AIoT refers to the incorporation of AI capabilities into IoT systems and devices, allowing these interconnected items to gather, analyse, and respond to data autonomously or semi-automatically. This convergence improves the capabilities of traditional IoT systems by introducing intelligence, predictive analytics, and decision-making capabilities at multiple levels of the IoT architecture, ranging from edge devices to clouds.

Drivers: Increasing government initiatives in digital transformation are expected to boost market growth. Governments worldwide see AIoT technologies as a way to improve efficiency, spark innovation, and enhance public services. By funding projects for smart cities, advanced manufacturing, and digital infrastructure, they aim to promote AIoT use. These initiatives focus on combining AI and IoT for better resource management, transportation, and healthcare. A rising focus on energy efficiency and sustainability also supports AIoT market growth. With growing concerns about climate change and resource depletion, businesses and governments are prioritizing technologies that lower energy use and optimize resources. AIoT solutions help achieve sustainability by enabling smarter energy management and automation, while also driving investments in AIoT technologies across different sectors.

Challenges: The lack of a competent workforce with experience in AIoT platforms is limiting market expansion. As more businesses attempt to use AIoT solutions, they have difficulties in hiring personnel with the appropriate technical expertise in both AI and IoT technologies. This skills gap restricts organisations' capacity to fully use AIoT capabilities, impeding their efforts to optimise operations and innovate. Without qualified individuals, firms may fail to properly integrate AI with IoT devices, leading to underutilisation of these technologies and missed possibilities for increased efficiency and production.

Market Trends: The market is expanding due to AIoT solutions' high efficiency. Better resource management and quicker data processing are made possible by these technologies. IoT devices that have AI built in can analyse vast volumes of data locally, cutting down on latency and the requirement for continuous cloud connections. This results in real-time decision-making, which is crucial for a number of applications, including healthcare and smart manufacturing. AIoT solutions are increasingly appealing to companies trying to increase their bottom line because of their rapid pattern and anomaly recognition, which improves operational efficiency and lowers energy usage and operating expenses.

Google LLC, IBM Corporation, Microsoft, Oracle, PTC, Salesforce, Inc, SAS Institute, Inc, SAP SE, Softweb Solutions Inc, and Thingstel Tech Solutions India Pvt Ltd are just a few of the major market players that are thoroughly examined in this market study along with revenue analysis, market segments, and competitive landscape data.

By Component: Based on the Component, Global AIoT Market is segmented as; Software, Services.

By Deployment: Based on the Deployment, Global AIoT Market is segmented as; On-premise Deployment, Cloud-based Deployment.

By End User: Based on the End User, Global AIoT Market is segmented as; Manufacturing, Infrastructure, Healthcare, Retail, BFSI, Automotive, Other.

By Region: This research also includes data for North America, Latin America, Asia-Pacific, Europe, Middle East & Africa.

This study also encompasses various drivers and restraining factors of this market for the forecast period. Various growth opportunities are also discussed in the report.