머신러닝 시장 분석 및 예측(-2033년) : 유형별, 제품별, 서비스별, 기술별, 구성요소별, 용도별, 전개별, 최종사용자별, 지역별
Machine Learning Market Analysis and Forecast to 2033: Type, Product, Services, Technology, Component, Application, Deployment, End User
상품코드 : 1608670
리서치사 : Global Insight Services
발행일 : 2024년 12월
페이지 정보 : 영문 350 Pages
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한글목차

머신러닝 시장 규모는 25.7%의 연평균 성장률(CAGR)로 2023년 245억 달러에서 2033년 2,259억 달러로 확대될 것으로 예상됩니다. 머신러닝 시장에는 명시적으로 프로그래밍하지 않고도 시스템이 경험을 통해 학습하고 개선할 수 있는 알고리즘과 모델의 개발 및 배포가 포함됩니다. 이 시장에는 데이터 분석, 패턴 인식 및 의사결정 과정을 촉진하는 소프트웨어 플랫폼, 인프라 및 서비스가 포함됩니다. 금융, 헬스케어, 자동차 등 다양한 산업에 걸쳐 자동화 및 예측 분석을 통해 혁신과 효율성을 촉진합니다. 이 시장은 급속한 발전, AI 기술 채택 확대, 데이터 기반 인사이트에 대한 수요 증가가 특징이며, 각 분야에서 성장과 혁신의 큰 기회를 제공하고 있습니다.

머신러닝 시장은 기술 발전과 산업 전반에 걸친 AI 통합의 진전에 힘입어 견조한 성장세를 보이고 있습니다. 효율적인 데이터 분석 및 예측 모델링 도구에 대한 수요에 힘입어 소프트웨어 분야가 주도하고 있습니다. 하드웨어, 특히 GPU와 TPU는 복잡한 알고리즘을 처리하는 데 필수적인 하위 부문으로 두 번째로 높은 성능을 보이고 있습니다. 기업들이 AI 솔루션 도입을 위해 전문가의 지도를 구하면서 컨설팅 및 도입 등 서비스 분야도 성장세를 보이고 있습니다. 지역별로는 북미가 기술 도입이 빠르고 AI 연구에 많은 투자를 하고 있는 북미가 우위를 점하고 있습니다. 유럽은 규제 프레임워크와 윤리적 AI에 초점을 맞추고 있어 두 번째로 강한 지역입니다. 아시아태평양에서는 중국과 인도가 정부의 지원과 급성장하는 기술 생태계에 힘입어 주요 지역으로 부상하고 있습니다. 자동차 및 헬스케어 분야는 머신러닝 애플리케이션의 최전선에서 자율주행 능력과 맞춤형 의료를 강화하는 데 앞장서고 있습니다. 이 역동적인 시장은 각 산업이 AI의 변혁적 잠재력을 활용함에 따라 지속적인 성장이 예상됩니다.

경쟁 환경은 급속한 기술 발전과 전략적 제휴로 형성되고 있습니다. 특히 데이터 프라이버시 및 보안 관련 규제 프레임워크는 시장 역학에 큰 영향을 미칩니다. 일반 데이터 보호 규정(GDPR)과 유사한 정책은 컴플라이언스를 요구하고 운영 비용에 영향을 미칩니다. 향후 예측에 따르면, 자율 시스템과 예측 분석에 머신러닝이 통합되면서 2033년까지 18%의 CAGR을 기록할 것으로 예상됩니다. R&D와 윤리적 AI 개발에 대한 투자가 가장 중요하며, R&D 비용은 15% 증가할 것으로 예상됩니다. 데이터 편향성, 윤리적 문제 등의 과제가 남아있지만, 헬스케어와 금융 분야에는 기회가 넘쳐나고 있습니다.

이 보고서는 세계 머신러닝 시장을 조사하여 시장 개요와 함께 유형별, 제품별, 서비스별, 기술별, 구성요소별, 용도별, 전개별, 최종사용자별, 지역별 동향, 시장 진입 기업 개요 등을 정리했습니다.

목차

제1장 머신러닝 시장 개요

제2장 주요 요약

제3장 시장에 관한 주요 인사이트

제4장 머신러닝 시장 전망

제5장 머신러닝 시장 전략

제6장 머신러닝 시장 규모

제7장 머신러닝 시장(유형별)

제8장 머신러닝 시장(제품별)

제9장 머신러닝 시장(서비스별)

제10장 머신러닝 시장(기술별)

제11장 머신러닝 시장(구성요소별)

제12장 머신러닝 시장(용도별)

제13장 머신러닝 시장(전개별)

제14장 머신러닝 시장(최종사용자별)

제15장 머신러닝 시장(지역별)

제16장 경쟁 구도

제17장 기업 개요

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영문 목차

영문목차

The machine learning market is anticipated to expand from $24.5 billion in 2023 to $225.9 billion by 2033, reflecting a CAGR of 25.7%. The Machine Learning Market encompasses the development and deployment of algorithms and models that enable systems to learn and improve from experience without being explicitly programmed. This market includes software platforms, infrastructure, and services that facilitate data analysis, pattern recognition, and decision-making processes. It spans various industries such as finance, healthcare, and automotive, driving innovation and efficiency through automation and predictive analytics. The market is characterized by rapid advancements, increased adoption of AI technologies, and a growing demand for data-driven insights, presenting significant opportunities for growth and transformation across sectors.

