AI in IoT Market (By Component: Platform, Services, Software; By End-user: Banking, Financial Services, & Insurance, IT And Telecommunication, Energy & Utilities, Healthcare Sector, Manufacturing Industry) - Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2024-2033
The global AI in IoT market size was USD 82.24 billion in 2023, calculated at USD 87.51 billion in 2024 and is expected to reach around USD 153.08 billion by 2033, expanding at a CAGR of 6.41% from 2024 to 2033. Factors such as growth in digitalization and an increase in the adoption of advanced technologies positively impacted the growth of the AI in IoT market.
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The U.S. AI in IoT market size was exhibited at USD 19 billion in 2023 and is projected to be worth around USD 36.15 billion by 2033, poised to grow at a CAGR of 6.64% from 2024 to 2033.
North America dominated the global AI in IoT market in 2023. The growing investment in advanced technologies, including cloud-based services, AI, machine learning, business analytics solutions, and IoT, aims to enhance business operations and customer experience by driving the growth of the market.
The United States is poised to dominate the AI in IoT market in North America due to substantial investments, AI innovations, and advanced data collection technologies. Increased government spending on IoT and AI, along with the growing presence of AI in IoT vendors, is expected to propel market growth during the forecast period. Furthermore, the demand for 5G-enabled IoT connections is projected to increase.
Asia Pacific is anticipated to witness the fastest growth in the AI in IoT market over the studied period. The increased penetration of digitalization and higher adoption of advanced technology are anticipated to offer significant growth opportunities for the market in this region. Furthermore, as a major contributor to the global economy, China's economic landscape is evolving rapidly due to rising labor costs and the unsustainable traditional migrant worker model. These factors have driven the economy to integrate automation into its industrial processes.
AI has emerged as a powerful technology capable of replicating human intellectual functions. Similarly, IoT refers to a network of interconnected devices with unique IDs that communicate data across a network without human interaction. The integration of AI in IoT systems has enabled businesses to develop sophisticated machines that mimic human behavior and assist in decision-making with minimal human intervention.
The AI in IoT market is growing rapidly due to the increasing fusion of AI technologies with IoT systems. This combination allows smart devices and networks to collect, analyze, and act on vast amounts of data in real-time, improving automation, efficiency, and decision-making capabilities.
Report Coverage | Details |
Market Size by 2033 | USD 153.08 Billion |
Market Size in 2023 | USD 82.24 Billion |
Market Size in 2024 | USD 87.51 Billion |
Market Growth Rate from 2024 to 2033 | CAGR of 6.41% |
Largest Market | North America |
Base Year | 2023 |
Forecast Period | 2024 to 2033 |
Segments Covered | Component, End-user, and Regions |
Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Rising big data volume
The expansion of mobile traffic, cloud computing, and the adoption of the AI in IoT market has significantly increased the volume and complexity of data and fueled the growth of big data. Big data analytics provide valuable insights and actionable information from large datasets. Organizations can utilize predictive analytics for risk assessment, operations, marketing, and fraud detection. Therefore, data and analytics are becoming indispensable components for enterprises.
Cybersecurity issues
The proliferation of the AI in IoT market products and services expands the network's surface area, increasing the number of potential attack vectors. An IoT could exploit a single connected, unprotected device to launch an active attack on a network. Such attacks on critical infrastructure in industrial settings could result in significant losses and can hinder market growth. Furthermore, the shortage of skilled professionals in AI infrastructure and concerns regarding data privacy and security are anticipated to impede market expansion.
Advancements in edge computing
A significant opportunity in the AI in IoT market is the advancement of edge computing technologies. Edge computing processes data closer to its source, such as IoT devices, minimizing latency, reducing transmission costs, and decreasing reliance on centralized cloud services. By embedding AI capabilities directly into edge devices, real-time data processing and decision-making become faster and more reliable, which enables more autonomous IoT operations.
The software segment dominated the global AI in IoT market in 2023. The segment is further divided into sub-segments: remote monitoring, security, data management, network bandwidth management, real-time streaming analytics, and edge solutions. Among these, data management holds a significant market share. IoT data management is commonly used to predict wear and tear on connected assets and infrastructure. Moreover, Continuous innovation in this software segment ensures its crucial role within the AI in the IoT ecosystem, promising sustained growth and expansion in the coming years.
The platform segment is expected to grow at a significant rate in the AI in IoT market during the projected period. This can be attributed to the technological advancements that enabled AI in IoT platforms, transforming industries worldwide, including BFSI, manufacturing, and healthcare. These platforms facilitate developers in connecting, managing, and integrating data from IoT devices into various applications and services. They also aim to reduce development time and costs for IoT solutions by providing standard components for enterprises to build upon. These factors have contributed to the growth of platforms in AI in IoT market.
