한글목차

세계 대규모 AI 모델 시장의 미래는 교육, 에너지, 자동차, 의료 시장에서의 기회로 인해 유망합니다. 세계 대규모 AI 모델 시장은 2025-2031년 연평균 복합 성장률(CAGR) 28.5%로 성장할 것으로 예상됩니다. 이 시장의 주요 촉진요인은 복잡한 작업을 위한 강력한 대규모 언어 모델에 대한 수요 증가, AI 엔지니어 및 데이터 사이언스자 증가, 의료, 금융, 자동차 등의 산업에서 이 모델의 활용이 증가하고 있기 때문입니다.

• Lucintel은 유형별로는 자연어 처리 기반 모델이 예측 기간 동안 가장 높은 성장세를 보일 것으로 예측했습니다.
• 용도별로는 교육 분야가 가장 높은 성장이 예상되고 있습니다.
• 지역별로는 아시아태평양이 예측 기간 동안 가장 높은 성장을 보일 것으로 예상됩니다.

대규모 AI 모델 시장의 전략적 성장 기회

대규모 AI 모델 시장에는 다양한 응용 분야에서 수많은 성장 기회가 있습니다. 이러한 기회를 식별하고 활용하면 혁신과 경쟁 우위를 촉진할 수 있습니다. 여기서는 AI 모델 시장에서 다양한 분야에 영향을 미칠 수 있는 5가지 주요 성장 기회를 소개하고자 합니다.

• 의료 진단 및 맞춤형 의료: 대규모 AI 모델은 의료의 진단 및 맞춤형 의료에 큰 잠재력을 가지고 있습니다. 방대한 의료 데이터를 분석함으로써 이러한 모델은 질병의 조기 발견, 개인화된 치료 계획, 신약 개발을 지원할 수 있습니다. 성장 기회는 의료 행위의 정확성과 효율성을 높이기 위해 AI를 의료 시스템에 통합하는 데 있습니다.
• 자율주행차 및 스마트 교통: AI 모델은 자율주행차 및 스마트 교통 시스템 개발에 필수적입니다. 고급 모델은 차량의 인식, 내비게이션, 의사결정 과정을 개선하고, AI를 활용하여 안전성을 높이고, 교통 관리를 최적화하고, 교통 인프라의 혁신을 촉진함으로써 모빌리티의 미래에 기여할 수 있는 기회를 제공합니다.
• 금융 서비스 및 리스크 관리: 금융 분야에서는 대규모 AI 모델이 리스크 관리, 사기 감지, 고객 서비스에 혁신을 가져오고 있습니다. AI는 금융 거래 및 시장 데이터를 분석하여 패턴과 이상 징후를 식별하고, 보다 정확한 리스크 평가와 개인화된 금융 서비스를 가능하게 하며, AI를 도입하여 의사결정과 업무 효율성을 향상시킬 수 있는 기회가 있습니다.
• 소매업과 고객 경험: AI 모델은 고객 경험을 개인화하고 재고 관리를 최적화함으로써 소매 업계를 강화하고 있습니다. 대규모 모델은 소비자의 행동과 취향을 분석하여 타겟팅된 마케팅을 추진하고 상품 추천을 개선할 수 있습니다. 성장의 기회는 AI를 활용하여 보다 매력적인 쇼핑 경험을 창출하고 소매 업무를 간소화하는 데에 있습니다.
• 산업 자동화 및 예지보전: AI 모델은 장비의 데이터를 분석하여 고장을 예측하고 유지보수 일정을 최적화함으로써 산업 자동화 및 예지보전을 촉진합니다. 이 용도는 운영 효율성을 개선하고 다운타임을 줄이며, AI를 산업 프로세스에 통합하여 생산성을 향상시키고 장비의 수명을 연장할 수 있습니다.

이러한 전략적 성장 기회는 다양한 산업을 변화시킬 수 있는 대규모 AI 모델의 잠재력을 부각시키고 있습니다. 의료, 운송, 금융, 소매, 산업 자동화 등의 용도에 집중함으로써 기업은 혁신을 촉진하고 경쟁 우위를 확보할 수 있으며, AI 모델의 지속적인 개발 및 배포는 이들 분야의 미래를 형성하고 새로운 성장의 길을 열어줄 것으로 보인다"고 말했습니다. 새로운 성장의 길을 열어줄 것입니다.

