Deep Learning Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

the Report Covers Global Deep Learning Market Growth and is Segmented by Offering Type (Hardware, Software, and Services), End-User Industry (BFSI, Retail, Manufacturing, Healthcare, Automotive, Telecom, and Media), Application (Image Recognition, Signal Recognition, Data Processing), and Geography (North America, Europe, Asia Pacific, Latin America, and Middle East and Africa). the Market Size and Forecasts are Provided in Terms of Value (USD) for all the Above Segments.

Deep Learning Market Size & Share Analysis - Growth Trends & Forecasts (2025 - 2030)

Deep Learning Market Size

Deep Learning Market Summary
Study Period 2019 - 2030
Market Size (2025) USD 34.89 Billion
Market Size (2030) USD 195.16 Billion
CAGR (2025 - 2030) 41.10 %
Fastest Growing Market Asia Pacific
Largest Market North America
Market Concentration Low

Major Players

Deep Learning Market Major Players

*Disclaimer: Major Players sorted in no particular order

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Deep Learning Market Analysis

The Deep Learning Market size is estimated at USD 34.89 billion in 2025, and is expected to reach USD 195.16 billion by 2030, at a CAGR of 41.1% during the forecast period (2025-2030).

Deep learning, a subfield of machine learning (ML), led to breakthroughs in several artificial intelligence tasks, including speech recognition and image recognition. Furthermore, the ability to automate predictive analytics is leading to the hype for ML. Factors such as enhanced support in product development and improvement, process optimization and functional workflows, and sales optimization, among others, have been driving enterprises across industries to invest in deep learning applications. Furthermore, the latest machine-learning approaches have significantly improved the accuracy of models, and new classes of neural networks have been developed for applications like image classification and text translation.

  •  Technological advances, such as increasing data center capacity, high computing power and the ability to carry out tasks without human input, have attracted significant attention. In addition, the growth of the deep learning industry is fueled by rapidly adopting cloud computing technology across a number of sectors.
  • Several developments are now advancing deep learning. According to SAS, improvements in algorithms have boosted the performance of deep learning methods. The increasing amount of data volumes has been supportive of the building of neural networks with several deep layers, including streaming data from the Internet of Things (IoT) and textual data from social media and physicians' notes. A significant amount of computational power is essential to solve deep learning problems, considering the iterative nature of deep learning algorithms-their complexity increases as the number of layers increases. The hardware running deep learning algorithms also needs to support the large volumes of data required to train the networks.
  • Computational advances in graphic processing units (GPUs) and distributed cloud computing have put incredible computing power at the users' disposal. This development is led by hardware providers, such as NVIDIA, Intel, and AMD, among others, which have been improving the computational speeds among other features and making them compatible with most-used open-source platforms, such as Tensorflow, Cognitive Toolkit (Microsoft), Chainer, Caffe, and PyTorch, among others. Therefore, 'open-sourcing deep learning capabilities' have become increasingly popular across enterprises. These open-source frameworks enable users to build machine-learning models efficiently and quickly.
  • Deep learning has a number of serious limitations that need to be overcome before it can achieve its full potential, such as the black box problem, overpopulation, lack of contextual understanding, data requirements and computational intensity, which might effect market
  •  As a result, COVID-19 has had an excellent impact for the technology sector. Deep learning algorithms have been employed for assisting diagnosis and detection of COVIDE-19 cases based on clinical images, e.g. chest Xray or CT scans. The growing demand for MRI analysis tools within the healthcare sector which has led to a rise in the depth learning market.

Deep Learning Industry Overview

The deep learning market is fragmented as it consists of several large players, such as IBM, Google, and Microsoft, among others, with substantial industrial experience in big data/analytical platforms. Other new entrants also have been making their way into the market and have been successfully increasing the number of use cases of deep learning across industries. Prominent new entrants that have made a significant impact on the market include H2O.ai, KNIME, and Dataiku.

In November 2023 - In a step towards advancing the realm of machine learning (ML) technologies and artificial intelligence (AI) within the telecommunications industry, Telenor and Ericsson have signed an (MoU) for a three-year collaboration that aims to explore, develop, and test advanced AI/ML solutions towards enhancing energy efficiency without compromising on the quality of connectivity in mobile networks.

In October 2022, Zendesk Inc. announced the launch of a new AI solution, Intelligent Triage and Smart Assist, empowering businesses to triage customer support requests automatically and access valuable data at scale.

In September 2022, Altair, a company providing computational science and artificial intelligence, announced the acquisition of rapid miner, a leader in advanced data analytics and machine learning (ML) software. With this acquisition, Altair's looking forward to strengthening its end-to-end data analytics (DA) portfolio.

Deep Learning Market Leaders

  1. Facebook Inc.

  2. Google LLC

  3. Microsoft Corporation

  4. IBM Corporation

  5. Amazon Web Services Inc.

  6. *Disclaimer: Major Players sorted in no particular order
Deep Learning Market Concentration
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Deep Learning Market News

  • September 2023: Amazon and Anthropic announced a strategic partnership that would bring together their respective technology and expertise in safer generative artificial intelligence (AI) to accelerate the development of Anthropic’s future foundation models and make them widely accessible to AWS consumers.
  • May 2022: Intel launched its second-generation Habana AI deep learning processors in order to deliver high efficiency and high performance. The launch of Habana's new deep learning processors is a key example of Intel executing on its AI strategy to give customers a wide array of solution choices from cloud to the edge, addressing the growing number and complex nature of AI workloads.
  • August 2022: Amazon launched a new Machine Learning (ML) software through which medical records of patients can be analyzed for better treatment of patients and reduce overall expenses.

