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Home » AI Accelerates Enterprise IoT Growth Beyond Connectivity
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AI

AI Accelerates Enterprise IoT Growth Beyond Connectivity

By Mia LiFebruary 6, 2026No Comments2 Mins Read
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  • Enterprise IoT revenue grew around 13% to US $324 billion in 2025.
  • Fewer than 1% of connections currently use true edge AI, raising doubts about near-term automation claims.

What happened: AI shifts the narrative from connectivity to autonomy

The global enterprise Internet of Things (IoT) market reached approximately US $324 billion in 2025, reflecting 13% annual growth, according to IoT Analytics’ State of Enterprise IoT 2026 report. The rise is attributed to increasing adoption of connected systems across manufacturing, logistics and infrastructure, alongside growing interest in integrating artificial intelligence into these deployments.

The total number of IoT connections worldwide climbed to 21.1 billion, with enterprise applications accounting for roughly 45% of the total. Growth was particularly strong in emerging markets such as China and India, where large-scale industrial digitalisation programmes are accelerating adoption.

However, despite the market’s scale, the report suggests that less than 1% of IoT connections currently feature genuine edge AI, meaning most systems still rely on centralised analytics and human intervention rather than autonomous machine decision-making.

At the same time, analysts noted a shift in corporate language: mentions of “IoT” in earnings calls are declining, while references to “AI” and “industrial AI” are increasing, signalling that companies are rebranding connected infrastructure as part of broader artificial intelligence strategies.

Also read: Intel results test turnaround amid AI demand
Also read: Intel, Nvidia, AMD: Who is going to win the AI chip race?

Why it’s important: Big spending, but limited real-world autonomy

The figures highlight how embedded IoT technologies have become in enterprise operations, supporting efficiency gains, asset monitoring and predictive maintenance. Yet the low penetration of edge AI raises questions about whether the industry is overstating its readiness for truly autonomous systems.

While vendors promote AI-powered IoT as a pathway to self-optimising factories and logistics networks, integrating AI into complex industrial environments remains technically challenging. Security risks, interoperability problems and legacy infrastructure constraints continue to slow deployment. Broader market forecasts suggest continued growth in enterprise IoT spending over the next few years, but it remains unclear whether this investment will translate into widespread autonomous operations or simply more sophisticated data collection. For now, the market’s momentum appears strong, but the promised leap from connectivity to autonomy may take longer than industry narratives suggest.

AI IoT IoT and AI Technology Trends
Mia Li

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