A new study sponsored by SAS shows that AIoT delivers tangible business value despite challenges.
A study shared by SAS, a global leader in data and artificial intelligence, shows that the convergence of artificial intelligence and the Internet of Things — AIoT — is improving the efficiency, safety, and decision-making capabilities of manufacturing, industrial, and energy companies worldwide.
Key findings from the SAS-sponsored IDC briefing, “How AIoT is Reshaping Industrial Efficiency, Safety, and Decision-Making,” include:
Predictive maintenance is currently the mainstream AIoT application. Nearly 71% of enterprises use AIoT for predictive maintenance. This makes it the most widely adopted application among surveyed manufacturing/industrial and energy companies. IT automation (53%) and supply chain and logistics (47%) are other major application areas for AIoT.
AIoT delivers tangible business value. 54% of respondents expect AIoT to significantly reduce costs. Moreover, 52% expect it to lead to smarter and faster innovation, and 49% expect it to streamline operational processes. Furthermore, 63% of respondents believe AIoT will improve productivity and competitiveness. The skills gap is the primary challenge. Indeed, the skills gap is the biggest obstacle to the success of AIoT, even surpassing traditional system integration and data quality issues. These become the most significant hindrance. Other challenges include high implementation costs, misaligned business processes, and cultural resistance. Addressing these issues is crucial to fully unlocking the potential of AIoT.
Heavy AIoT users reap greater value. Organizations heavily using AIoT are twice as likely to report significantly higher-than-expected benefits compared to those using the technology only minimally. Notably, less than 3% of organizations reported that the value of AIoT “did not meet expectations.”
Strong momentum. Globally, 62% of organizations have adopted AIoT, with another 31% planning to adopt it. Among existing adopters, 43% have achieved widespread deployment or full integration.
Adoption rates and perceived value vary across regions. The Asia Pacific region leads in moderate AIoT adoption, while North America shows strong growth momentum. The Europe, Middle East, and Africa (EMEA) region remains optimistic about the value of AIoT across all use cases. “Our research found that heavy AIoT users are almost twice as likely as other users to report benefits far exceeding their expectations. Less than 3% of the industrial executives surveyed believed that the value of AIoT was not meeting expectations,” said Kathy Lange, research director for AI software at IDC.
“The conclusion is clear: AIoT is driving innovation, streamlining operations, and enabling smarter, faster decision-making.”
This IDC study is based on a survey of more than 300 executives in the global manufacturing and energy sectors.
“This IDC briefing confirms what our customers in the global manufacturing and energy sectors have told us: AIoT has evolved from a buzzword into a powerful technology and business priority. Whether it’s enhancing predictive maintenance for critical equipment or improving factory and grid operations, AIoT can significantly reduce costs, improve quality, and increase efficiency,” said Jason Mann, vice president of IoT at SAS.
Manufacturing Transformation
Manufacturers and industrial enterprises face numerous challenges, including supply chain disruptions, national security concerns, and persistent labor shortages. To address these challenges, manufacturers are accelerating their digital transformation strategies. They are leveraging technologies such as Artificial Intelligence of Things (AIoT) to modernize operations and address labor shortages.
Factory automation is one of the most significant outcomes of this transformation, and AIoT is the catalyst driving its growth. Manufacturers across industries are using AIoT for automation. This includes not only task automation but also decision automation — optimizing processes, improving product quality, and reducing downtime.
“As clearly illustrated in this briefing, AIoT creates business value. The more industrial enterprises use AIoT, the greater the benefits. We expect the adoption of AIoT solutions to accelerate as enterprises achieve increased efficiency, productivity, and cost savings. TD SYNNEX remains committed to supporting SAS partners and their AIoT customers,” said Dez Tsai, Senior Director of Global Artificial Intelligence, Data, and Supplier Transformation at TD SYNNEX, a strategic IT distribution partner of SAS.
Injecting Vitality into the Market
For power and energy companies, AIoT offers numerous advantages. By analyzing data from countless sensors across the power grid and key equipment, including generators, power plants, and wind turbines, AIoT can help operators manage costs, predict demand, optimize operations, and enhance sustainability. Thus, it improves grid efficiency.
Artificial intelligence technologies enable more people within an organization, including those with varying skill levels and roles, to interact with data. This directly addresses the skills gaps identified in research. Whether working on the factory floor, maintaining overhead lines, or developing corporate strategy, all personnel can leverage the Internet of Things (IoT) along with generative, agent-based, and traditional AI (i.e., machine learning) to make data-driven decisions.
Accelerating AIoT Innovation
SAS IoT solutions integrate AI, machine learning, and edge-to-cloud integration to analyze massive amounts of high-speed data. Combining AI with these IoT solutions can enhance the value of existing infrastructure investments. This enables the digital transformation of the workforce by shifting from human oversight to intelligent coordination.
Other organizations that have benefited from SAS IoT and streaming analytics to improve asset reliability, enhance product quality, and increase the efficiency of connected systems include: Georgia-Pacific, Jakarta Smart City, Lloyd’s List, Lockheed Martin, Cary Town (North Carolina), Volvo Trucks and Mark Trucks, and Weinberger.