation scenarios. These insights help organisations strategically allocate resources and determine the most effective path forward,” she added.