PUBLISHER: Mind Commerce | PRODUCT CODE: 2080568
PUBLISHER: Mind Commerce | PRODUCT CODE: 2080568
Agentic AI represents a major shift from pre-programmed automation to autonomous, goal-directed reasoning. By integrating with the Internet of Things (IoT), these AI agents move beyond simple "if-this-then-that" rules to deliver Decisions as a Service (DaaS), fundamentally transforming how industries operate.
Traditional IoT relies on static thresholds, whereas Agentic IoT interprets context to make complex choices independently.
Agentic AI converts passive data networks into self-managing physical systems.
Deploying autonomous decision-makers into physical infrastructure introduces critical technical and operational hurdles.
Many industry verticals will be transformed through AI integration with enterprise, industrial, and consumer product and service systems. It is destined to become an integral component of business operations including supply chains, sales and marketing processes, product and service delivery, and support models.
We see AIoT evolving to become more commonplace as a standard feature from big analytics companies in terms of digital transformation for the connected enterprise. This will be realized in infrastructure, software, and SaaS-managed service offerings. Recent years have witnessed rapid growth for IoT data-as-a-service offerings to become AI-enabled decisions-as-a-service-solutions, customized on a per industry and company basis. Certain data-driven verticals such as the utility and energy service industries will lead the way.
As IoT networks proliferate throughout every major industry vertical, there will be an increasingly large amount of unstructured machine data. The growing amount of human-oriented and machine-generated data will drive substantial opportunities for AI support of unstructured data analytics solutions. Data generated from IoT-supported systems will become extremely valuable, both for internal corporate needs as well as for many customer-facing functions such as product life-cycle management.
The use of AI for decision-making in IoT and data analytics will be crucial for efficient and effective decision-making, especially in streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real time will add an entirely new dimension to service logic.
In many cases, the data itself, and actionable information will be the service. AIoT infrastructure and services will, therefore, be leveraged to achieve more efficient IoT operations, improve human-machine interactions, and enhance data management and analytics, creating a foundation for IoT Data as a Service (IoTDaaS) and AI-based Decisions as a Service.
This AIoT market report provides an analysis of technologies, leading companies and solutions. The report also provides quantitative analysis including market sizing and forecasts for AIoT infrastructure, services, and specific solutions for the period 2026 through 2030.
The report also provides an assessment of the impact of 5G upon AIoT (and vice versa) as well as blockchain and specific solutions such as Data as a Service, Decisions as a Service, and the market for AIoT in smart cities.