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After the initial buzz surrounding generative artificial intelligence (AI) from 2023, a new report claims that firms in the manufacturing segment are dragging their feet regarding full-scale integration.

The report, put together by AI firm Lucidworks, highlighted a trend of manufacturing firms’ waning interest in generative AI in recent months. The study gleaned its data from a pool of over 2,500 executives at the intersection of AI and manufacturing to reach its findings, noting that AI spending in the ecosystem is down by double-digit percentages since the start of the year.

Per the report, 36% of surveyed respondents are keen on keeping AI spending flat as they scan the horizons for favorable metrics before increasing investments. Compared to 2023, only 6% of executives expressed hesitancy toward increasing the size of their AI bets, highlighting a massive decline in interest.

The waning interest in the segment is not far-fetched. The respondents expressed their worries over the perceived risks associated with generative AI models. 44% of respondents say concerns around the response accuracy of AI models are a major factor in their decision to stall the integration of the technology.

Since launch, AI models have grappled with the existential problem of hallucination, skewing the accuracy of responses and diminishing user trust levels. While several researchers have made significant strides in solving AI’s hallucination problems, analysts say the issue may be here for the long term.

According to Lucidworks’ study, implementation cost for AI systems is another reason for manufacturers’ slow pace of adoption. Apart from the steep cost of an infrastructure overhaul, companies in the vertical will have to fork out a fortune to train employees on the latest AI models.

Outside of costs, 3% of manufacturing firms are uncertain about turning to AI over fears of job displacement of their employees. Entry-level customer service and design roles face the most risk of replacement by generative AI systems, with upskilling failing to cater to the challenge.

“While many manufacturers see the potential benefits of generative AI, challenges such as response accuracy and cost are causing them to take a more cautious approach,” said Lucidwoks CEO Mike Sinoway. “This is reflected in spending plans, with significantly fewer planning to increase AI investments compared to last year.”

Finding a balance

Despite the fears expressed by manufacturing companies, Lucidworks’ study highlighted the upsides of finding a healthy balance with AI, pointing to the general “above-average cost benefits” in the long term.

Firms in the vertical can improve their design optimization with generative AI at a pace beyond human capabilities while advancing predictive maintenance abilities for companies. Other perks include seamless integration with other emerging technologies, quality control, improved customization, and energy efficiency.

“B2B companies and manufacturers have much to gain if they can balance cost and risk to improve efficiency, enhance the buyer experience, and reduce operational costs using generative AI,” said Sinoway.

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.

Watch: Calvin Ayre is all in on Metanet—the game-changing fusion of enterprise blockchain, AI & IPv6

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