The manufacturing segment led the AI in IoT market in 2023. The manufacturing sector has increasingly utilized AI-powered IoT solutions to boost operational efficiency, enhance product quality, and minimize downtime. Companies are integrating AI with IoT to develop ‘smart factories’ where machinery and equipment communicate, predict failures, and self-optimize operations using real-time data. This integration has streamlined production processes by significantly reducing operational costs and contributed to the segment’s major market share.
The banking, financial services, & insurance segment is expected to grow at a significant rate in the AI in IoT market during the forecast period. In the banking, financial services, & insurance (BFSI) sector, IoT-enabled connected banking solutions help banks better serve their customers by utilizing data from various smart devices. This information allows customers to make informed financial decisions. Additionally, banks can offer value-added services, financial assistance, and personalized products using readily available customer data.
Segments Covered in the Report
By Component
By End-user
By Geography
Chapter 1. Introduction
1.1. Research Objective
1.2. Scope of the Study
1.3. Definition
Chapter 2. Research Methodology (Premium Insights)
2.1. Research Approach
2.2. Data Sources
2.3. Assumptions & Limitations
Chapter 3. Executive Summary
3.1. Market Snapshot
Chapter 4. Market Variables and Scope
4.1. Introduction
4.2. Market Classification and Scope
4.3. Industry Value Chain Analysis
4.3.1. Raw Material Procurement Analysis
4.3.2. Sales and Distribution Channel Analysis
4.3.3. Downstream Buyer Analysis
Chapter 5. COVID 19 Impact on AI in IoT Market
5.1. COVID-19 Landscape: AI in IoT Industry Impact
5.2. COVID 19 - Impact Assessment for the Industry
5.3. COVID 19 Impact: Global Major Government Policy
5.4. Market Trends and Opportunities in the COVID-19 Landscape
Chapter 6. Market Dynamics Analysis and Trends
6.1. Market Dynamics
6.1.1. Market Drivers
6.1.2. Market Restraints
6.1.3. Market Opportunities
6.2. Porter’s Five Forces Analysis
6.2.1. Bargaining power of suppliers
6.2.2. Bargaining power of buyers
6.2.3. Threat of substitute
6.2.4. Threat of new entrants
6.2.5. Degree of competition
Chapter 7. Competitive Landscape
7.1.1. Company Market Share/Positioning Analysis
7.1.2. Key Strategies Adopted by Players
7.1.3. Vendor Landscape
7.1.3.1. List of Suppliers
7.1.3.2. List of Buyers
Chapter 8. Global AI in IoT Market, By Component
8.1. AI in IoT Market, by Component, 2024-2033
8.1.1. Platform
8.1.1.1. Market Revenue and Forecast (2021-2033)
8.1.2. Services
8.1.2.1. Market Revenue and Forecast (2021-2033)
8.1.3. Software
8.1.3.1. Market Revenue and Forecast (2021-2033)
Chapter 9. Global AI in IoT Market, By End-user
9.1. AI in IoT Market, by End-user, 2024-2033
9.1.1. Banking, Financial Services, & Insurance
9.1.1.1. Market Revenue and Forecast (2021-2033)
9.1.2. IT And Telecommunication
9.1.2.1. Market Revenue and Forecast (2021-2033)
9.1.3. Energy & Utilities
9.1.3.1. Market Revenue and Forecast (2021-2033)
9.1.4. Healthcare Sector
9.1.4.1. Market Revenue and Forecast (2021-2033)
9.1.5. Manufacturing Industry
9.1.5.1. Market Revenue and Forecast (2021-2033)
Chapter 10. Global AI in IoT Market, Regional Estimates and Trend Forecast
10.1. North America
10.1.1. Market Revenue and Forecast, by Component (2021-2033)
10.1.2. Market Revenue and Forecast, by End-user (2021-2033)
10.1.3. U.S.
10.1.3.1. Market Revenue and Forecast, by Component (2021-2033)
10.1.3.2. Market Revenue and Forecast, by End-user (2021-2033)
10.1.4. Rest of North America
10.1.4.1. Market Revenue and Forecast, by Component (2021-2033)
10.1.4.2. Market Revenue and Forecast, by End-user (2021-2033)
10.2. Europe
10.2.1. Market Revenue and Forecast, by Component (2021-2033)
10.2.2. Market Revenue and Forecast, by End-user (2021-2033)
10.2.3. UK
