Manufacturers in the United States and globally are looking to tap artificial intelligence (AI) systems and generative AI to improve business operations, boost automation and drive efficiency gains.
A recent Lucidworks survey of more 6,000 employees involved in AI technology decision-making found 42% of manufacturing participants have a positive sentiment toward AI and 92% of U.S. manufacturing respondents surveyed plan to increase AI investment in the next year.Â
In the survey, Lucidworks devised a comprehensive set of criteria to measure generative AI adoption, reviewing the level of AI investment, leadership commitment, the number of generative AI initiatives already launched and the number of planned generative AI initiatives.
It then categorized companies into four stages based on their launched initiatives, finding only a quarter of respondents stood out as pioneers in generative AI. Â
Although more than 90% of respondents plan to invest, industries across the board have a very long way to go before they reap the full benefits of generative AI, explains Mike Sinoway, CEO of Lucidworks.
“It can be overwhelming to even know where to begin, not to mention the legitimate concerns around security and accuracy,” he says.
He adds most surprising among all these findings was the fact that over 40% of the companies have launched AI efforts without any initiatives focused on AI governance.
“This seems to be a fairly risky approach,” he notes.
From Sinoway’s perspective, business operations improvement will be the area of most interest to manufacturing firms, as it translates into cost savings.
“While revenue growth is attractive, manufacturers will likely see the quickest gains by using AI to automate administrative processes,” he says. “Also, by employing generative AI in G&A functions, companies can free up valuable human resources to focus on more strategic tasks while benefiting from streamlined operations and cost savings.”
Despite the willingness from most survey respondents to invest in AI, 12% of those surveyed said they have a negative reaction toward AI.
“The negative reaction toward AI stems from the fear of making costly mistakes,” Sinoway says. “Companies are caught in a dilemma between the fear of falling behind in innovation and the fear of security breaches or misinformation.”
He adds this balance between adopting cutting-edge technology and ensuring security and accuracy is a significant hurdle to overcome.
“The possibility of anything from a security breach to providing incorrect or offensive responses to customers undermines leaders’ trust in generative AI,” he says. “We also saw in the survey that companies are concerned about the transparency in understanding how AI-based decisions are made, potential job displacement, and ensuring responsiveness in terms of timeliness and tone.”
Sam Zheng, CEO, DeepHow agrees AI has vast potential across various sectors of manufacturing.
“But in my view, its most revolutionary aspect in manufacturing will be in knowledge transfer and process optimization,” he says. “In traditional setups, it takes significant time for expert knowledge to be transferred to newcomers or across different teams.”
He explains AI can capture, categorize and make this expert knowledge accessible in real-time.
“This not only fast-tracks learning curves but also preserves the invaluable tacit knowledge that often goes undocumented,” Zheng says.
Beyond knowledge transfer, AI can also play a transformative role in predictive maintenance, quality control, demand forecasting and supply chain optimization.
“With real-time data analysis, AI can predict and identify bottlenecks or inefficiencies in the manufacturing process, enabling companies to optimize their workflows and reduce costs,” he says.
He advocates a stepwise approach for manufacturing firms looking to invest in AI, starting with a small-scale pilot program.
“This allows companies to assess the potential of AI applications without a full-scale commitment,” he says. “This provides firsthand experience and a clearer understanding of the potential ROI.”
Zheng also recommends engaging in workshops or seminars that are tailored to educate industries about the potential applications and benefits of AI.
“It’s an excellent opportunity for knowledge exchange and networking,” he says. “Collaborating with startups or AI-focused companies can also provide insights and hands-on demonstrations.”
Sinoway says manufacturing firms should maintain a healthy amount of caution, but completely failing to adopt generative AI would be a devastating mistake.
“Generative AI is not as effective or secure at scale on its own,” he says. “It requires boundaries to ground responses in truth and create an added layer of security for internal data and documents.”
He notes manufacturers up to this point have mostly been focused on using AI for governance initiatives and cost reduction.
“Over the next two years, I think those two initiatives will be table stakes,” he explains. “We’ll be watching manufacturing and B2B companies successfully implement AI to address revenue growth, customer experience improvement and additional automation.”