The machine learning market is witnessing robust expansion, propelled by technological advancements and the increasing integration of AI across industries. The software segment leads, driven by the demand for efficient data analytics and predictive modeling tools. Hardware, particularly GPUs and TPUs, follows as the second-highest performing sub-segment, essential for processing complex algorithms. The services segment, encompassing consulting and deployment, is also gaining momentum as enterprises seek expert guidance to implement AI solutions.nnRegionally, North America dominates due to early technology adoption and substantial investments in AI research. Europe is the second strongest region, with a focus on regulatory frameworks and ethical AI. Within Asia-Pacific, China and India emerge as key players, fueled by governmental support and a burgeoning tech ecosystem. The automotive and healthcare sectors are at the forefront of machine learning applications, enhancing autonomous driving capabilities and personalized medicine. This dynamic market is poised for continued growth as industries harness AI's transformative potential.

In 2023, the Machine Learning Market exhibited impressive dynamism, with a projected market volume of 1.2 billion units, forecasting growth to 2.5 billion units by 2033. The software segment commands the largest market share at 45%, driven by the proliferation of AI applications across industries. Hardware follows with a 30% share, buoyed by advancements in processing capabilities. Services, encompassing consulting and deployment, hold a 25% share, reflecting the increasing need for tailored solutions. Key players such as Google, IBM, and Microsoft dominate the landscape, leveraging innovation and strategic partnerships to maintain their competitive edge.

The competitive environment is shaped by rapid technological advancements and strategic alliances. Regulatory frameworks, particularly in data privacy and security, significantly influence market dynamics. The General Data Protection Regulation (GDPR) and similar policies necessitate compliance, impacting operational costs. Investment in R&D and ethical AI development is paramount, with a predicted 15% increase in R&D expenditure. Opportunities abound in sectors like healthcare and finance, though challenges such as data bias and ethical concerns persist.

The North American machine learning market is a leader, driven by significant investments and technological advancements. The United States spearheads this growth with its robust research and development infrastructure. Companies in this region are rapidly adopting machine learning to enhance business operations and customer experiences. The presence of major technology firms further accelerates innovation and market expansion.

Europe follows closely, with a strong focus on integrating machine learning across various industries. The European Union's initiatives to foster digital transformation play a crucial role. Countries like Germany and the United Kingdom are at the forefront, leveraging machine learning to gain competitive advantages.

In the Asia-Pacific region, the machine learning market is experiencing exponential growth. This surge is fueled by the increasing adoption of artificial intelligence technologies in countries such as China, Japan, and India. Governments and private sectors are heavily investing in AI infrastructure, propelling market dynamics. The region's burgeoning tech startups contribute to a vibrant ecosystem.

Latin America is gradually embracing machine learning, with Brazil and Mexico leading the charge. The market here benefits from a growing interest in digitalization and automation. Industries are recognizing the potential of machine learning to optimize processes and drive innovation.

The Middle East and Africa are emerging markets, showing promising potential. The adoption of machine learning is driven by initiatives to diversify economies and enhance technological capabilities. Countries like the United Arab Emirates and South Africa are investing in AI research, setting the stage for future growth.

Key Companies

Data Robot, H2 Oai, C3ai, Open AI, Graphcore, SAS Institute, Databricks, Deep Mind, Element AI, Cerebras Systems, Anaconda, Ponyai, Samba Nova Systems, Numenta, Vicarious, Cognitive Scale, Skymind, Ayasdi, Clarifai, Sentient Technologies

Sources

U.S. Department of Energy - Office of Science, European Commission - Digital Strategy, National Institute of Standards and Technology (NIST), Organisation for Economic Co-operation and Development (OECD), United Nations Educational, Scientific and Cultural Organization (UNESCO) - Institute for Statistics, International Telecommunication Union (ITU), World Economic Forum - Centre for the Fourth Industrial Revolution, Stanford University - Human-Centered Artificial Intelligence (HAI), Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL), University of California, Berkeley - Berkeley Artificial Intelligence Research (BAIR) Lab, Association for the Advancement of Artificial Intelligence (AAAI), Neural Information Processing Systems (NeurIPS) Conference, International Conference on Machine Learning (ICML), Conference on Computer Vision and Pattern Recognition (CVPR), Association for Computing Machinery (ACM) Conference on Knowledge Discovery and Data Mining (KDD), IEEE International Conference on Data Mining (ICDM), United Nations Conference on Trade and Development (UNCTAD), The Alan Turing Institute, European Union Agency for Cybersecurity (ENISA), The World Bank - Digital Development Partnership

Research Scope

Our research scope provides comprehensive market data, insights, and analysis across a variety of critical areas. We cover Local Market Analysis, assessing consumer demographics, purchasing behaviors, and market size within specific regions to identify growth opportunities. Our Local Competition Review offers a detailed evaluation of competitors, including their strengths, weaknesses, and market positioning. We also conduct Local Regulatory Reviews to ensure businesses comply with relevant laws and regulations. Industry Analysis provides an in-depth look at market dynamics, key players, and trends. Additionally, we offer Cross-Segmental Analysis to identify synergies between different market segments, as well as Production-Consumption and Demand-Supply Analysis to optimize supply chain efficiency. Our Import-Export Analysis helps businesses navigate global trade environments by evaluating trade flows and policies. These insights empower clients to make informed strategic decisions, mitigate risks, and capitalize on market opportunities.

TABLE OF CONTENTS

1. Machine Learning Market Overview

2. Executive Summary

3. Premium Insights on the Market

4. Machine Learning Market Outlook

5. Machine Learning Market Strategy

6. Machine Learning Market Size

7. Machine Learning Market, by Type

8. Machine Learning Market, by Product

9. Machine Learning Market, by Services

10. Machine Learning Market, by Technology

11. Machine Learning Market, by Component

12. Machine Learning Market, by Application

13. Machine Learning Market, by Deployment

14. Machine Learning Market, by End User

15. Machine Learning Market, by Region

16. Competitive Landscape

17. Company Profiles

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