Manufacturers delay Gen AI rollout due to increasing accuracy concerns: Study
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Manufacturing Sector Adopts Generative AI at a Slower Pace Amid Accuracy Concerns
Manufacturers are advancing their Generative AI initiatives more slowly than anticipated primarily due to concerns about accuracy, according to a recent study by Lucidworks. The study, which surveyed over 2,500 global leaders involved in AI technology decision-making, found that 58% of manufacturing leaders are planning to increase their AI spending in 2024. This figure is lower compared to the global consensus of 63% and significantly below the U.S. consensus of 69%. Last year, an overwhelming 93% of both general leaders and manufacturing leaders were set to increase AI investments.
Growing Investment in AI
Recent data from PitchBook revealed a surge in U.S. venture capital funding, largely influenced by substantial investments in AI companies. Investors are channeling funds into startups with high hopes that AI adoption will lead to considerable revenue gains. Lucidworks' study also noted that nearly 50% of manufacturers globally have reported increased cost savings this year after integrating AI into their operations.
"While the potential benefits of generative AI are recognized by many manufacturers, issues such as response accuracy and costs are prompting a more cautious implementation," commented Mike Sinoway, CEO of Lucidworks.
Challenges with Generative AI
Generative AI works by processing inputs or prompts to create new content based on historical data used for training. However, it sometimes produces erroneous or nonsensical results known as hallucinations. While 36% of all respondents are worried about these hallucinations affecting accuracy, this concern is more prevalent among manufacturing leaders, with 44% expressing anxiety over the issue.
Despite the fact that only 20% of planned AI projects were executed by manufacturers over the past year, 55% feel their AI adoption status is comparable to that of their peers.
Cost Considerations
In the last year, 70% of manufacturing companies opted for pricier commercial AI models. Lucidworks suggests that manufacturers may shift towards more affordable and efficient open-source models if these alternatives can deliver the required performance at lesser costs. While manufacturers are optimistic about the potential cost benefits of AI, they aim to maximize its value despite the reduced projected spending this year.