대규모 AI 모델 시장 성장 촉진요인 및 과제

대규모 AI 모델 시장은 기술적 진보, 경제적 요인, 규제적 고려사항 등 다양한 촉진요인과 과제에 영향을 받고 있습니다. 이러한 요인을 이해하는 것은 시장을 탐색하고 기회를 효과적으로 활용하기 위해 매우 중요합니다. 여기서는 시장에 영향을 미치는 주요 촉진요인 및 과제를 소개합니다.

대규모 AI 모델 시장을 이끄는 요인은 다음과 같다:

• 기술 발전: 연산 능력과 모델 아키텍처의 발전이 대규모 AI 모델의 성장을 가속하고 있습니다. 트랜스포머 네트워크 및 분산 학습 기술과 같은 혁신은 더욱 정교하고 고성능 모델을 가능하게 합니다. 이러한 기술 발전은 성능을 향상시키고 AI의 잠재적 용도를 확대하여 시장 성장을 가속하고 투자를 유치할 수 있도록 돕습니다.
• 데이터 가용성 향상: 데이터 가용성이 비약적으로 증가함에 따라 대규모 AI 모델 학습을 위한 풍부한 리소스가 제공됩니다. 다양하고 광범위한 데이터 세트에 대한 접근성은 모델의 정확도와 능력을 향상시킵니다. 이러한 촉진요인은 보다 효과적인 AI 솔루션 개발을 지원하고 의료, 금융, 소매 등 다양한 분야의 혁신을 가속화할 수 있습니다.
• 자동화 수요 증가: 제조, 금융, 물류 등의 산업에서 자동화 수요 증가는 AI 모델 채택을 촉진하는 주요 요인입니다. 자동화는 효율성을 높이고, 비용을 절감하며, 다양한 프로세스의 정확도를 향상시킵니다. 대규모 AI 모델은 고도화된 자동화 솔루션을 실현하는 데 중요한 역할을 하며, 시장 확대와 응용을 촉진할 것입니다.
• 투자 및 자금 조달: 민관 양측의 막대한 투자와 자금 조달이 대규모 AI 모델의 발전에 박차를 가하고 있습니다. 벤처캐피털, 정부 보조금, 기업 투자는 연구개발을 지원하고 최첨단 AI 기술의 개발 및 배포를 가속화하고 있습니다. 이러한 재정적 지원은 시장 성장의 큰 원동력이 되고 있습니다.
• 세계 경쟁 환경: AI 시장의 경쟁 환경은 혁신과 발전을 촉진합니다. 기업과 국가들은 경쟁력을 유지하고 기술 발전을 선도하기 위해 대규모 AI 모델에 투자하고 있습니다. 이러한 압력은 지속적인 개선과 보다 진보되고 유능한 AI 솔루션의 창출을 촉진합니다.

대규모 AI 모델 시장의 과제는 다음과 같다:

• 규제와 윤리적 우려: 규제와 윤리적 우려는 대규모 AI 모델 시장에 큰 도전이 되고 있습니다. 데이터 프라이버시, 알고리즘의 편향성, 투명성 등의 이슈는 엄격한 규제와 윤리적 가이드라인의 개발로 이어지고 있습니다. 이러한 규제 준수는 혁신의 속도에 영향을 미치고 운영의 복잡성을 증가시킬 수 있습니다.
• 높은 계산 비용: 대규모 AI 모델 개발 및 배포에는 막대한 계산 리소스가 필요하며, 이는 높은 비용으로 이어집니다. 강력한 하드웨어와 막대한 에너지 소비가 필요하기 때문에 재정적, 환경적 문제가 발생합니다. 지속 가능하고 확장 가능한 AI 솔루션을 확보하기 위해서는 이러한 비용 문제를 해결하는 것이 필수적입니다.
• 인력 부족: 숙련된 AI 전문가 부족이 시장의 과제입니다. 대규모 AI 모델 개발의 복잡성은 머신러닝, 데이터 사이언스, 엔지니어링 전문 지식을 필요로 합니다. 이러한 인력 부족은 혁신의 속도를 제한하고 조직이 AI 기술을 충분히 활용할 수 있는 능력을 저해할 수 있습니다.

앞서 설명한 시장 성장 촉진요인과 과제는 대규모 AI 모델 시장의 역동적인 특성을 잘 보여줍니다. 기술 발전, 데이터 가용성, 자동화 수요 증가는 성장을 가속하는 반면, 규제 문제, 높은 비용, 인력 부족은 큰 걸림돌로 작용하고 있습니다. 이러한 요인을 이해하는 것은 시장을 탐색하고 새로운 기회를 활용하는 데 있어 매우 중요합니다.

