After a series of reports showing there is “soaring” enthusiasm for internet of things (IoT) deployments, with multiple emerging technologies acting as catalysts, a study from Omdia has revealed a clear enterprise focus on extracting immediate value from IoT data streams, with organisations prioritising technologies that enable rapid decision-making and operational responsiveness.
The Omdia IoT enterprise survey took the view of over 600 enterprises across 10 countries, and the analyst said the data generated indicate clearly that edge computing and artificial intelligence (AI) integration represent a fundamental shift in how enterprises approach IoT deployments.
The analyst added that, in the face of shifting tariffs, IoT enterprises’ success with their deployments is leading to wider ones, as well as increased investments, and an exploration of new IoT services and applications. And as edge computing infrastructure becomes more sophisticated and AI algorithms continue to advance, enterprises were positioned to unlock even greater value from their IoT investments through intelligent, autonomous systems that can adapt and optimise in real time.
Larger IoT deployments often command greater marginal spending and open the value chain for suppliers who can provide consulting or professional services.
Indeed, among the survey findings was that, because of increased complexities, real-time analytics has emerged as the dominant technology priority for enterprise IoT deployments, with 82% of organisations either currently using or planning to implement real-time data processing capabilities on IoT data. Surprisingly, given the hype around the technology, this compared with 78% of organisations either currently using or planning to implement AI.
And with 95% of respondents expecting measurable benefits from IoT in two years, Omdia observed that the combination of edge processing and AI is accelerating adoption timelines and expanding the scope of possible applications.
IoT investments were found to be surging. Despite economic uncertainty, 87% of enterprises plan on spending more than $500,000 in 2026. Of all enterprises, 36% plan on spending between $1m and $5m, while 22% plan to spend more than $5m. Of all respondents, 81% are either at full IoT deployment or in trial stages of deployment, and 79% of businesses are deploying more than one IoT project. Of these enterprises, 25% are deploying more than five projects. Omdia predicted that over the next 12 months, the percentage of IoT enterprises deploying more than 10,000 devices will climb to 46%, with 18% deploying more than 50,000 devices.
Most global enterprises were found to be deploying IoT broadly in multiple areas of their business, the so-called “broad” strategy, or were using it widely as part of an overall digital transformation, the “core” strategy. This was down slightly from 90%, who said IoT was broad or core to their strategy in 2024.
Across verticals, healthcare is more broadly adopting IoT (55%), with 11% of enterprises taking a targeted approach. Omdia cautioned that certain healthcare institutions, like hospitals, may need to take a broad approach to address a wide range of applications. Agriculture differed most from the mean, with 15% of enterprises adopting a targeted approach.
IoT enterprises in the “active” phase of their deployments were considerably more likely to be considered as having IoT “core” to their digital transformation (56%). This suggests, said the operator, that trials and planning have helped build IoT into the enterprise’s overall operations. In contrast, 17% of IoT enterprises in the “planning” stage were taking a targeted approach, suggesting, said Omdia, that these deployments are very controlled.
Assessing what he thought was the main narrative of the report, Omdia IoT principal analyst John Canali noted that while the “hype and bluster” about IoT has died down, IoT deployments were now delivering impressive results to the enterprises they serve. Success is breeding success, as enterprises are expanding their deployments both with more devices as well as layering new applications on to existing ones.
“Strong adoption of 5G and edge computing are laying the groundwork for real-time analytics,” he said. “More than ever, we are seeing IoT evolve from simple data collection to process automation. Our research demonstrates that over 75% of enterprises are starting to layer additional services like AI and machine learning to process the massive amounts of data coming from their IoT deployments – this is another important step transforming business operations from reactive to predictive and creating an environment where critical decisions can be made in milliseconds rather than minutes.
“IoT should be seen as a framework in which different technologies and services can play important roles,” said Canali. “Some enterprises are evolving their deployments further and looking to layer in services such as AI, so that they can predict issues before they occur. 5G connectivity allows massive amounts of data to be collected from devices and sensors, while AI is used to parse the data and increase efficiency. In this sense, AI should not be seen as crowding out IoT investment, but instead, AI is helping to drive the success of IoT deployments and thus will likely accelerate IoT investment.”
