시장보고서
상품코드
1956723

인공 신경망 시장 규모, 점유율, 동향 및 성장 분석 보고서(2026-2034년)

Global Artificial Neural Network Market Size, Share, Trends & Growth Analysis Report 2026-2034

발행일: | 리서치사: Value Market Research | 페이지 정보: 영문 161 Pages | 배송안내 : 1-2일 (영업일 기준)

    
    
    




※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

인공 신경망 시장 규모는 2025년 5억 5,000만 달러에서 2034년에는 28억 5,000만 달러에 달할 것으로 예측되며, 2026년부터 2034년까지 CAGR 20.02%로 성장할 전망입니다.

인공 신경망(ANN) 시장은 산업 분야에서의 머신러닝 및 딥러닝 기술 활용 확대에 따라 큰 폭의 성장이 예상됩니다. 계산 능력의 발전과 빅데이터의 보급으로 ANN은 이미지 인식, 자연어 처리, 예측 분석 등 다양한 응용 분야에서 없어서는 안 될 존재가 되고 있습니다. 의료, 금융, 자동차 등의 분야에서 자동화 및 지능형 시스템에 대한 수요가 증가함에 따라 혁신을 촉진하고 성능과 효율성을 향상시킬 수 있는 보다 진보된 신경망 아키텍처가 개발되고 있습니다.

조직이 인공지능의 잠재력을 활용하고자 하는 가운데, 기존 시스템에 ANN을 통합하는 것이 전략적 우선순위가 되고 있습니다. 이러한 추세는 데이터 처리와 의사결정을 원천에서 실시간으로 수행하는 엣지 컴퓨팅의 부상으로 더욱 가속화되고 있습니다. 그 결과, 기업들은 특정 산업 문제에 대응하는 맞춤형 솔루션을 개발하기 위해 연구개발에 투자하고 있으며, 이는 기술 공급자와 최종사용자 간의 협력을 촉진하는 경쟁 환경을 조성하고 있습니다. 또한, AI 모델의 설명 가능성과 투명성에 대한 강조도 인공신경망의 미래를 형성하고 있습니다. 이는 자동화된 의사결정 과정에서 이해관계자들이 더 큰 책임성을 요구하게 되었기 때문입니다.

향후 인공신경망 시장은 자율시스템, 스마트 시티 등 신흥 분야에서 응용 범위가 급격하게 확대될 것으로 예상됩니다. 인공신경망이 사물인터넷(IoT), 블록체인과 같은 다른 기술과 융합하면 혁신과 효율성을 위한 새로운 기회가 열릴 것입니다. 조직이 디지털 전환을 최우선 과제로 삼고 있는 가운데, 인공신경망을 활용하여 인사이트를 높이고 비즈니스 민첩성을 향상시키는 능력은 시장에서 중요한 차별화 요소로 작용할 것이며, 향후 몇 년 동안 인공신경망 분야의 지속적인 성장과 중요성 확고히 할 것입니다.

목차

제1장 소개

제2장 주요 요약

제3장 시장 변수, 동향, 프레임워크

제4장 세계의 인공 신경망 시장 : 구성요소별

제5장 세계의 인공 신경망 시장 : 전개 방식별

제6장 세계의 인공 신경망 시장 : 기업 규모별

제7장 세계의 인공 신경망 시장 : 산업별

제8장 세계의 인공 신경망 시장 : 지역별

제9장 경쟁 구도

제10장 기업 개요

KSM 26.03.19

The Artificial Neural Network Market size is expected to reach USD 2.85 Billion in 2034 from USD 0.55 Billion (2025) growing at a CAGR of 20.02% during 2026-2034.

The Artificial Neural Network (ANN) market is poised for significant expansion as industries increasingly leverage machine learning and deep learning technologies. With advancements in computational power and the proliferation of big data, ANNs are becoming integral to various applications, including image recognition, natural language processing, and predictive analytics. The growing demand for automation and intelligent systems across sectors such as healthcare, finance, and automotive is driving innovation, leading to the development of more sophisticated neural architectures that enhance performance and efficiency.

As organizations seek to harness the potential of artificial intelligence, the integration of ANNs into existing systems is becoming a strategic priority. This trend is further fueled by the rise of edge computing, which allows for real-time data processing and decision-making at the source. Consequently, businesses are investing in research and development to create tailored solutions that address specific industry challenges, thereby fostering a competitive landscape that encourages collaboration between technology providers and end-users. The emphasis on explainability and transparency in AI models is also shaping the future of ANNs, as stakeholders demand greater accountability in automated decision-making processes.

Looking ahead, the ANN market is expected to witness a surge in applications across emerging fields such as autonomous systems and smart cities. The convergence of ANNs with other technologies, such as the Internet of Things (IoT) and blockchain, will unlock new opportunities for innovation and efficiency. As organizations continue to prioritize digital transformation, the ability to leverage ANNs for enhanced insights and operational agility will be a key differentiator in the marketplace, positioning the ANN sector for sustained growth and relevance in the coming years.

Our reports are meticulously crafted to provide clients with comprehensive and actionable insights into various industries and markets. Each report encompasses several critical components to ensure a thorough understanding of the market landscape:

Market Overview: A detailed introduction to the market, including definitions, classifications, and an overview of the industry's current state.

Market Dynamics: In-depth analysis of key drivers, restraints, opportunities, and challenges influencing market growth. This section examines factors such as technological advancements, regulatory changes, and emerging trends.

Segmentation Analysis: Breakdown of the market into distinct segments based on criteria like product type, application, end-user, and geography. This analysis highlights the performance and potential of each segment.

Competitive Landscape: Comprehensive assessment of major market players, including their market share, product portfolio, strategic initiatives, and financial performance. This section provides insights into the competitive dynamics and key strategies adopted by leading companies.

Market Forecast: Projections of market size and growth trends over a specified period, based on historical data and current market conditions. This includes quantitative analyses and graphical representations to illustrate future market trajectories.

Regional Analysis: Evaluation of market performance across different geographical regions, identifying key markets and regional trends. This helps in understanding regional market dynamics and opportunities.

Emerging Trends and Opportunities: Identification of current and emerging market trends, technological innovations, and potential areas for investment. This section offers insights into future market developments and growth prospects.

MARKET SEGMENTATION

By Component

  • Solution
  • Services

By Deployment Mode

  • Cloud
  • On-Premise

By Enterprise Size

  • Large Enterprises
  • SMEs

By Industry

  • Healthcare
  • BFSI
  • Retail And E-Commerce
  • Manufacturing
  • Automotive
  • Others

COMPANIES PROFILED

  • Hewlett Packard Enterprise Development LP, Salesforce Inc, IBM Corporation, Intel Corporation, Microsoft Corporation, Amazon Web Services Inc, NVIDIA Corporation, Google Inc, Qualcomm Technologies Inc, Oracle Corporation

We can customise the report as per your requriements

TABLE OF CONTENTS

Chapter 1. PREFACE

  • 1.1. Market Segmentation & Scope
  • 1.2. Market Definition
  • 1.3. Information Procurement
    • 1.3.1 Information Analysis
    • 1.3.2 Market Formulation & Data Visualization
    • 1.3.3 Data Validation & Publishing
  • 1.4. Research Scope and Assumptions
    • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

  • 2.1. Market Snapshot
  • 2.2. Segmental Outlook
  • 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

  • 3.1. Market Lineage Outlook
  • 3.2. Penetration & Growth Prospect Mapping
  • 3.3. Value Chain Analysis
  • 3.4. Regulatory Framework
    • 3.4.1 Standards & Compliance
    • 3.4.2 Regulatory Impact Analysis
  • 3.5. Market Dynamics
    • 3.5.1 Market Drivers
    • 3.5.2 Market Restraints
    • 3.5.3 Market Opportunities
    • 3.5.4 Market Challenges
  • 3.6. Porter's Five Forces Analysis
  • 3.7. PESTLE Analysis

Chapter 4. GLOBAL ARTIFICIAL NEURAL NETWORK MARKET: BY COMPONENT 2022-2034 (USD MN)

