Deep Learning Market Share Growing Rapidly with Recent Trends and Outlook By 2030

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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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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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 is due 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.

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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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Covid-19 Scenario

  • During the Covid-19 pandemic, the demand for deep learning witnessed a significant rise for implementation of digital voice assistance by businesses to help their customers. In addition, rise in focus on virtual reality and augmented technologies by various key market players of different countries led to increased adoption of deep learning algorithms.
  • The deep learning market experienced the growth during the pandemic, due to rise in demand for anti-money laundering (AML), fraud detection solutions, and other solutions to prevent frauds related to money.
  • Deep learning methods have been used to track the spread of coronavirus and take preventive measures and implement regulations to tackle the spread.

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