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New research from Google Cloud and The Harris Poll reveals that the pandemic led to a significant increase in AI use across manufacturers. According to a survey of senior executives at over 1,000 companies, two-thirds of manufacturers that use AI in their day-to-day operations report that their reliance on AI is increasing, with 74% claiming that they align with the changing work landscape.
According to a 2020 PricewaterhouseCoopers survey, companies in manufacturing expect efficiency gains over the next five years attributable to digital transformations. McKinsey’s research with the World Economic Forum puts the value creation potential of manufacturers implementing “Industry 4.0” — the automation of traditional industrial practices — at $3.7 trillion in 2025.
Seventy-six percent of respondents to the Google Cloud report say that they’ve turned to “disruptive technologies” like AI, data analytics, and the cloud to help navigate the pandemic. Manufacturers told surveyors that they’ve tapped AI to optimize their supply chains including in the management (36%), risk management (36%), and inventory management (34%) domains. Even among firms that currently don’t use AI in their day-to-day operations, about a third believe it would make employees more efficient (37%) and be helpful for employees overall (31%), according to Google Cloud.
Manufacturing is undergoing a resurgence as business owners look to modernize their factories and speed up operations. According to ABI Research, more than 4 million commercial robots will be installed in over 50,000 warehouses around the world by 2025, up from under 4,000 warehouses as of 2018. Oxford Economics anticipates 12.5 million manufacturing jobs will be automated in China, while McKinsey projects machines will take upwards of 30% of these jobs in the U.S.
Ford is among the manufacturers using AI within its operations via a relationship with Google. Announced in February, the automaker plans to leverage Google’s expertise in data, AI, and machine learning as a part of Team Upshift, a six-year partnership and collaborative group launching in 2023. Ford says the initiative will accelerate modernization of product development, manufacturing, and supply chain management, including exploration of using vision AI for manufacturing employee training and even more reliable plant equipment performance.
“[This] will supercharge our efforts to democratize AI across our business, from the plant floor to vehicles to dealerships,” Bryan Goodman, director of AI and cloud at Ford, said in a statement. “We used to count the number of AI and machine learning projects at Ford. Now it’s so commonplace that it’s like asking how many people are using math. This includes an AI ecosystem that is fueled by data, and that powers a ‘digital network flywheel.'”
Barriers to adoption
Automotive OEMs, automotive suppliers, and heavy machinery are among the top three subsectors deploying AI, with companies in metals, industrial and assembly, and heavy machinery seeing the highest uptick. The five dominant areas where AI is currently employed in manufacturing spans quality inspection (39%), supply chain management (36%), risk management (36%), production line quality checks (35%), and inventory management (34%). And manufacturers peg assisting with business continuity (38%), helping employees increasing efficiency (38%), and helping employees overall (34%) as the top reasons they leverage AI.
But despite the uptick in deployment of AI in the manufacturing industry, barriers threaten to slow adoption. Twenty-five percent of respondents say that they lack the talent to properly use AI, while 23% say they don’t have the IT infrastructure and over 20% say it’s too cost-prohibitive. Nineteen percent of manufacturers told Google Cloud that they consider AI an “unproven” technology, and 16% claim that they lack the necessary stakeholder buy-in, stymieing AI implementation efforts.
The Google Cloud findings come after Alation’s latest quarterly State of Data Culture Report, which similarly discovered that only a small percentage of professionals believe AI is being used effectively across their organizations. A lack of executive buy-in was a top reason, Alation reported, with 55% of respondents to the company’s survey citing this as more important than a lack of employees with data science skills.
“Even though some barriers exist, many companies believe they have the right IT infrastructure to successfully implement AI,” the coauthors of the Google Cloud report wrote. “As AI becomes more pervasive in solving real-world problems for manufacturers, we see a shift from ‘pilot purgatory’ to the ‘golden age of AI.’ The industry is no stranger to innovation — from the days of mass production to lean manufacturing, six sigma, and more recently, enterprise resource planning. And now, AI promises to deliver even more innovation.”
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