As we enter 2026, the convergence of Artificial Intelligence (AI) and Internet of Things (IoT) infrastructure is reshaping industries, bringing unprecedented opportunities for optimized operations, enhanced security, and improved sustainability. This transformation is part of the rapidly growing field of AIOT.
Five AIoT Trends in 2026
Scenario-Based AIoT Solutions Are Rapidly Unlocking New Business Value
Thanks to AIoT, we are witnessing a profound digital transformation that transcends basic IT and moves towards deep integration with Operational Technology (OT). Business value no longer stems from fragmented data collection but increasingly from natural and continuous insights into daily operations. By embedding sensing capabilities into specific real-world scenarios, AIoT enables automated agility and real-time decision-making, thereby rapidly creating new business value.
Large-Scale AI Models Are Evolving to Provide New Capabilities for “AI+”
Large-scale AI models are empowering core analytics and processing processes through “AI+” integration. Large language models have revolutionized human-computer interaction, while industry-specific models are reshaping how IoT data interacts with the physical world. We have already seen these models significantly improve accuracy and efficiency by embedding artificial intelligence into data analytics and signal processing. AI agents are bridging the gap between perception and human intent, enabling users to communicate naturally using everyday language.
Edge AI is transforming devices from data collectors into intelligent analyzers
The “cloud + AI” model is increasingly becoming the only option for enterprise digital transformation. By migrating AI capabilities from the cloud to the edge, enterprises can achieve millisecond-level response times, seamless offline operation, and maintain local privacy.
This localized architecture extends its value by significantly optimizing storage efficiency. This is particularly important for complex video analytics. Edge devices can now accurately identify key targets, such as people or vehicles, at the source. The system then applies differential coding — preserving critical foreground details while compressing background areas. This significantly reduces storage requirements without sacrificing visual clarity.
Responsible AI integrates ethics into every stage of innovation
AI is transforming our lives, work, and businesses at an unprecedented pace. However, this transformation also brings a crucial responsibility: ensuring that innovation unfolds in a safe, ethical, transparent, and universally beneficial manner. Responsible AI is no longer an option; it is both a moral imperative and a strategic necessity, capable of building trust, mitigating risks, and driving long-term innovation.
It should permeate the entire AI lifecycle — from R&D to deployment and practical application.
AIoT is expanding the role of technology in business, society, and the environment
AIoT is being widely applied across a broader range of social and environmental sectors, demonstrating how intelligent systems can serve both humanity and nature. Specialized AIoT devices are revolutionizing conservation efforts, from wildlife monitoring to vegetation health tracking. For example, crop growth monitoring systems utilizing AIoT technology for large-scale real-time analysis are becoming increasingly prevalent in agriculture, enabling precision management and yield optimization through digitalization.