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Global AIoT Platform Market to Reach USD 435.09 Billion by 2032

Global AIoT Platform Market Size Study, by Offering (Solution, Services), by Solution Type (Connectivity Management, Device Management, Application Management), by Industry Vertical (Manufacturing, BFSI, Healthcare, Retail, Energy and Utilities, Transportation and Logistics, Others), and Regional Forecasts 2022-2032

Product Code: ICTNGT-28535285
Publish Date: 28-10-2024
Page: 200

The global AIoT Platform market is valued at approximately USD 27.7 billion in 2023 and is anticipated to grow with a robust CAGR of around 35.8% over the forecast period 2024-2032. The AIoT (Artificial Intelligence of Things) platform combines the power of AI technologies with IoT infrastructure to create an intelligent system that significantly enhances data management, improves human-machine interactions, and streamlines IoT operations. This synergistic blend of AI and IoT is fostering a wave of innovation across various industries by enabling devices to communicate autonomously, optimize operations, and deliver real-time analytics.
A key driver for the growth of the AIoT Platform market is the surge in digitalization across industries, driven by the increasing adoption of IoT devices and advancements in AI technologies. These trends are reshaping sectors such as manufacturing, healthcare, and transportation by integrating intelligent systems that enhance efficiency, reduce costs, and improve decision-making processes. Moreover, the development of edge computing technologies, which allow real-time data processing and reduce latency, coupled with the scalability and flexibility offered by cloud computing, is further fueling the market expansion. Additionally, the integration of AIoT with blockchain technology enhances security and transparency, adding another layer of appeal to the adoption of AIoT platforms.
However, the market is not without challenges. Concerns surrounding data privacy and security, along with the lack of standardization in data formats and communication protocols, present significant obstacles. Moreover, the high cost of implementation and maintenance of AIoT solutions can deter small and medium-sized enterprises (SMEs) from adopting these technologies. Despite these challenges, the growing demand for automation, predictive maintenance, and the expansion of AIoT applications in emerging smart city initiatives and infrastructure projects are expected to create lucrative growth opportunities in the coming years.
The North American region held the largest market share in 2023, primarily due to the region’s significant investments in advanced technologies such as cloud computing, AI, machine learning, and IoT to enhance business operations and customer experiences. On the other hand, the Asia-Pacific region is poised for the highest growth during the forecast period, driven by increased digitalization, higher adoption of advanced technology, and the growing need for AIoT solutions across various industries.
Major market players included in this report are:
Tencent Cloud
Amazon Web Services Inc.
Microsoft Corporation
SAS Institute Inc.
SAP SE
Hewlett Packard Enterprise Development LP
Intel Corporation
Axiomtek Co., Ltd.
NXP Semiconductors
Google LLC
Sharp Corporation (SHARP)
Cisco Systems Inc.
International Business Machines Corporation (IBM)
Oracle Corporation
Williot

The detailed segments and sub-segment of the market are explained below:
By Offering
• Solution
• Services
By Solution Type
• Connectivity Management
• Device Management
• Application Management
By Industry Vertical
• Manufacturing
• BFSI
• Healthcare
• Retail
• Energy and Utilities
• Transportation and Logistics
• Others
By End User
• B2B
• B2G
• B2C
By Region:
North America
• U.S.
• Canada
Europe
• UK
• Germany
• France
• Spain
• Italy
• ROE
Asia Pacific
• China
• India
• Japan
• Australia
• South Korea
• RoAPAC
Latin America
• Brazil
• Mexico
• RoLA
Middle East & Africa
• Saudi Arabia
• South Africa
• RoMEA
Years considered for the study are as follows:
• Historical year – 2022
• Base year – 2023
• Forecast period – 2024 to 2032
Key Takeaways:
• Market Estimates & Forecast for 10 years from 2022 to 2032.
• Annualized revenues and regional level analysis for each market segment.
• Detailed analysis of geographical landscape with Country level analysis of major regions.
• Competitive landscape with information on major players in the market.
• Analysis of key business strategies and recommendations on future market approach.
• Analysis of competitive structure of the market.
• Demand side and supply side analysis of the market.

Chapter 1. Global AIoT Platform Market Executive Summary
1.1. Global AIoT Platform Market Size & Forecast (2022-2032)
1.2. Regional Summary
1.3. Segmental Summary
1.3.1. By Offering
1.3.2. By Solution Type
1.3.3. By Industry Vertical
1.4. Key Trends
1.5. Recession Impact
1.6. Analyst Recommendation & Conclusion

