New research from Google Cloud and The Harris Poll reveals that the pandemic has led to a significant increase in the use of AI among manufacturers. According to a survey of senior executives from over 1,000 companies, two-thirds of manufacturers who use AI in their day-to-day operations say their addiction to AI is increasing, with 74% saying they are aligning themselves with it. evolution of the work landscape.

According to a 2020 PricewaterhouseCoopers investigation, companies in the manufacturing sector expect efficiency gains over the next five years from digital transformations. McKinsey’s research with the World Economic Forum assesses 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 those polled in the Google Cloud report say they have turned to “disruptive technologies” such as AI, data analytics and the cloud to help navigate the pandemic. Manufacturers told surveyors that they have used AI to optimize their supply chains, including in management (36%), risk management (36%) and asset management. stocks (34%). Even among companies that don’t currently use AI in their day-to-day operations, about a third believe it would make employees more efficient (37%) and be useful for all employees (31%), according to Google Cloud. .

Manufacturing is experiencing a resurgence as business owners seek to modernize their factories and speed up operations. According to ABI research, more than 4 million commercial robots will be installed in more than 50,000 warehouses worldwide by 2025, compared to less than 4,000 warehouses in 2018. Oxford Economics anticipates 12.5 million manufacturing jobs will be automated in China, while McKinsey predicts that machines will occupy more than 30% of those jobs in the United States

Ford is one of the manufacturers using AI in its operations through a relationship with Google. Announced in February, the automaker plans to leverage Google’s expertise in data, AI and machine learning as part of Team Upshift, a six-year partnership and collaborative group launched in 2023. Ford says initiative will accelerate modernization of product development, manufacturing, and supply chain management, including exploring the use of vision AI for training manufacturing employees and even more reliable performance of factory equipment.

“[This] will step up our efforts to democratize AI across our business, from the factory to vehicles to dealerships, ”said Bryan Goodman, director of AI and cloud at Ford, 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 a data-fueled AI ecosystem that powers a ‘digital network flywheel’.

Barriers to adoption

Automotive OEMs, Automotive OEMs, and Heavy Machinery are among the top three AI-deploying subsectors, with companies in metals, industry and assembly, and heavy machinery posting the largest increase . The top five areas where AI is currently employed in manufacturing cover quality inspection (39%), supply chain management (36%), risk management (36%), controls the quality of production lines (35%) and inventory management (34%). . And manufacturers see supporting business continuity (38%), helping increase employee efficiency (38%), and helping employees as a whole (34%) as the most important reasons they are leveraging AI.

But despite the increasing deployment of AI in manufacturing, obstacles threaten to slow adoption. Twenty-five percent of respondents say 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 expensive . Nineteen percent of manufacturers told Google Cloud that they consider AI to be an “unproven” technology, and 16% say they lack the necessary buy-in from stakeholders, which hinders business development. AI implementation efforts.

The Google Cloud findings come after inflation’s latest quarterly State of Data Culture report, which also found that only a small percentage of professionals believe AI is being used effectively in their organizations. Lack of leadership buy-in was one of the main reasons, Alation reported, with 55% of company survey respondents citing this as more important than the lack of employees with data science skills. .

“Even though some hurdles exist, many companies believe they have the right IT infrastructure to successfully implement AI,” wrote the co-authors of the Google Cloud report. “As AI becomes increasingly ubiquitous in solving real-world problems for manufacturers, we are seeing a shift from ‘pilot purgatory’ to the ‘golden age of AI’. Industry is no stranger to innovation – from the era of mass production and lean manufacturing, six sigma and, more recently, enterprise resource planning. And now, AI promises to deliver even more innovation.