Study: AI boosts realized value from IoT initiatives

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. The study, conducted by SAS, Deloitte and Intel with research and analysis from IDC, asked 450 business leaders about their use of IoT and AI technologies.

“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,” says 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.

Other key findings include:

• 79% of senior leaders are involved in IoT project decisions, and 92% of those leaders say that AIoT value exceeds expectations.
• 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. That’s followed by improving the ability to innovate (17.5%), offering customers new digital services (14.3%) and decreasing operational costs (11.1%).
• Companies that have developed AIoT capabilities report stronger results across critical organizational goals including the ability to speed up operations, introduce new digital services, improve employee productivity and decrease costs. For example, companies using IoT data to speed up operations without AI saw a 32% increase; companies adding AI to the mix saw speeds improve by 53%.
• 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.

“AI and IoT are no longer in separate swim lanes,” adds Melvin Greer, chief data scientist at Intel Americas. “AI closes the loop in an IoT environment where IoT devices gather or create data, and AI helps automate important choices and actions based on that data. Today, most organizations using IoT are only at the first ‘visibility’ phase where they can start to see what’s going on through IoT assets. But they’re moving toward the reliability, efficiency and production phases, which are more sophisticated and require stronger AI capabilities.”