Design Engineering

Study: Pairing AI, IoT together outperforms IoT alone

By DE Staff   

Automation Machine Building

Ninety percent of business leaders adopting AI and IoT report exceeding value expectations.

According to a survey of global business leaders, conducted by SAS, Deloitte and Intel with research and analysis by IDC, the best predictor of deriving value from IoT initiatives is the use of artificial intelligence (AI). In total, the survey (AIoT – How IoT Leaders are Breaking Away) asked 450 business leaders from around the world about their use of IoT and AI technologies.

Of survey respondents who heavily using AI in their IoT operations, 90% 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 many business indicators including 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, COO at SAS. “I think it is fair to say that most successful IoT operations are actually AIoT operations.”

According to the study, 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.


The survey’s other findings include:

68% of companies rely on IoT data to inform daily operational decisions through spreadsheets and other non-AI technology. Only 12% of respondents use IoT to inform planning decisions, but when AI enters the picture, respondents using the data for daily planning increases to 31%.

34% of respondents said increasing revenue is the top goal for using AioT, followed by improving the ability to innovate (17.5%), offering customers new digital services (14.3%), and decreasing operational costs (11.1%).

Business intelligence (33%), near-real-time monitoring and visibility (31%) and condition-based monitoring (30%) topped the list of analysis techniques used with IoT projects.

For AIoT success, however, initiatives need to start at the top said Andy Daecher, Principal, Deloitte Consulting LLP and Internet of Things Practice Leader. “These initiatives really have to be on the CEO’s agenda,” he 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.”


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