Skip to main content

AI adoption not yet leading to business benefits for manufacturers

AI Head
(Image credit: Shutterstock)

Artificial Intelligence (AI) may be a hugely promising technology in the manufacturing industry, but so far it’s remained nothing more than a promise.

That's according to a new report from Google Cloud which claims many manufacturers are still stuck in “pilot purgatory” as nascent AI technologies aren't mature enough for wider rollouts just yet.

The report also cites recent Gartner findings which claim only around a fifth (21%) of companies in the manufacturing industry have active AI initiatives in production.

Despite this current situation, however, the future is far from grim for AI in manufacturing. The Covid-19 pandemic has, most likely, spurred a significant increase in the use of AI and other digital enablers, Google Cloud claims.

Helps with business continuity

Polling 1,000 senior manufacturing executives in seven countries for the report, Google Cloud found that three-quarters (76%) turned to digital enablers and disruptive technologies such as data and analytics, cloud, and AI, to mitigate the negative effects of the pandemic. Furthermore, two-thirds of manufacturers who successfully deployed AI said they’re relying more on the tool with each passing day. 

Automotive/OEMs, automotive suppliers and heavy machinery are the three sub-sectors deploying AI for their everyday operations the most.

Drilling deeper into what these companies are using AI for, Google Cloud found that business continuity and employee efficiency were the two biggest use cases, as well as to be of help for employees overall. 

The report states AI’s strength in augmenting employees is evident, be it by providing prescriptive analytics, flagging safety hazards, detecting potential defects on the assembly line, or something entirely different.

Improving employee efficiency aside, AI’s other big use cases are quality control and supply chain optimization, it was stated. Many firms use it for quality inspection and product/production line quality checks, as well as for supply chain management, risk management and inventory management.

To make AI more widely adopted in the manufacturing industry, it needs to be easy to deploy, and easy to use, the report concludes. The industry will move away from “pilot purgatory” and into the “golden age” of AI, as the technology becomes more ubiquitous in solving actual problems.  

Sead Fadilpašić is a journalist - crypto, blockchain and new tech in general. He is also a hubSpot certified content creator and Writer.