Deep Learning Market to Reach $179.96 Bn, Globally, by 2030 at 39.2% CAGR: Allied Market Research
Increase in computing power, decline in hardware costs, adoption of cloud-based technology, and usage in big data analytics drive the growth of the global deep learning market.
PORTLAND, Ore., Jan. 18, 2022 /PRNewswire/ -- Allied Market Research published a report, titled, "Deep Learning Market by Component (Hardware, Software and Service), by Application (Image Recognition, Signal Recognition, Data Mining, and Others) and by Industry Vertical (Security, Marketing, Automotive, Retail & E-Commerce, Healthcare, Manufacturing, Law, and Others): Global Opportunity Analysis and Industry Forecast, 2021–2030." According to the report, the global deep learning industry generated $6.85 billion in 2020, and is expected to reach $179.96 billion by 2030, witnessing a CAGR of 39.2% from 2021 to 2030.
Drivers, Restraints, and Opportunities
Increase in computing power, decline in hardware costs, adoption of cloud-based technology, and usage in big data analytics drive the growth of the global deep learning market. However, surge in complexity in hardware due to complex algorithm, lack of technical expertise, and absence of standards and protocols hinders the market growth. On the other hand, cumulative spending in the healthcare, travel, tourism, and hospitality industries present new opportunities in the coming years.
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The software segment to continue its lead position during the forecast period
Based on component, the software segment contributed to the highest share in 2020, accounting for nearly half of the global deep learning market, and is expected to continue its lead position during the forecast period. This isdue to increase in demand for deep learning software across various organizations such as healthcare and BFSI and surge in need of software among organizations for production planning and predictive maintenance. However, the service segment is estimated to manifest the highest CAGR of 40.7% from 2021 to 2030, owing to rise in demand for software-as-a-service (SaaS) with its numerous benefits such as scalability and one-time customer acquisition cost.
The security segment to continue its leadership status during the forecast period
Based on industry vertical, the security segment accounted for the highest share in 2020, contributing to nearly one-fifth of the global deep learning market, and is expected to continue its leadership status during the forecast period. This is due to identification of more advanced malware & threats and detection of unusual activities that may signal existence of rogue actors. However, the healthcare segment is estimated to witness the largest CAGR of 42.0% from 2021 to 2030. This is attributed to empowerment of the sector with its advanced & vast library of specialized algorithms and lightening computational power.
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North America to maintain its dominant share in terms of revenue by 2030
Based on region, North America held the highest market share in 2020, contributing to nearly two-fifths of the global deep learning industry, and is expected to maintain its dominant share in terms of revenue by 2030. This is due to increase in investments in deep learning start-ups and surge in popularity of deep learning technology among end users. However, Asia-Pacific is projected to portray the highest CAGR of 40.9% during the forecast period. This is due to increased utilization of deep learning algorithms with rise in digitalization in healthcare, telecommunication, automotive, and banking, financial services and insurance (BFSI) sectors.
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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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