- Manufacturers are cautious about implementing generative AI due to accuracy concerns, with only 58% planning to increase AI spending in 2024, lower than global and U.S. averages.
- Despite reduced AI spending, manufacturers see AI’s value, with 70% using costly commercial models but considering a shift to open-source solutions.
OUR TAKE
The tech industry must balance innovation with reliability to ensure AI enhances rather than disrupts manufacturing operations. Overcoming challenges like response accuracy and cost is essential for AI to revolutionise manufacturing effectively. The stakes are high, and success will favour those who master this delicate balance.
–Jasmine Zhang, BTW reporter
What happened
Manufacturers are implementing generative AI initiatives more slowly than expected due to concerns about accuracy, according to a Lucidworks study. Surveying over 2,500 global AI decision-makers, it found 58% of manufacturing leaders plan to increase AI spending in 2024, less than the global and U.S. averages of 63% and 69%, respectively.
Generative AI, which creates new content from prompts based on training data, can produce inaccurate outputs known as hallucinations, with 44% of manufacturing respondents expressing concerns over this issue. Despite only 20% of planned AI projects being executed last year, 55% of manufacturers feel on par with their peers in AI adoption.
Moreover, 70% opted for costly commercial AI models, though a shift to open-source models is anticipated if they prove efficient and cost-effective. Manufacturers aim to maximise AI’s value amid reduced spending.
Also read: 5 of Fatih Porikli’s most important thoughts on Gen AI
Also read: China surges ahead in generative AI adoption
Why it’s important
The slow roll-out of generative AI in manufacturing underscores a critical tension in the tech industry: the race to innovate versus the need for precision. Despite the hype, manufacturers are cautious, and rightly. So, Lucidworks’ study reveals that 44% of manufacturers are wary of AI’s infamous “hallucinations,” which produce inaccurate results. Yet, the potential is undeniable, nearly half reported cost savings from AI adoption this year.
PitchBook data from last week highlighted a surge in U.S. venture capital funding driven by AI, signaling strong investor confidence. However, as Mike Sinoway, CEO of Lucidworks, aptly noted, challenges like response accuracy and cost are causing hesitation.
The broader industry needs to take note. If AI’s promise of revolutionising manufacturing is to be realised, overcoming these hurdles is essential. Manufacturers must balance innovation with reliability, ensuring AI enhances rather than disrupts their operations. The stakes are high, and the winners will be those who master this delicate dance.