Deep Learning Market Report - Table of Contents

1. INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Industry Stakeholder Analysis
  • 4.4 Assessment of Impact of COVID-19 on Deep Learning Market

5. MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Computing Power, coupled with the Presence of Large Unstructured Data
    • 5.1.2 Ongoing Efforts toward the Integration of DL in Consumer-based Solutions
    • 5.1.3 Growing Use of Deep Learning in Retail Sector is Driving the Market
  • 5.2 Market Challenges
    • 5.2.1 Operational and Infrastructural Concerns, such as Hardware Complexity and Need for Skilled Workforce
  • 5.3 Market Opportunities
  • 5.4 Technology Evolution of Deep Learning
  • 5.5 Analysis of Key Machine Learning Libraries

6. MARKET SEGMENTATION

  • 6.1 Offering
    • 6.1.1 Hardware
    • 6.1.2 Software and Services
  • 6.2 End-User Industry
    • 6.2.1 BFSI
    • 6.2.2 Retail
    • 6.2.3 Manufacturing
    • 6.2.4 Healthcare
    • 6.2.5 Automotive
    • 6.2.6 Telecom and Media
    • 6.2.7 Other End-user Industries
  • 6.3 Application
    • 6.3.1 Image Recognition
    • 6.3.2 Signal Recognition
    • 6.3.3 Data Processing
    • 6.3.4 Other Applications
  • 6.4 Geography
    • 6.4.1 North America
    • 6.4.2 Europe
    • 6.4.3 Asia-Pacific
    • 6.4.4 Rest of the World

7. COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Facebook Inc.
    • 7.1.2 Google
    • 7.1.3 Amazon Web Services Inc
    • 7.1.4 SAS Institute Inc
    • 7.1.5 Microsoft Corporation
    • 7.1.6 IBM Corp
    • 7.1.7 Advanced Micro Devices Inc
    • 7.1.8 Intel Corp
    • 7.1.9 NVIDIA Corp
    • 7.1.10 Rapidminer Inc
  • *List Not Exhaustive

8. INVESTMENT ANALYSIS

9. FUTURE OF THE MARKET

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Deep Learning Industry Segmentation

 The method for AI which teaches computers to handle data as if inspired by the brains of humans is called "Deep Learning".The study covers the revenues from hardware, software, and services driven by deep learning. The hardware segment includes the demand study for central processing units (CPUs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), graphics processing units (GPUs), networking products, and data storage devices. Cloud-based platforms for deep learning applications, such as image recognition, signal recognition, and data processing, are also covered in the study. Other Applications will include natural language processing, speech recognition, product recommendations, and predictive maintenance.

Deep learning market is segmented by offering type (hardware, software, and services), end-user industry (BFSI, retail, manufacturing, healthcare, automotive, telecom, and media), application (image recognition, signal recognition, data processing), and geography (North America, Europe, Asia Pacific, Latin America, and Middle East and Africa).The market sizes and forecasts are provided in terms of value (USD) for all the above segments.

Offering Hardware
Software and Services
End-User Industry BFSI
Retail
Manufacturing
Healthcare
Automotive
Telecom and Media
Other End-user Industries
Application Image Recognition
Signal Recognition
Data Processing
Other Applications
Geography North America
Europe
Asia-Pacific
Rest of the World
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Deep Learning Market Research FAQs

How big is the Deep Learning Market?

The Deep Learning Market size is expected to reach USD 34.89 billion in 2025 and grow at a CAGR of 41.10% to reach USD 195.16 billion by 2030.

What is the current Deep Learning Market size?

In 2025, the Deep Learning Market size is expected to reach USD 34.89 billion.

Who are the key players in Deep Learning Market?

Facebook Inc., Google LLC, Microsoft Corporation, IBM Corporation and Amazon Web Services Inc. are the major companies operating in the Deep Learning Market.

Which is the fastest growing region in Deep Learning Market?

Asia Pacific is estimated to grow at the highest CAGR over the forecast period (2025-2030).

Which region has the biggest share in Deep Learning Market?

In 2025, the North America accounts for the largest market share in Deep Learning Market.

What years does this Deep Learning Market cover, and what was the market size in 2024?

In 2024, the Deep Learning Market size was estimated at USD 20.55 billion. The report covers the Deep Learning Market historical market size for years: 2019, 2020, 2021, 2022, 2023 and 2024. The report also forecasts the Deep Learning Market size for years: 2025, 2026, 2027, 2028, 2029 and 2030.

Deep Learning Industry Report

Statistics for the 2025 Deep Learning market share, size and revenue growth rate, created by Mordor Intelligence™ Industry Reports. Deep Learning analysis includes a market forecast outlook for 2025 to 2030 and historical overview. Get a sample of this industry analysis as a free report PDF download.