AI in IoT Market Analysis

Software Segment Analysis

In the AI in IoT market, software is expected to garner the largest revenue share of 61.6% during the forecasted years. The dominance of the segment is since it provides the intelligence layer for AI IoT, which includes device management, analytics platforms, middleware, and AI model deployment frameworks. Software allows enterprises to process large volumes of IoT data and integrate edge or cloud AI solutions.  In October 2025, ASUS IoT announced that it had launched AISVision 365, which is a cloud-native AI-vision platform that is designed to accelerate industrial AI deployment by enabling machine-vision projects directly in the browser. The platform integrates data annotation, model training, and inference management, supporting AI tasks such as classification, segmentation, anomaly detection, and object detection with continuous cloud updates. It also offers flexible deployment across cloud and edge environments, compatible with Windows, Linux, NVIDIA Jetson, and ARM-based hardware, hence denoting a wider segment scope.

Technology Segment Analysis

By the conclusion of 2035, machine learning & deep learning in the technology segment are likely to garner a significant revenue share in the artificial intelligence in IoT market. ML & DL are foundational factors that derive actionable intelligence from IoT sensor data, allowing anomaly detection, predictive insights, automation, as well as self-optimizing systems.  In this regard July 2025, AWS announced the general availability of multivariate anomaly detection in AWS IoT SiteWise, which enables industrial customers to automatically identify abnormalities across equipment and asset data. Besides, this capability embeds machine learning directly into the IoT platform, allowing predictive and preventive maintenance without requiring any ML expertise. The firm also mentioned that it helps industries monitor critical assets such as turbines, compressors, and motors in real time, improving operational efficiency and reducing costly downtime.

End use Segment Analysis

The manufacturing segment in the AI in IoT market will grow at a considerable rate over the forecasted period. The growth of the subtype is highly subject to huge operational efficiency gains from predictive maintenance, real-time quality control, and automation.  In addition, smart factories and AI IoT initiatives increase productivity and reduce downtime, increasing uptake in this field. The subtype also benefits from AI-based robotics that streamline assembly lines and reduce human error. In addition, the IoT-enabled sensors continuously collect production data, feeding AI models that optimize machine performance and energy usage. Furthermore, AI-powered supply chain analytics help manufacturers predict demand, manage inventory, and minimize delays. The integration of AI in IoT enhances worker safety by monitoring equipment conditions and environmental hazards in real time, hence making it suitable for standard artificial intelligence (AI) in IoT market growth.

Our in-depth analysis of the global AI in IoT market includes the following segments: