Google Research Reveals Where and How of AI Utilization in Manufacturing, and Barriers

By Chantal Polsonetti

Category:
Technology Trends

While the promise of artificial intelligence (AI) transforming the manufacturing industry is not new, long-ongoing AI Utilization in Manufacturingexperimentation hasn’t yet led to widespread business benefits.  New research from Google Cloud, however, reveals that the COVID-19 pandemic may have spurred a significant increase in the use of AI and other digital enablers among manufacturers. According to their data—which polled more than 1,000 senior manufacturing executives across seven countries—76% have turned to digital enablers and disruptive technologies, such as data and analytics, cloud, and artificial intelligence due to the pandemic.  Another 66% of manufacturers who use AI in their day-to-day operations report that their reliance on AI is increasing. 

Moving from edge cases to mainstream business needs

The top three sub-sectors deploying AI to assist in day-to-day operations are automotive/OEMs (76%), automotive suppliers (68%), and heavy machinery (67%).  Google Cloud’s research shows that companies who currently use AI in day-to-day operations are looking for assistance with business continuity (38%), helping make employees more efficient (38%), and to be helpful for employees overall (34%). AI/ML technology can augment manufacturing employees’ efforts, whether by providing prescriptive analytics like real-time guidance and training, flagging safety hazards, or detecting potential defects on the assembly line.

In terms of specific AI use cases called out by the research, two main areas emerged: quality control and supply chain optimization. In the quality control category, 39% of surveyed manufacturers who use AI in their day-to-day operations use it for quality inspection and 35% for product and/or production line quality checks. Using AI vision, production line workers can spend less time on repetitive product inspections and can instead focus on more complex tasks, such as root cause analysis.

In the supply chain optimization category, manufacturers said they tapped AI for supply chain management (36%), risk management (36%), and inventory management (34%).

AI use differs by geography, but not for the reasons you may think.

The extent to which AI is already being used today varies quite strongly between geographies. While 80% and 79% of manufacturers in Italy and Germany, respectively, report using AI in day-to-day operations, that percentage plummets in the United States (64%), Japan (50%) and Korea (39%).

Although the most common barrier, just a quarter (23%) of manufacturers surveyed believe they don’t have the talent to properly leverage AI. Cost, too, does not appear to be a roadblock (21% of those surveyed). Rather, the missing link appears to be having the right technology platform and tools to manage a production-grade AI pipeline.

Looking ahead: The Golden Age of AI for manufacturing

The key to widespread adoption of AI lies in its ease of deployment and use. As AI becomes more pervasive in solving real-world problems for manufacturers, Google Cloud sees the industry moving away from "pilot purgatory" to the "golden age of AI." The manufacturing industry is no stranger to innovation, from the days of mass production, to lean manufacturing, six sigma and, more recently, enterprise resource planning. AI promises to bring even more innovation to the forefront.

To learn more about these findings, download the full report here

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