목차

제1장 주요 요약

제2장 세계의 대규모 AI 모델 시장 : 시장 역학

• 서론, 배경, 분류
• 공급망
• 업계 촉진요인과 과제

제3장 시장 동향과 예측 분석(2019-2031년)

• 거시경제 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 대규모 AI 모델 시장 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 대규모 AI 모델 시장 : 유형별
  • 자연언어처리 기초 모델
  • 컴퓨터 비전 기반 모델
  • 멀티모달 기반 모델
  • 기타
• 세계의 대규모 AI 모델 시장 : 용도별
  • 교육
  • 에너지
  • 자동차
  • 의료
  • 기타

제4장 지역별 시장 동향과 예측 분석(2019-2031년)

• 세계의 대규모 AI 모델 시장 : 지역별
• 북미의 대규모 AI 모델 시장
• 유럽의 대규모 AI 모델 시장
• 아시아태평양의 대규모 AI 모델 시장
• 기타 지역의 대규모 AI 모델 시장

제5장 경쟁 분석

• 제품 포트폴리오 분석
• 운영 통합
• Porter의 Five Forces 분석

제6장 성장 기회와 전략 분석

• 성장 기회 분석
  • 세계의 대규모 AI 모델 시장 성장 기회 : 유형별
  • 세계의 대규모 AI 모델 시장 성장 기회 : 용도별
  • 세계의 대규모 AI 모델 시장 성장 기회 : 지역별
• 세계 대규모 AI 모델 시장의 새로운 동향
• 전략적 분석
  • 신제품 개발
  • 세계의 대규모 AI 모델 시장 생산능력 확대
  • 세계 대규모 AI 모델 시장에서의 인수합병(M&A) 및 합작투자(JV)
  • 인증 및 라이선싱

제7장 주요 기업 개요

• OpenAI
• Microsoft
• Google
• NVIDIA
• Alibaba
• Baidu
• Tencent
• Huawei
• Naver
• Anthropic

영문목차

The future of the global large AI model market looks promising with opportunities in the education, energy, automotive, and medical markets. The global large AI model market is expected to grow with a CAGR of 28.5% from 2025 to 2031. The major drivers for this market are the increasing demand for powerful large language models for complex tasks, a growing pool of AI engineers & data scientists, and the rising use of this model in industries like healthcare, finance, and automotive.

• Lucintel forecasts that, within the type category, the natural language processing foundation model is expected to witness the highest growth over the forecast period.
• Within the application category, education is expected to witness the highest growth.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period.

Gain valuable insights for your business decisions with our comprehensive 150+ page report.

Emerging Trends in the Large AI Model Market

The large AI model market is experiencing transformative shifts driven by several emerging trends. These trends reflect advancements in technology, changes in regulatory landscapes, and evolving market needs. Understanding these trends is crucial for stakeholders aiming to navigate the dynamic AI landscape and capitalize on emerging opportunities.

• Increased Multimodal Capabilities: Large AI models are increasingly incorporating multimodal capabilities, enabling them to process and integrate diverse data types such as text, images, and audio. This trend is driven by advancements in model architectures and training techniques, allowing for more sophisticated and context-aware AI systems. The result is enhanced performance in applications like autonomous vehicles, virtual assistants, and creative content generation.
• Focus on Ethical AI and Regulation: There is a growing emphasis on developing ethical AI frameworks and regulatory standards to address concerns about bias, transparency, and accountability. Governments and organizations are working to establish guidelines that ensure responsible AI use. This trend is reshaping the market by fostering trust and ensuring compliance, which is becoming a competitive differentiator for AI developers.
• Expansion of AI in Industry-Specific Applications: AI models are being increasingly tailored for specific industries such as healthcare, finance, and manufacturing. Industry-specific applications are driving demand for customized models that address unique challenges and requirements. This specialization allows for more effective solutions and drives growth in sectors where AI can provide significant operational improvements and innovations.
• Advancements in Model Efficiency and Accessibility: Innovations in model efficiency are making large AI models more accessible and cost-effective. Techniques such as model compression, pruning, and distributed training are reducing the computational resources required. This trend is democratizing access to advanced AI technologies, enabling smaller organizations and developing countries to leverage powerful AI solutions.
• Integration of AI with Edge Computing: The integration of AI with edge computing is enhancing real-time processing and reducing latency. By deploying AI models on edge devices, organizations can achieve faster data analysis and decision-making. This trend is particularly impactful for applications requiring immediate responses, such as autonomous systems and IoT devices.

