The AIoT market size is forecasted to rise from USD 18.37 billion in 2024 to USD 79.13 billion by 2030, at a CAGR of 27.6% during the period.
The need for AIoT solutions is predicted to grow due to the exponential growth of data generated from IoT devices. As the number of connected IoT devices continues to rise exponentially, there’s an urgent requirement for solid frameworks that can manage and analyze all the data created effectively. The other key factor for enhancing the AIoT market is the need for automation and efficient running of activities. In the modern world, most companies are more orientated towards implementing AIoT systems in their marketing strategies to increase operations’ efficiency while decreasing costs. The need to enhance user experience and provide personalization plays an essential role within the growing AIoT market. Making it possible for businesses to respond quickly and in a more personalized manner to their customers’ needs when combined with IoT gadgets is appealing to many businesses in this age.
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Moreover, the emergence of Generative AI technologies adds to this urgency, with many companies identifying them as essential for their future strategies. As the regulatory framework for the use of AI becomes more defined, especially for corporations, these provisions are regarded as safeguards and structures that promote sustainable management. Moreover, these tendencies bring a crucial situation for adopting AIoT, as companies integrating such technologies will not only create better experiences for end-users but also optimize their internal operations, all in preparation for the cut-throat competition presented by the AIoT market.
By offering, the service segment is projected to register the highest CAGR during the forecast period.
In the AloT market, services are needed to implement and deploy AloT solutions, which can be classified into professional and managed services. To ensure that the application of AloT solutions in businesses is smooth, Professional services include training and consulting, deployment and integration, and support and maintenance. For instance, AWS offers a broad consultation service to help with the system architecture, management, and security. At the same time, Microsoft has consulting services for the Azure IoT solutions for system setup and development. Oracle and SAP also provide specific consulting on implementing the AloT and maximizing IoT data. For instance, in April 2024 SAP came up with dedicated services on IoT, emerging for the digital economy, connecting loT data to ERP fundamentals for improving operational effectiveness.
Based on deployment type, the cloud-based AIoT segment holds the largest market size during the forecast period.
Based on cloud-based AIoT, data collection and processing from IoT devices are used. Tying the loT devices to the cloud is crucial since this environment best suits processing and storing data in numerous applications and products. AloT architecture of cloud-based systems is divided into four layers: the device layer, connectivity layer, user communication layer, and cloud layer. The device layer includes sensors, beacons, cars, embedded devices, and tags. The connectivity layer, including field and cloud gateways, is essential in interacting between cloud storage and the controllers, intelligent devices, and sensors. The cloud layer is central to AloT because it provides the environments, including Al engines, data visualization tools, APIs, data storage, and analytics for information processing. At the same time, the user communication layer enables interaction through the mobile application and web portal.
Unique Features in the AIoT Market
AIoT integrates advanced AI algorithms with IoT devices to enable real-time data processing and decision-making. This combination allows businesses to analyze large volumes of data instantly and take immediate action, enhancing operational efficiency and responsiveness, especially in critical applications like manufacturing, healthcare, and logistics.
One of the standout features of AIoT is its ability to drive autonomous operations. AI-enabled IoT devices can perform tasks without human intervention, such as predictive maintenance, autonomous vehicles, and smart energy management. This automation reduces the need for manual oversight and increases operational efficiency across industries.
AIoT often incorporates edge computing, which enables data processing closer to the source of data generation. By minimizing the need to send data to central servers, edge computing enhances the speed of decision-making, reduces latency, and alleviates bandwidth constraints, making AIoT applications more efficient and reliable, especially in remote locations or time-sensitive scenarios.
AIoT devices are increasingly leveraging 5G networks for faster data transfer, ultra-low latency, and improved connectivity. 5G’s capabilities allow AIoT systems to operate in real time, supporting high-demand applications like autonomous vehicles, smart cities, and industrial automation. This integration accelerates innovation and creates new opportunities for AIoT use cases.
AIoT solutions excel in predictive analytics, helping businesses predict and prevent equipment failures before they occur. By analyzing data from IoT sensors, AI algorithms can identify patterns and anomalies, enabling businesses to perform maintenance only when needed, reducing downtime, and lowering operational costs in sectors like manufacturing, energy, and healthcare.
Market Players
The major vendors covered in the AIoT market include IBM (US), Cisco (US), AWS (US), Google (US), Microsoft (US), Oracle (US), HPE (US), Intel (US), Hitachi (Japan), SAP (Germany), Tencent Cloud (China), Sharp Global (Japan), SAS (US), PTC (US), Telit Cinterion (UK), Robert Bosch (Germany), Axiomtek (Taiwan), Softweb Solutions (US), Wiliot (Israel), Relayr (US), Terminus Group (China), C3 IoT (US), Clearblade (US), Semifive (South Korea), Falkonry (US), Uptake (US), Butlr (US).
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