AI in IoT Market Outlook

The AI in IoT market is expected to expand its roots at a steady CAGR of 6.4% during the forecast period. The market is likely to hold a revenue of USD 82.1 billion in 2023 while it is anticipated to cross a value of USD 153.1 billion by 2033.

With the increasing demand for tracking of assets and performance management appliances by both transportation and connected devices, the market for dedicated services is expected to flourish. In addition, the increasing global operators of mobile network services for increasing connectivity platforms are also driving the market upward.

The advancements in artificial intelligence, coupled with ubiquitous network access, and real-time data exchange, are accelerating IoT deployments. To an unprecedented level of efficiency, which may boost the market value of IoT products in the coming decade.

Artificial Intelligence has proved to be an effective instrument in the collection of big data. This platform provides the foundation and tools necessary to automate and implement real-time decisions in IoT-related applications. For IoT devices to reach their full potential, substantial investment in new technology may have to be made to make full use of them.

Attributes Details
AI in IoT Market CAGR (2023 to 2033) 6.4%
AI in IoT Market Size (2023) USD 82.1 billion
AI in IoT Market Size (2033) USD 153.1 billion

In combining AI in conjunction with the Internet of Things, new possibilities can be created that may change the face and structure of industries, businesses, and economies. Through the IoT, artificial intelligence provides intelligent technologies for mimicking intelligent behavior and helping make decisions without human intervention.

During pandemic, the pharmaceutical companies have been exponentially increasing the use of AI to track spread of the virus and develop vaccines. The companies must access cost-effective, consistent, and highly secure computing power to support medical work, students academic research, and maintain the productivity of remote employees. All of these are key factors are driving the market growth during the period.

Due to an increase in manufacturing activity in 2021 and the rise in the adoption of autonomous vehicles in the automation market, the demand for AI in IoT components increased.

A novel coronavirus has further demonstrated the importance of businesses being able to cope with digital disruption. Companies starting to look for technologies that make them more sustainable and able to adapt to new technologies. Moreover, AI and automation adoption may continue to grow at an exponential rate.

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How is the AI in IoT Market evolving in the Current Technological Market?

The growing IoT market has exponentially formed demand for managing and securing data generated from the smart devices. The AI integrated IoT technology enables the devices to record and track insights and offer a real-time visibility thereby enhancing customer experience. With decreasing delivery time and low latency, along with real-time tracking of the products, the market is likely to experience considerable growth in the forecast period.

In the retail sector, cloud AI is being used mainly for enhancing the customer experience of their programs and creating IoT-based products that focus on customers. A new generation of legacy vendors offer software to gain a stronghold throughout the value chain. This has formed as a result of intense competition in industrial IoT and market maturation.

Recently their has been a growing demand among the manufacturers to deploy computer based 100% automated data management system (DMS). As part of an AI-enabled IoT application for manufacturing, IoT-enabled applications can also be used to effectively monitor and optimize the performance of equipment, produce quality control, and collaborate between machines and humans.

Manufacturing and supply chain operations that are faster and more efficient can significantly reduce the time required for a product to reach its market.

As a result of the rising demand for advanced artificial intelligence applications in the BFSI sector, IoT may grow to become a more secure way to conduct business transactions and help to close data breaches. The development of technological and scientific advancement in IoT and the development of artificial intelligence in automation devices may ensure the market may thrive and develop further.

What are the Technological Challenges in the AI in IoT Market?

Edge chips are facing the challenge of power consumption and size constraints in automotive and consumer electronics. As there is a rising demand for real-time, low-latency response edge AI in these markets. With its SoC, the company hopes to resolve this issue with a computing platform that uses less power and is compact while delivering sufficient computing power for biometrics and AI.

The high cost of artificial intelligence and the lack of knowledge among consumers may slow its growth in the IoT sector. The growing concerns about privacy and security of personal data are one of the key factors leading to the decline of this market.

This artificial intelligence is expected to produce unmemorable results where this technology may result in mundane jobs for low-income-level people. All of these factors contribute to a decline in the market.

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Which Component Segment is Stimulating Market Growth for AI in IoT Market?

Platforms account for a leading market share of AI in IoT, with a CAGR of 5.7% during the forecast period. AI capabilities, such as machine learning-based analytics, are increasingly being incorporated with IoT platforms and solution vendors' solutions. To tap into the massive amount of data generated by IoT devices. As enterprises across numerous vertical industry segments integrate IoT solutions with AI capabilities.

They are becoming nimble while reducing reaction time and relying less on traditional tools for analysis of IoT data, and depending more on advanced technological solutions. Additionally, these solutions improve human-machine interactions by enhancing operational prediction accuracy and agility.