These emerging trends are reshaping the large AI model market by enhancing capabilities, fostering ethical practices, and expanding applications across various industries. As AI technology continues to evolve, these trends will drive innovation and influence market dynamics, creating new opportunities and challenges for stakeholders.

Recent Developments in the Large AI Model Market

Recent developments in the large AI model market reflect rapid technological advancements and shifting market dynamics. These developments are shaping the future of AI by introducing new capabilities, addressing regulatory challenges, and influencing global competition. Here are five key developments impacting the market.

• Advancements in Transformer Architectures: Transformer architectures, such as GPT-4 and its successors, have significantly advanced the capabilities of large AI models in natural language understanding and generation. These models are setting new benchmarks in performance, enabling more nuanced and context-aware interactions. The advancements are driving improvements in applications like chatbots, content creation, and language translation.
• Growth of AI-as-a-Service (AIaaS): The rise of AI-as-a-Service platforms is transforming how organizations access and utilize large AI models. Providers like Microsoft Azure and Amazon Web Services offer scalable AI solutions without the need for extensive in-house infrastructure. This development is democratizing access to advanced AI technologies, allowing businesses of all sizes to leverage AI for various applications.
• Increased Focus on AI Ethics and Governance: The market is witnessing a heightened focus on AI ethics and governance, with organizations and governments developing frameworks to address issues related to bias, transparency, and accountability. Initiatives such as the EU's AI Act and industry-specific guidelines are shaping how large AI models are developed and deployed, ensuring responsible use and building public trust.
• Expansion into Emerging Markets: Large AI models are expanding into emerging markets, with significant investments in regions like Asia-Pacific and Latin America. This expansion is driven by growing digital infrastructure and increasing demand for AI solutions in sectors such as finance, healthcare, and retail. The market dynamics are shifting as companies adapt their strategies to cater to diverse regional needs.
• Innovations in Model Training and Deployment: New techniques in model training and deployment, such as federated learning and decentralized AI, are enhancing the efficiency and scalability of large AI models. These innovations allow for more secure and collaborative training processes while reducing the need for centralized data storage. They are enabling more personalized and adaptive AI solutions.

These key developments are driving significant changes in the large AI model market, influencing technology, accessibility, and governance. As the market evolves, these developments will continue to impact how AI is utilized and integrated into various sectors, shaping the future of AI technology and its applications.

Strategic Growth Opportunities for Large AI Model Market

The large AI model market presents numerous growth opportunities across various applications. Identifying and leveraging these opportunities can drive innovation and competitive advantage. Here are five key growth opportunities in the AI model market, each with the potential to impact various sectors.

• Healthcare Diagnostics and Personalized Medicine: Large AI models offer significant potential in healthcare for diagnostics and personalized medicine. By analyzing vast amounts of medical data, these models can assist in early disease detection, personalized treatment plans, and drug discovery. The growth opportunity lies in integrating AI with healthcare systems to enhance accuracy and efficiency in medical practices.
• Autonomous Vehicles and Smart Transportation: AI models are crucial for the development of autonomous vehicles and smart transportation systems. Advanced models improve vehicle perception, navigation, and decision-making processes. The opportunity is in leveraging AI to enhance safety, optimize traffic management, and drive innovations in transportation infrastructure, contributing to the future of mobility.
• Financial Services and Risk Management: In the financial sector, large AI models are transforming risk management, fraud detection, and customer service. By analyzing financial transactions and market data, AI can identify patterns and anomalies, enabling more accurate risk assessments and personalized financial services. The opportunity lies in deploying AI to improve decision-making and operational efficiency.
• Retail and Customer Experience: AI models are enhancing the retail industry by personalizing customer experiences and optimizing inventory management. Large models can analyze consumer behavior and preferences, driving targeted marketing and improving product recommendations. The growth opportunity is in using AI to create more engaging shopping experiences and streamline retail operations.
• Industrial Automation and Predictive Maintenance: AI models are advancing industrial automation and predictive maintenance by analyzing equipment data to predict failures and optimize maintenance schedules. This application improves operational efficiency and reduces downtime. The opportunity is in integrating AI with industrial processes to enhance productivity and extend equipment lifespan.

