DBT Bureau
Bengaluru, 30 July 2024
Despite all the hype, global consultancy firm Gartner said around 30% of all generative AI projects will not survive beyond proof of concepts (PoCs) by 2025. According to the report, poor data quality, inadequate risk controls, escalating costs or unclear business value are seen as probable causes for such trend.
“After last year’s hype, executives are impatient to see returns on GenAI investments, yet organisations are struggling to prove and realise value. As the scope of initiatives widens, the financial burden of developing and deploying GenAI models is increasingly felt,” said Rita Sallam, distinguished VP analyst, Gartner.
A major challenge for organisations is to justify the substantial investment in GenAI for productivity enhancement, which can be difficult to directly translate into financial benefit, the report stated.
The report said that despite many organisations leveraging GenAI to transform their business models and create new business opportunities, these deployment approaches come with significant costs, ranging from $5 million to $20 million.
“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 criteria versus immediate return on investment (ROI).
“Historically, many chief financial officers (CFOs) have not been comfortable with investing today for indirect value in the future. This reluctance can skew investment allocation to tactical versus strategic outcomes,” said the report.
The research also said that early adopters of GenAI across industries and business processes are reporting a range of business improvements that vary by use case, job type and skill level of the worker.