10.2.3.1. Market Revenue and Forecast, by Component (2021-2033)
10.2.3.2. Market Revenue and Forecast, by End-user (2021-2033)
10.2.4. Germany
10.2.4.1. Market Revenue and Forecast, by Component (2021-2033)
10.2.4.2. Market Revenue and Forecast, by End-user (2021-2033)
10.2.5. France
10.2.5.1. Market Revenue and Forecast, by Component (2021-2033)
10.2.5.2. Market Revenue and Forecast, by End-user (2021-2033)
10.2.6. Rest of Europe
10.2.6.1. Market Revenue and Forecast, by Component (2021-2033)
10.2.6.2. Market Revenue and Forecast, by End-user (2021-2033)
10.3. APAC
10.3.1. Market Revenue and Forecast, by Component (2021-2033)
10.3.2. Market Revenue and Forecast, by End-user (2021-2033)
10.3.3. India
10.3.3.1. Market Revenue and Forecast, by Component (2021-2033)
10.3.3.2. Market Revenue and Forecast, by End-user (2021-2033)
10.3.4. China
10.3.4.1. Market Revenue and Forecast, by Component (2021-2033)
10.3.4.2. Market Revenue and Forecast, by End-user (2021-2033)
10.3.5. Japan
10.3.5.1. Market Revenue and Forecast, by Component (2021-2033)
10.3.5.2. Market Revenue and Forecast, by End-user (2021-2033)
10.3.6. Rest of APAC
10.3.6.1. Market Revenue and Forecast, by Component (2021-2033)
10.3.6.2. Market Revenue and Forecast, by End-user (2021-2033)
10.4. MEA
10.4.1. Market Revenue and Forecast, by Component (2021-2033)
10.4.2. Market Revenue and Forecast, by End-user (2021-2033)
10.4.3. GCC
10.4.3.1. Market Revenue and Forecast, by Component (2021-2033)
10.4.3.2. Market Revenue and Forecast, by End-user (2021-2033)
10.4.4. North Africa
10.4.4.1. Market Revenue and Forecast, by Component (2021-2033)
10.4.4.2. Market Revenue and Forecast, by End-user (2021-2033)
10.4.5. South Africa
10.4.5.1. Market Revenue and Forecast, by Component (2021-2033)
10.4.5.2. Market Revenue and Forecast, by End-user (2021-2033)
10.4.6. Rest of MEA
10.4.6.1. Market Revenue and Forecast, by Component (2021-2033)
10.4.6.2. Market Revenue and Forecast, by End-user (2021-2033)
10.5. Latin America
10.5.1. Market Revenue and Forecast, by Component (2021-2033)
10.5.2. Market Revenue and Forecast, by End-user (2021-2033)
10.5.3. Brazil
10.5.3.1. Market Revenue and Forecast, by Component (2021-2033)
10.5.3.2. Market Revenue and Forecast, by End-user (2021-2033)
10.5.4. Rest of LATAM
10.5.4.1. Market Revenue and Forecast, by Component (2021-2033)
10.5.4.2. Market Revenue and Forecast, by End-user (2021-2033)
Chapter 11. Company Profiles
11.1. Google LLC
11.1.1. Company Overview
11.1.2. Product Offerings
11.1.3. Financial Performance
11.1.4. Recent Initiatives
11.2. SAP SE
11.2.1. Company Overview
11.2.2. Product Offerings
11.2.3. Financial Performance
11.2.4. Recent Initiatives
11.3. PTC Inc.
11.3.1. Company Overview
11.3.2. Product Offerings
11.3.3. Financial Performance
11.3.4. Recent Initiatives
11.4. Salesforce, Inc.
11.4.1. Company Overview
11.4.2. Product Offerings
11.4.3. Financial Performance
11.4.4. Recent Initiatives
11.5. Hitachi Ltd.
11.5.1. Company Overview
11.5.2. Product Offerings
11.5.3. Financial Performance
11.5.4. Recent Initiatives
11.6. Softweb Solutions Inc.
11.6.1. Company Overview
11.6.2. Product Offerings
11.6.3. Financial Performance
11.6.4. Recent Initiatives
11.7. Amazon Web Services Inc.
11.7.1. Company Overview
11.7.2. Product Offerings
11.7.3. Financial Performance
11.7.4. Recent Initiatives
11.8. IBM Corporation
11.8.1. Company Overview
11.8.2. Product Offerings
11.8.3. Financial Performance
11.8.4. Recent Initiatives
11.9. SAS Institute Inc.
11.9.1. Company Overview
11.9.2. Product Offerings
11.9.3. Financial Performance
11.9.4. Recent Initiatives
11.10. Oracle Corporation
11.10.1. Company Overview
11.10.2. Product Offerings
11.10.3. Financial Performance
11.10.4. Recent Initiatives
Chapter 12. Research Methodology
12.1. Primary Research
12.2. Secondary Research
12.3. Assumptions
Chapter 13. Appendix
13.1. About Us
13.2. Glossary of Terms
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