These strategic growth opportunities highlight the potential of large AI models to transform various industries. By focusing on applications such as healthcare, transportation, finance, retail, and industrial automation, organizations can drive innovation and achieve significant competitive advantages. The continued development and deployment of AI models will shape the future of these sectors and create new avenues for growth.

Large AI Model Market Driver and Challenges

The large AI model market is influenced by a range of drivers and challenges, encompassing technological advancements, economic factors, and regulatory considerations. Understanding these elements is crucial for navigating the market and leveraging opportunities effectively. Here are the major drivers and challenges impacting the market.

The factors responsible for driving the large AI model market include:

• Technological Advancements: Advances in computational power and model architectures are driving the growth of large AI models. Innovations like transformer networks and distributed training techniques enable more sophisticated and capable models. These technological improvements enhance performance and expand the potential applications of AI, fueling market growth and attracting investments.
• Increased Data Availability: The exponential growth in data availability provides a rich resource for training large AI models. Access to diverse and extensive datasets improves model accuracy and capabilities. This driver supports the development of more effective AI solutions and accelerates innovation across various sectors, including healthcare, finance, and retail.
• Rising Demand for Automation: The increasing demand for automation in industries such as manufacturing, finance, and logistics is a key driver for AI model adoption. Automation enhances efficiency, reduces costs, and improves accuracy in various processes. Large AI models play a crucial role in enabling advanced automation solutions, driving market expansion and application.
• Investment and Funding: Significant investment and funding from both public and private sectors are fueling advancements in large AI models. Venture capital, government grants, and corporate investments support research and development, accelerating the development and deployment of cutting-edge AI technologies. This financial backing is a major driver of market growth.
• Global Competitive Pressure: The competitive landscape in the AI market drives innovation and development. Companies and countries are investing in large AI models to maintain a competitive edge and lead in technological advancements. This pressure encourages continuous improvement and the creation of more advanced and capable AI solutions.

Challenges in the large AI model market include:

• Regulatory and Ethical Concerns: Regulatory and ethical concerns pose significant challenges for the large AI model market. Issues such as data privacy, algorithmic bias, and transparency are under scrutiny, leading to the development of stringent regulations and ethical guidelines. Compliance with these regulations can impact the speed of innovation and increase operational complexities.
• High Computational Costs: Developing and deploying large AI models requires substantial computational resources, which translates to high costs. The need for powerful hardware and extensive energy consumption poses financial and environmental challenges. Addressing these costs is essential for ensuring sustainable and scalable AI solutions.
• Talent Shortages: The shortage of skilled AI professionals is a challenge for the market. The complexity of developing large AI models requires expertise in machine learning, data science, and engineering. This talent gap can limit the pace of innovation and hinder the ability of organizations to fully leverage AI technologies.

The drivers and challenges outlined highlight the dynamic nature of the large AI model market. Technological advancements, data availability, and rising demand for automation are propelling growth, while regulatory concerns, high costs, and talent shortages present significant hurdles. Understanding these factors is crucial for navigating the market and capitalizing on emerging opportunities.

List of Large AI Model Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies large AI model companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the large AI model companies profiled in this report include-

• OpenAI
• Microsoft
• Google
• NVIDIA
• Alibaba
• Baidu
• Tencent
• Huawei
• Naver
• Anthropic

Large AI Model by Segment

The study includes a forecast for the global large AI model market by type, application, and region.

Large AI Model Market by Type [Analysis by Value from 2019 to 2031]:

• Natural Language Processing Foundation Model
• Computer Vision Foundation Model
• Multimodal Foundation Model
• Others

Large AI Model Market by Application [Analysis by Value from 2019 to 2031]:

• Education
• Energy
• Automotive
• Medical
• Others

Large AI Model Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the Large AI Model Market

The landscape of the large AI model market is evolving rapidly, driven by advancements in technology, shifting geopolitical dynamics, and varying regulatory environments. As AI models grow in complexity and application, countries like the United States, China, Germany, India, and Japan are at the forefront of significant developments. Each country is advancing in different ways, influencing global trends and competition. This overview highlights the latest advancements and strategic movements in these key markets, providing a snapshot of their unique contributions and challenges.

