Gartner: 30% of Gen AI Projects to be Abandoned by 2025

Projects including generative AI (Gen AI) are expected to be abandoned after the proof-of-concept phase by the end of 2025.

According to Gartner, this high abandonment rate comes in the wake of organisations rushing to adopt the technology amid its global hype. At least 30% of all Gen AI projects are expected to be abandoned due to poor data quality, inadequate risk controls, escalating costs or unclear business value, according to Gartner.

The consultant suggests that businesses have a challenging road ahead, as both their investment strategies and deployment practices could be impacted moving forward.

Currently Gen AI deployment costs range from US$5m to US$20m.  

Rita Sallam, Distinguished VP Analyst at Gartner said, “After last year's hype, executives are impatient to see returns on Gen AI investments, yet organisations are struggling to prove and realise value.

“As the scope of initiatives widens, the financial burden of developing and deploying Gen AI models is increasingly felt.”  

Justifying Gen AI

This research from Gartner comes at a time when Gen AI adoption is currently ranking as one of the top priorities of businesses across sectors. Earlier in the same month, it also forecasted a US$5.26tn global IT spend in 2024, with Gen AI expected to drive 24% growth across data centres.

Likewise, a Capgemini study also released in the same month was optimistic about what it described as “explosive” Gen AI adoption, suggesting that increasing investment is driving forward will play an essential role in augmenting the software workforce.

Yet like with digital transformations, implementation across an organisation may be hard to achieve. A major challenge that is arising for organisations is justifying the substantial investment into Gen AI to enhance productivity, which Gartner suggests can be difficult to directly translate into financial benefit for a business.

Currently, many organisations around the world are leveraging Gen AI to uplift their business models and create new opportunities for innovation. However, these deployment approaches come with significant costs, as the below figure highlights.

“Unfortunately, there is no one size fits all with Gen AI, and costs aren’t as predictable as other technologies,” Sallam notes. “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.”  

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

Achieving real business value

Early adopters of Gen AI across multiple industries and business processes are reporting a range of business improvements. These extend across use case, job type and worker skill level. 

Gartner says that, by analysing business value and the total costs of Gen AI business model innovation, organisations can establish the direct ROI and future value impact. This ultimately serves as a crucial tool for making informed investment decisions about Gen AI business model innovation.   

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

Plenty of large organisations are using Gen AI to drive success. For instance, Nvidia harnessed the technology’s power to briefly overtake Microsoft as the world’s most valuable company, hitting a US$3tn market cap.

The company’s success has been attributed to heavy demand for its AI processors, as it continues to power ahead alongside Gen AI to transform its business development.

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