Platforms were created to enable developers to connect, manage, and integrate data collected from IoT devices into various applications and services. Platforms like these are designed to reduce the development time and cost of IoT solutions by setting up standard components upon which enterprises can build. These factors have contributed to the market growth of platforms in the IoT market.

Country-wise Insights

Countries Revenue Share % (2023)
United States 19.4%
Germany 9.4%
Japan 6.8%
Australia 2.8%
North America 29.4%
Europe 22.9%
Countries CAGR % (2023 to 2033)
China 7.1%
India 6.8%
United Kingdom 5.5%

Which Regions are Contributing to the Growth of AI in IoT?

North America is anticipated to hold the largest market for AI in IoT market. The market for artificial intelligence in IoT in the United States is expected to account for a 5.8% CAGR during the forecast period. By 2032, the market is expected to be worth USD 49 billion in the future years.

Businesses in North America are adopting the AI technology thereby propelling the demand for te market. This growing adoption of technology along wiith cloud services is mainly owing to the presence of key players operating in the region. Increased investments for developing new technologies have significantly contributed to the growth of this sector.

Asia Pacific is anticipated to dominate the AI in IoT market during the forecast period. In the upcoming years, the market is anticipated to increase significantly due to the continued investments and growth of the IT business in China. In China, the company is anticipated to grow at a 5.6% CAGR throughout the forecast period.

As a result of the growth of Internet penetration, advances in technology, the proliferation of mobile devices, and networking infrastructure. As well as the influx of consumers utilizing technologically advanced and connected devices. All are factors contributing to the development of the market in this region. Increasing industrial automation in the region is also driving the demand for artificial intelligence in IoTs in China .

According to the forecast, Japan may reach a CAGR of 5.2% in 2032. Increasing industrial production and the expansion of mobile technologies are expected to boost market demand for AI in IoT in this region. Market value in South Korea is expected to reach USD 5.3 billion during the forecast period. A CAGR of 5% is predicted for the market during the forecast period.

As a result of the growing revolution in the consumer shopping experience and the implementation of smart building infrastructures, AI in IoT has become an integral part of the growing IoT market in this region. Besides boosting the economy, this region is focusing on digitization post-Covid-19 by using AI and 5G networks.

During the forecast period, the artificial intelligence market for IoT in the United Kingdom is expected to thrive at a CAGR of 4.6% during the period. Because of the emergence of IoT and Machine-to-Machine technologies, AI in IoTs is expected to see a high degree of growth in this region. With the increasing demand to increase research and industrial capacity in this region, the market demand for AI in IoT is growing.

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Category-wise Landscape

Category By Component
Leading Segment Platform
Market Share (2022) 47.3%
Category By Technologies
Leading Segment ML and Deep Learning
Market Share (2022) 79.4%

How Deep Learning and Machine Learning are Driving the Growth of AI in IoT markets?

Machine learning holds a substantial market share in the AI in IoT segment. The market is anticipated to record a CAGR of 5.7% during the forecast period. With massive data volumes, machine learning is becoming a powerful tool for data analysis. In conjunction with ML and edge computing, IoT devices can filter out most background noise and allow cloud analytics engines and edge devices to analyze the relevant data.

AI is part of the overall value of the Internet of Things, as analytics plays a key role in increasing the overall benefit of IoT. By adopting deep learning and machine learning and AI, companies can use behavioral insights. To predict the demands of their customers and networks and automatically alert them to potential problems, and customize their products.

Targeting the sensors to capture certain things, deep learning, and machine learning tools may help fuse the layers to share reports in real time with the authorities. Thus, deep learning and machine learning are gaining popularity in the market.

Competition Scenario

Through strategic partnerships, manufacturers can increase production and meet consumer demand, increasing both their revenues and market share. The introduction of new products and technologies may allow end-users to reap the benefits of new technologies. Increasing the company's production capacity is one of the potential benefits of a strategic partnership.

