Market Overview

The Global Mobile Artificial Intelligence (AI) Market is Forecast to Reach $17.83 Billion by 2023: Growing Demand for Edge Computing in IoT


The Global Mobile Artificial Intelligence (AI) Market is Forecast to Reach $17.83 Billion by 2023: Growing Demand for Edge Computing in IoT

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DUBLIN, Aug 8, 2018 /PRNewswire/ --

The "Mobile Artificial Intelligence (AI) Market by Application (Smartphones, Cameras, Drones, Automotive, AR/VR, Robotics, Smart Boards, and PCS), Technology Node (10nm, 20 to 28nm, 7nm and Others), and Geography - Global Forecast to 2023" report has been added to's offering.

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According to this report, the mobile AI market is expected to reach USD 17.83 billion by 2023 from USD 5.11 billion in 2018, at a CAGR of 28.41% during the forecast period.

The growth of this market can be attributed to the increasing demand for AI-capable processors for use in mobile devices, rise in cognitive computing, and growing number of AI applications. Factors such as premium pricing of AI processors and limited number of AI experts are restraining market growth.

This report covers the mobile AI market by application, technology node, and geography.

Among all applications, smartphones are expected to hold the largest size of the market throughout the forecast period. Growing requirement for higher security, low latency, faster computing, and less reliance on connectivity is boosting the adoption of devices with dedicated AI chips. On-device AI uses dedicated AI chipsets, which are likely to become prominent in all flagship smartphones in the near future. It is expected that the use of dedicated AI chips in smartphones will increase substantially by 2023, and these chips will be available in most smartphones sold in the coming years.

The mobile AI market for AR/VR applications is expected to grow at the highest rate between 2018 and 2023. Large tech companies such as Qualcomm (US), Google, Microsoft (US), and Apple (US) have shown their interests in contributing to the growth of augmented technology by adopting strategies such as product launches, acquisitions, or funding.

AR and VR, coupled with AI, will provide smarter, more relevant, and personalized experience. For instance, in July 2017, Microsoft announced the next generation of its mixed reality HoloLens headset HoloLens 2 which will have a dedicated AI coprocessor known as the Holographic Processing Unit (HPU). Qualcomm, in February 2018, announced its Snapdragon 845 VR headset reference design to fuel next-generation VR experience.

In terms of technology node, the mobile AI market for 20-28nm is expected to grow at a high rate between 2018 and 2023. The market for drones, robotics, and surveillance cameras wherein vision processing units are used is likely to grow at a significant rate in the near future. Processors such as VPU Jetson and S32V234 are built upon 20-28nm technology nodes. These processors are used in an array of applications, including ADAS, drones, robotics, security cameras, and AR/VR headsets.

The mobile AI market in APAC is expected to grow at the highest CAGR during the forecast period. The region is becoming the center of attraction for major investments as it holds significant business expansion opportunities.

Various AI processor start-ups in China are raising funds to grow in the market. For example, ThinkForce (China) raised around USD 68 million, and DeePhi (China) raised around USD 40 million. Along with this, increasing government spending to boost the AI network in China is expected to further contribute to market growth during the forecast period.

Major players in the mobile AI market are Apple (US), NVIDIA (US), Huawei (China), Samsung Electronics (South Korea), Qualcomm (US), Intel (US), IBM (US), Microsoft (US), MediaTek (Taiwan), and Google (US).

Key Topics Covered

1 Introduction

1.1 Study Objectives
1.2 Definition
1.3 Study Scope
1.3.1 Markets Covered
1.3.2 Geographic Scope
1.3.3 Years Considered for the Study
1.4 Currency
1.5 Package Size
1.6 Limitations
1.7 Stakeholders

2 Research Methodology

2.1 Research Data
2.1.1 Secondary Data Secondary Sources
2.1.2 Primary Data Primary Sources Key Industry Insights Breakdown of Primaries
2.2 Market Size Estimation
2.2.1 Bottom-Up Approach
2.2.2 Top-Down Approach
2.3 Market Breakdown and Data Triangulation
2.4 Research Assumptions

3 Executive Summary

4 Premium Insights

4.1 Attractive Opportunities in Mobile AI Market
4.2 Mobile AI Market, By Technology Node (Million Units)
4.3 Market, By Application (Million Units)
4.4 Market in APAC, By Application and Country (Million Units)
4.5 Market, By Region (Million Units)

5 Market Overview

5.1 Market Dynamics
5.1.1 Drivers Growing Demand for AI-Capable Processors in Mobile Devices Rise of Cognitive Computing Growing Number of AI Applications
5.1.2 Restraints Premium Pricing of AI Processors Limited Number of AI Experts
5.1.3 Opportunities Dedicated Low-Cost AI Chips for Camera and Vision Applications in Mobile Devices Growing Demand for Edge Computing in IoT
5.1.4 Challenges Unreliability of AI Algorithms in Mobile Apps Creating Models and Mechanisms of AI

6 Mobile AI Market, By Application

6.1 Introduction
6.2 Smartphones
6.3 Cameras
6.4 Drones
6.5 Robotics
6.6 Automotive
6.7 AR/VR
6.8 Others

7 Mobile AI Market, By Technology Node

7.1 Introduction
7.2 20-28nm
7.3 10nm
7.4 7nm and Others

8 Mobile AI Market, By Region

8.1 Introduction
8.2 North America
8.2.1 US
8.2.2 Canada
8.2.3 Mexico
8.3 Europe
8.3.1 Germany
8.3.2 UK
8.3.3 France
8.3.4 Italy
8.3.5 Rest of Europe (RoE)
8.4 Asia Pacific (APAC)
8.4.1 China
8.4.2 Japan
8.4.3 South Korea
8.4.4 Rest of APAC
8.5 Rest of the World (RoW)
8.5.1 Middle East & Africa (MEA)
8.5.2 South America

9 Competitive Landscape

9.1 Overview
9.2 Ranking Analysis
9.3 Competitive Situations and Trends
9.3.1 Product Launches and Developments
9.3.2 Agreements, Partnerships, Collaborations, and Contracts
9.3.3 Mergers & Acquisitions

10 Company Profiles

10.1 Key Players
10.1.1 Nvidia
10.1.2 Intel
10.1.3 Microsoft
10.1.4 IBM
10.1.5 Qualcomm
10.1.6 Apple
10.1.7 Huawei (Hisilicon)
10.1.8 Alphabet (Google)
10.1.9 Samsung
10.1.10 Mediatek
10.2 Other Companies
10.2.1 Graphcore
10.2.2 Cerebras Systems
10.2.3 Cambricon Technology
10.2.4 Deephi Tech
10.2.5 Shanghai Thinkforce Electronic Technology Co. Ltd. (Thinkforce)
10.2.6 Sambanova Systems
10.2.7 Rockchip (Fuzhou Rockchip Electronics Co. Ltd.)
10.2.8 Thinci
10.2.9 Kneron

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