Businesses Face Hurdles Getting GenAI Past Pilot Phase: Gartner
Generative AI may be the buzz phrase of 2024, but how many AI initiatives actually make it past the pilot phase and result in long-term strategy? At least 30% of GenAI projects are expected to be abandoned after proof of concept by the end of 2025, according to Gartner.
The company attributes the high failure rate to poor data quality, inadequate risk controls, rising costs, or unclear business value.
Distinguished VP analyst Rita Sallam shared findings from the recent report at the Gartner Data & Analytics Summit in Sydney. Though the findings were not specific to CPG, the consumer goods industry has experienced many of these challenges.
Risk vs Reward
While productivity rates often increase, stakeholders may have difficulty tying the metric to financial goalposts — for them, it may not be enough to justify the high cost of GenAI implementation, which typically ranges from $4 million to $20 million, per Gartner.
“After last year's hype, executives are impatient to see returns on GenAI investments, yet organizations are struggling to prove and realize value,” said Sallam. “As the scope of initiatives widen, the financial burden of developing and deploying GenAI models is increasingly felt.”
The challenge is that it’s not a one-size-fits-all approach, particularly as costs can be unpredictable and results vary depending on how much is spent, what the use case is, and what the deployment approach is.
In the consumer goods industry, these factors can vary wildly from company to company. There are marketing approaches that give way to elevated consumer experiences, such as Diageo's packaging initiative, where tourists take home GenAI-created artwork on a Johnnie Walker bottle. Others, meanwhile, might target more tangible results in the workforce, such as Procter & Gamble’s internal generative AI tool, which is being used for upskilling.
Also: Learn how BIC is expediting innovation with generative AI.
“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,” said Sallam.
How to Prove Value
The key is establishing direct ROI and future value impact, per Gartner. It’s a complicated dance between analyzing business value and the cost of GenAI business model innovation.
“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 organizations strategically allocate resources and determine the most effective path forward.”
Without an appropriate waiting period, investments can appear to fall short. The impact isn’t always immediately evident, said Sallam.
Gartner data from 2023 paints an optimistic picture. Over 800 business leaders reported an average 15.8% increase in revenue and 5.2% in cost savings, and 22.6% productivity growth, as a result of early generative AI adoption across industries and business processes.