  • 4.1. Market Analysis, Insights and Forecast Component
  • 4.2. Solution Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 4.3. Services Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL ARTIFICIAL NEURAL NETWORK MARKET: BY DEPLOYMENT MODE 2022-2034 (USD MN)

  • 5.1. Market Analysis, Insights and Forecast Deployment Mode
  • 5.2. Cloud Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 5.3. On-Premise Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL ARTIFICIAL NEURAL NETWORK MARKET: BY ENTERPRISE SIZE 2022-2034 (USD MN)

  • 6.1. Market Analysis, Insights and Forecast Enterprise Size
  • 6.2. Large Enterprises Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 6.3. SMEs Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL ARTIFICIAL NEURAL NETWORK MARKET: BY INDUSTRY 2022-2034 (USD MN)

  • 7.1. Market Analysis, Insights and Forecast Industry
  • 7.2. Healthcare Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.3. BFSI Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.4. Retail And E-Commerce Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.5. Manufacturing Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.6. Automotive Estimates and Forecasts By Regions 2022-2034 (USD MN)
  • 7.7. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL ARTIFICIAL NEURAL NETWORK MARKET: BY REGION 2022-2034(USD MN)

  • 8.1. Regional Outlook
  • 8.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.2.1 By Component
    • 8.2.2 By Deployment Mode
    • 8.2.3 By Enterprise Size
    • 8.2.4 By Industry
    • 8.2.5 United States
    • 8.2.6 Canada
    • 8.2.7 Mexico
  • 8.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.3.1 By Component
    • 8.3.2 By Deployment Mode
    • 8.3.3 By Enterprise Size
    • 8.3.4 By Industry
    • 8.3.5 United Kingdom
    • 8.3.6 France
    • 8.3.7 Germany
    • 8.3.8 Italy
    • 8.3.9 Russia
    • 8.3.10 Rest Of Europe
  • 8.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.4.1 By Component
    • 8.4.2 By Deployment Mode
    • 8.4.3 By Enterprise Size
    • 8.4.4 By Industry
    • 8.4.5 India
    • 8.4.6 Japan
    • 8.4.7 South Korea
    • 8.4.8 Australia
    • 8.4.9 South East Asia
    • 8.4.10 Rest Of Asia Pacific
  • 8.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.5.1 By Component
    • 8.5.2 By Deployment Mode
    • 8.5.3 By Enterprise Size
    • 8.5.4 By Industry
    • 8.5.5 Brazil
    • 8.5.6 Argentina
    • 8.5.7 Peru
    • 8.5.8 Chile
    • 8.5.9 South East Asia
    • 8.5.10 Rest of Latin America
  • 8.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
    • 8.6.1 By Component
    • 8.6.2 By Deployment Mode
    • 8.6.3 By Enterprise Size
    • 8.6.4 By Industry
    • 8.6.5 Saudi Arabia
    • 8.6.6 UAE
    • 8.6.7 Israel
    • 8.6.8 South Africa
    • 8.6.9 Rest of the Middle East And Africa

Chapter 9. COMPETITIVE LANDSCAPE

  • 9.1. Recent Developments
  • 9.2. Company Categorization
  • 9.3. Supply Chain & Channel Partners (based on availability)
  • 9.4. Market Share & Positioning Analysis (based on availability)
  • 9.5. Vendor Landscape (based on availability)
  • 9.6. Strategy Mapping

Chapter 10. COMPANY PROFILES OF GLOBAL ARTIFICIAL NEURAL NETWORK INDUSTRY

  • 10.1. Top Companies Market Share Analysis
  • 10.2. Company Profiles
    • 10.2.1 Hewlett Packard Enterprise Development LP
    • 10.2.2 Salesforce Inc
    • 10.2.3 IBM Corporation
    • 10.2.4 Intel Corporation
    • 10.2.5 Microsoft Corporation
    • 10.2.6 Amazon Web Services Inc
    • 10.2.7 NVIDIA Corporation
    • 10.2.8 Google Inc
    • 10.2.9 Qualcomm Technologies Inc
    • 10.2.10 Oracle Corporation
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