Global Mobile Artificial Intelligence (AI) Market Sales to Hit $84.80 Billion By 2030

High demand for artificial intelligence in smartphones, rise in demand for AI-capable processors, and increase in investment in AI technologies drive the growth of the global mobile artificial intelligence (AI) market. However, high pricing of artificial processors hinders the market growth. On the other hand, the emergence of edge computing presents new opportunities in the coming years.

According to the report published by Allied Market Research, the global mobile artificial intelligence (AI) market generated $8.56 billion in 2020, and is expected to reach $84.80 billion by 2030, witnessing a CAGR of 26.44% from 2021 to 2030. The report offers a detailed analysis of changing market trends, top segments, key investment pockets, value chain, regional landscape, and competitive scenario.

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Covid-19 Scenario:

Sudden slowdown of product development activities due to lockdown measures and lack of sufficient workforce impacted the production of smartphones, robots, camera, and drones. This led to reduced demand for mobile AI during the pandemic.
In addition, manufacturing activities in the automotive sector have been stopped partially or completely during the lockdown. This also reduced the demand for mobile AI. However, the demand is expected to rise during the post-lockdown as production volumes get back on track.
Reduction in demand for mobile devices and other electronics devices during the pandemic affected the market for mobile artificial intelligence (AI) up to an extent.

The report offers detailed segmentation of the global mobile artificial intelligence (AI) market based on technology node, component, application, and region.

Based on component, the hardware segment held the largest market share in 2020, accounting for nearly two-thirds of the total share, and is estimated to continue its lead position during the forecast period. However, the software segment is projected to register the highest CAGR of 29.4% from 2021 to 2030.

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Based on application, the smartphones segment accounted for the highest share in 2020, contributing to nearly two-fifths of the global mobile artificial intelligence (AI) market, and is projected to maintain its dominance during the forecast period. However, the robotics segment is estimated to manifest the fastest CAGR of 30.6% from 2021 to 2030.

Based on region, North America contributed to the largest share in 2020, accounting for nearly two-fifths of the total market share, and is expected to maintain its leadership status by 2030. However, Asia-Pacific is estimated to portray the highest CAGR of 27.7% during the forecast period.

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Leading players of the global mobile artificial intelligence (AI) market analyzed in the research include NVIDIA Corporation (U.S.), Microsoft Corporation (U.S.), Intel Corporation (U.S.), Qualcomm Inc. (U.S.), IBM Corporation (U.S.), Google (U.S.), Apple Inc. (U.S.), MediaTek Inc. (Taiwan), Samsung Electronics (South Korea), and Huawei Technologies (China).

About Us:

Allied Market Research (AMR) is a full-service market research and business-consulting wing of Allied Analytics LLP based in Portland, Oregon. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of “Market Research Reports” and “Business Intelligence Solutions.” AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.

Pawan Kumar, the CEO of Allied Market Research, is leading the organization toward providing high-quality data and insights. We are in professional corporate relations with various companies and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.

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