• United States: The U.S. continues to lead in AI innovation with significant investments from both private and public sectors. Companies like OpenAI and Google are pushing the boundaries with new models that integrate multimodal capabilities, combining text, images, and other data forms. The U.S. also benefits from a robust ecosystem of AI startups and research institutions, fostering rapid development. Regulatory discussions around ethical AI and data privacy are becoming more pronounced, aiming to balance innovation with responsible use.
• China: China is aggressively advancing its AI capabilities, with state-backed initiatives driving the development of large models for various applications, including natural language processing and computer vision. The government's support includes substantial funding and strategic planning through initiatives like the New Generation Artificial Intelligence Development Plan. Chinese tech giants like Baidu and Alibaba are making significant strides, though the market faces challenges related to data privacy regulations and geopolitical tensions impacting international collaborations.
• Germany: Germany is positioning itself as a leader in ethical AI and industry-specific applications. With strong government backing and significant investment in research, German companies are focusing on integrating AI models into manufacturing and automotive sectors. Initiatives like the AI4EU project aim to enhance collaboration across Europe. Germany is also leading discussions on ethical AI standards, ensuring that developments align with European values and regulations, which impacts its competitive positioning on the global stage.
• India: India is emerging as a key player in the AI market with a focus on affordable and scalable AI solutions. The country is leveraging its vast talent pool and growing tech ecosystem to develop models suited for diverse applications, from healthcare to agriculture. Government initiatives such as the National AI Strategy are promoting AI research and development. However, India faces challenges related to infrastructure and data privacy, which could influence the pace of its AI advancements.
• Japan: Japan is known for its innovation in robotics and AI integration into various sectors. Companies like SoftBank and NEC are developing advanced AI models that enhance automation and human-machine interaction. The Japanese government is fostering AI research through initiatives like the Society 5.0 framework, which aims to integrate AI into daily life and industry. Japan's focus on human-centric AI and collaboration between technology and traditional industries is shaping its competitive edge in the global market.

Features of the Global Large AI Model Market

Market Size Estimates: Large AI model market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: Large AI model market size by type, application, and region in terms of value ($B).

Regional Analysis: Large AI model market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the large AI model market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the large AI model market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the large AI model market by type (natural language processing foundation model, computer vision foundation model, multimodal foundation model, and others), application (education, energy, automotive, medical, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global Large AI Model Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global Large AI Model Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global Large AI Model Market by Type
  • 3.3.1: Natural Language Processing Foundation Model
  • 3.3.2: Computer Vision Foundation Model
  • 3.3.3: Multimodal Foundation Model
  • 3.3.4: Others
• 3.4: Global Large AI Model Market by Application
  • 3.4.1: Education
  • 3.4.2: Energy
  • 3.4.3: Automotive
  • 3.4.4: Medical
  • 3.4.5: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global Large AI Model Market by Region
• 4.2: North American Large AI Model Market
  • 4.2.1: North American Market by Type: Natural Language Processing Foundation Model, Computer Vision Foundation Model, Multimodal Foundation Model, and Others
  • 4.2.2: North American Market by Application: Education, Energy, Automotive, Medical, and Others
• 4.3: European Large AI Model Market
  • 4.3.1: European Market by Type: Natural Language Processing Foundation Model, Computer Vision Foundation Model, Multimodal Foundation Model, and Others
  • 4.3.2: European Market by Application: Education, Energy, Automotive, Medical, and Others
• 4.4: APAC Large AI Model Market
  • 4.4.1: APAC Market by Type: Natural Language Processing Foundation Model, Computer Vision Foundation Model, Multimodal Foundation Model, and Others
  • 4.4.2: APAC Market by Application: Education, Energy, Automotive, Medical, and Others
• 4.5: ROW Large AI Model Market
  • 4.5.1: ROW Market by Type: Natural Language Processing Foundation Model, Computer Vision Foundation Model, Multimodal Foundation Model, and Others
  • 4.5.2: ROW Market by Application: Education, Energy, Automotive, Medical, and Others

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global Large AI Model Market by Type
  • 6.1.2: Growth Opportunities for the Global Large AI Model Market by Application
  • 6.1.3: Growth Opportunities for the Global Large AI Model Market by Region
• 6.2: Emerging Trends in the Global Large AI Model Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global Large AI Model Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Large AI Model Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: OpenAI
• 7.2: Microsoft
• 7.3: Google
• 7.4: NVIDIA
• 7.5: Alibaba
• 7.6: Baidu
• 7.7: Tencent
• 7.8: Huawei
• 7.9: Naver
• 7.10: Anthropic