Engineering 101

Manufacturers Among the Top Group Putting AIoT into Action


A recent survey of global business leaders reveals the most significant predictor in realizing value from Internet of Things (IoT) initiatives across an organization is the heavy use of artificial intelligence (AI). Ninety percent of survey respondents heavily using AI in their IoT operations reported exceeding value expectations. The research also showed organizations using IoT with AI appear to be more competitive than IoT-only enterprises by a double-digit margin across a variety of business indicators like employee productivity, innovation and operating costs.

“In these results, we are seeing that organizations working with IoT data realize that if they want to get the real value out of the data, they need AI and analytics,” said Oliver Schabenberger, Chief Operating Officer at SAS. “I think it is fair to say that most successful IoT operations are actually AIoT operations.” AIoT is defined as decision making aided by AI technologies in conjunction with connected IoT sensor, system or product data. AI technologies include deep learning, machine learning, natural language processing, voice recognition and image analysis.

One of the key focuses of the study was that of companies implementing AIoT. As it turns out, manufacturers are among the top groups putting the technology into play.

Western Digital’s Khera said they had to be persistent and keep pushing on pairing IoT data with AI. “Those projects are now our plan of record process to use AI,” said Khera. “It’s working well, and it’s trusted across the board. We are now using advanced analytics to help us tackle problems in R&D. I can use various advanced analytic techniques to understand the shape of my data, to understand the features, what are the drivers, I can look for hidden effects for anomalies that traditional techniques or the human eye just won’t see.”

Jay Cei, Chief Operating Officer at Ulbrich Steel, a global metal manufacturer, said his priority is to gain acceptance for AIoT across the company. “People are going to fear losing their jobs,” Cei said. “What I really believe is [AIoT] is going to enable them to function at least two levels higher than they can now. I really see these operators functioning as business unit managers as a result of this. I’m looking at SAS® Analytics for IoT as one of the AI-embedded solutions for me to use to get us to be able to better execute our capabilities-driven strategy.”

It’s important to remember that any implementation of this nature must start at the top.

For AIoT success, the bottom line is to start at the top according to Andy Daecher, Principal, Deloitte Consulting LLP and Internet of Things Practice Leader. “These initiatives really have to be on the CEO’s agenda,” Daecher said. “He or she needs to repeatedly say, ‘this needs to happen in our organization.’ You can’t have a successful AIoT initiative without the business initiating it, period. These are really business initiatives, not technology initiatives.”

Read the full IoT study, which provides eye-opening insights here.

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