Chapter 2. Global AIoT Platform Market Definition and Research Assumptions
2.1. Research Objective
2.2. Market Definition
2.3. Research Assumptions
2.3.1. Inclusion & Exclusion
2.3.2. Limitations
2.3.3. Supply Side Analysis
2.3.3.1. Availability
2.3.3.2. Infrastructure
2.3.3.3. Regulatory Environment
2.3.3.4. Market Competition
2.3.3.5. Economic Viability (Consumer’s Perspective)
2.3.4. Demand Side Analysis
2.3.4.1. Regulatory frameworks
2.3.4.2. Technological Advancements
2.3.4.3. Environmental Considerations
2.3.4.4. Consumer Awareness & Acceptance
2.4. Estimation Methodology
2.5. Years Considered for the Study
2.6. Currency Conversion Rates

Chapter 3. Global AIoT Platform Market Dynamics
3.1. Market Drivers
3.1.1. Surge in Digitalization and IoT Adoption
3.1.2. Rise in Demand for Automation and Predictive Maintenance
3.1.3. Expansion of AIoT Applications Across Industries
3.2. Market Challenges
3.2.1. Data Privacy & Security Concerns
3.2.2. High Implementation and Maintenance Costs
3.3. Market Opportunities
3.3.1. Growth of Smart Cities and Infrastructure
3.3.2. Integration with Blockchain Technology
3.3.3. Emergence of 5G Networks

Chapter 4. Global AIoT Platform Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model
4.1.7. Porter’s 5 Force Impact Analysis
4.2. PESTEL Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.2.5. Environmental
4.2.6. Legal
4.3. Top Investment Opportunity
4.4. Top Winning Strategies
4.5. Disruptive Trends
4.6. Industry Expert Perspective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Global AIoT Platform Market Size & Forecasts by Offering 2022-2032
5.1. Segment Dashboard
5.2. Global AIoT Platform Market: Solution Revenue Trend Analysis, 2022 & 2032 (USD Billion)
5.2.1. Connectivity Management
5.2.2. Device Management
5.2.3. Application Management
5.3. Global AIoT Platform Market: Services Revenue Trend Analysis, 2022 & 2032 (USD Billion)

Chapter 6. Global AIoT Platform Market Size & Forecasts by Industry Vertical 2022-2032
6.1. Segment Dashboard
6.2. Global AIoT Platform Market: Industry Vertical Revenue Trend Analysis, 2022 & 2032 (USD Billion)
6.2.1. Manufacturing
6.2.2. BFSI
6.2.3. Healthcare
6.2.4. Retail
6.2.5. Energy and Utilities
6.2.6. Transportation and Logistics
6.2.7. Others

Chapter 7. Global AIoT Platform Market Size & Forecasts by Region 2022-2032
7.1. North America AIoT Platform Market
7.1.1. U.S. AIoT Platform Market
7.1.1.1. Offering Breakdown Size & Forecasts, 2022-2032 (USD Billion)
7.1.1.2. Industry Vertical Breakdown Size & Forecasts, 2022-2032 (USD Billion)
7.1.2. Canada AIoT Platform Market
7.2. Europe AIoT Platform Market
7.2.1. U.K. AIoT Platform Market
7.2.2. Germany AIoT Platform Market
7.2.3. France AIoT Platform Market
7.2.4. Spain AIoT Platform Market
7.2.5. Italy AIoT Platform Market
7.2.6. Rest of Europe AIoT Platform Market
7.3. Asia-Pacific AIoT Platform Market
7.3.1. China AIoT Platform Market
7.3.2. India AIoT Platform Market
7.3.3. Japan AIoT Platform Market
7.3.4. Australia AIoT Platform Market
7.3.5. South Korea AIoT Platform Market
7.3.6. Rest of Asia-Pacific AIoT Platform Market
7.4. Latin America AIoT Platform Market
7.4.1. Brazil AIoT Platform Market
7.4.2. Mexico AIoT Platform Market
7.4.3. Rest of Latin America AIoT Platform Market
7.5. Middle East & Africa AIoT Platform Market
7.5.1. Saudi Arabia AIoT Platform Market
7.5.2. South Africa AIoT Platform Market
7.5.3. Rest of Middle East & Africa AIoT Platform Market

Chapter 8. Competitive Intelligence
8.1. Key Company SWOT Analysis
8.1.1. Company 1
8.1.2. Company 2
8.1.3. Company 3
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. Tencent Cloud
8.3.1.1. Key Information
8.3.1.2. Overview
8.3.1.3. Financial (Subject to Data Availability)
8.3.1.4. Product Summary
8.3.1.5. Market Strategies
8.3.2. Amazon Web Services Inc.
8.3.3. Microsoft Corporation
8.3.4. SAS Institute Inc.
8.3.5. SAP SE
8.3.6. Hewlett Packard Enterprise Development LP
8.3.7. Intel Corporation
8.3.8. Axiomtek Co., Ltd.
8.3.9. NXP Semiconductors
8.3.10. Google LLC
8.3.11. Sharp Corporation (SHARP)
8.3.12. Cisco Systems Inc.
8.3.13. International Business Machines Corporation (IBM)
8.3.14. Oracle Corporation
8.3.15. Williot

Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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