AIoT Market Trends, Analysis & Forecast, 2032
As per a recent research report, AIoT Market surpass USD 110 Bn by 2032.
The market demand is propelled
by the convergence of Artificial Intelligence (AI) and the Internet of Things
(IoT). AIoT, a powerful combination of intelligent algorithms and connected
devices, is revolutionizing industries, creating new business opportunities, and
transforming the way we live & work. The recent years have seen increased
adoption of smart devices, data generation, and advancements in AI
technologies.
The integration of AIoT has
created multitude of possibilities, including predictive maintenance, smart
homes, autonomous vehicles, precision agriculture, industrial automation, and
much more. This convergence has the potential to streamline operations, enhance
efficiency, and deliver seamless user experiences across various sectors. The
rapid adoption of IoT devices across industries, along with the escalating
demand for real-time data analysis and decision-making, is fueling the need for
AIoT solutions.
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The AIoT services market segment will record a strong growth during
2023 and 2032, owing to need for effective integration of AI capabilities with the
IoT infrastructure across industries. AIoT services include consulting, system
integration, managed services, and support. These services are designed to
assist organizations in deploying, managing, and optimizing AIoT solutions,
enabling them to extract maximum value from their connected devices and data. The
service providers bring expertise in AI algorithms, data analytics, cloud
computing, and cybersecurity, helping businesses overcome implementation
challenges, enhance operational efficiency, and drive innovation.
The AIoT market from on-premise segment is expected to grow
significantly through 2032, on account of greater control offered by this
deployment to organization over their data, security, and customization. This
deployment model is favored by industries with stringent data privacy
requirements, regulatory compliance needs, or specific infrastructure
limitations that restrict the use of cloud-based services. On-premise
deployment enables organizations to leverage the power of AI and IoT while
maintaining direct ownership and management of their technology stack. It
allows for seamless integration with existing systems and networks, ensuring
compatibility and enabling real-time data processing & analysis. By
deploying AIoT solutions on-premise, businesses can enjoy increased data
sovereignty, reduced latency, and enhanced data privacy.
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North
America AIoT market will garner notable revenues by 2032. The region's advanced
technological infrastructure, strong digital ecosystem, and high concentration
of tech-savvy companies create a fertile ground for AIoT innovation &
deployment. Numerous industries, including healthcare, manufacturing,
transportation, and retail, are harnessing AIoT solutions to drive digital
transformation, improve operational efficiency, and gain a competitive edge.
The favorable government initiatives, supportive regulatory frameworks, and a
skilled workforce focused on AI & IoT will augment the regional industry
growth in the coming years.
Partial chapters of report table of contents
(TOC):
Chapter 2 Executive Summary
2.1 AIoT platforms market
360ยบ synopsis, 2018 - 2032
2.2 Business trends
2.2.1 Total Addressable
Market (TAM)
2.3 Regional trends
2.4 Component trends
2.5 Deployment trends
2.6 End-use trends
Chapter 3 AIot Platforms Market Industry
Insights
3.1 Impact on COVID-19
impact
3.2 Russia-Ukraine war
impact
3.3 Industry ecosystem
analysis
3.4 Deployment & innovation
landscape
3.5 Patent analysis
3.6 Key news and
initiatives
3.7 Regulatory landscape
3.8 Impact forces
3.8.1 Growth drivers
3.8.1.1 Rising adoption in
manufacturing industry
3.8.1.2 High efficiency of
AIoT platforms devices
3.8.1.3 AIoT industrial
hardware is growing smarter
3.8.1.4 Increased adoption
of AIoT platforms devices across sectors for real-time decision making
3.8.1.5 Growing
investments in IoT
3.8.1.6 Edge-Computing-Powered
Artificial Intelligence of Things
3.8.2 Industry pitfalls
& challenges
3.8.2.1 Shortage of
skilled workforce in companies requiring expertise in AIoT platforms
3.8.2.2 Complexities in
industry value chain
3.9 Profit margin
analysis
3.10 Vendor matrix
analysis
3.11 Growth potential
analysis
3.12 Porter’s analysis
3.13 PESTEL analysis
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