Market Developments:

  • Google Cloud announced the release of Vertex AI, a managed machine learning (ML) platform designed to help enterprises deploy and maintain AI and IoT models. It usually takes less than 80% less code for Vertex AI to train a model than other competitive platforms. ML engineers and data scientists at all levels of expertise can build, manage and maintain ML and IoT projects at all stages of development using Machine Learning Operations (MLOps).
  • Bosch launched an IoT platform Phantom Edge, that allows manufacturers to get real-time data on their power consumption. With Phantom Edge, manufacturers get real-time alerts and notifications for actionable insights. In addition to automating data capture and ensuring accurate downtimes, this software also provides managers with timely. Bias-free, and precise data so that they can set targets, monitor performance, gain insights, and constantly improve in the market.
  • In January 2022, Johnson Controls completed the acquisition of FogHorn. A company that provides edge AI software to industrial and commercial IoT applications. Johnson Controls announced that it has acquired Foghorn's Edge Artificial Intelligence for its OpenBlue smart building platform. In addressing the pressing issues of sustainability, indoor air quality, energy efficiency, and smart, secure buildings. Edge AI brings intelligence to the source of data on-site, providing effective, real-time solutions to buildings.
  • In April 2022, Synaptic launched its edge AI evaluation kit (EVK) which utilizes the capabilities of its Katana system-on-a-chip (SoC) by building a human recognition, sound, and motion detection system for improving biometrics and other AI applications at the edge of the networks. Within this technology, the company is addressing different problems such as power consumption and size constraints for edge semiconductors.
  • In April 2022, Gupshup acquired Active.Ai, a startup that provides conversational AI to fintech firms and banks in all-cash transactions. The acquisition may enable Gupshup to offer better customer experience solutions for the BFSI market.

Key Segments Covered

By Components:

  • Platform
  • Software Solutions
  • Services
    • Professional Services
      • Deployment and Integration
      • Support and Maintenance
      • Training and Consulting
    • Managed Services

By Technologies:

  • ML and Deep Learning
  • NLP

By Verticals:

  • Manufacturing
  • Energy and Utilities
  • Transportation and Mobility
  • BFSI
  • Government and Defense
  • Retail
  • Healthcare and Life Sciences
  • Telecom
  • Others(agriculture, education, telecom, and tourism and hospitality)

By Key Regions Covered:

  • North America
    • United States
    • Canada
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America
  • Europe
    • Germany
    • United Kingdom
    • France
    • Spain
    • Russia
    • Rest of Europe
  • Japan
  • Asia Pacific Excluding Japan
    • China
    • India
    • Malaysia
    • Singapore
    • Australia
    • Rest of Asia Pacific Excluding Japan (APEJ)
  • The Middle East and Africa
    • GCC Countries
    • Israel
    • South Africa
    • The Middle East and Africa (MEA)

Frequently Asked Questions

Where is the higher demand for AI in IoT?

The Asia-Pacific region generated the highest demand for AI in IoT in 2023.

Which regional market will witness higher growth in AI in the IoT market?

The Asia-Pacific market is expected to grow at the highest CAGR of 7.1% through 2033.

Which is the preferred material for making AI in IoT?

The semiconductor material segment is the preferred material for making AI in IoT.

Which product type is in higher demand for AI in IoT Market?

The embedded AI segment is in the highest demand for AI in the IoT market.

How the AI in IoT market Value in 2024?

The global AI in IoT market exhibited a Market Value of USD 89 billion in 2024.

Table of Content
	1. Executive Summary
	2. Market Overview
	3. Market Background
	4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033
	5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Components
		5.1. Platform
		5.2. Software Solutions
		5.3. Services
			5.3.1. Deployment and Integration
			5.3.2. Support and Maintenance
			5.3.3. Training and Consulting
			5.3.4. Managed Services
	6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Technologies
		6.1. ML and Deep Learning
		6.2. NLP
	7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Verticals
		7.1. Manufacturing
		7.2. Energy and Utilities
		7.3. Transportation and Mobility
		7.4. BFSI
		7.5. Government and Defense
		7.6. Retail
		7.7. Healthcare and Life Sciences
		7.8. Telecom
		7.9. Others
	8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region
		8.1. North America
		8.2. Latin America
		8.3. Europe
		8.4. South Asia
		8.5. East Asia
		8.6. Oceania
		8.7. MEA
	9. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	10. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	11. Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	12. South Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	13. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	14. Oceania Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	15. MEA Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country
	16. Key Countries Market Analysis
	17. Market Structure Analysis
	18. Competition Analysis
		18.1. Google
		18.2. Microsoft
		18.3. IBM
		18.4. AWS
		18.5. Oracle
		18.6. SAP
		18.7. PTC
		18.8. GE
		18.9. Salesforce
		18.10. Hitachi
		18.11. Uptake
		18.12. SAS
		18.13. Autoplant Systems Pvt Ltd
		18.14. Kairos
		18.15. Softweb Solutions
		18.16. Arundo
		18.17. C3 IoT
		18.18. Anagog
		18.19. Imagimob
		18.20. Thingstel
	19. Assumptions & Acronyms Used
	20. Research Methodology
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