大規模AIモデル市場レポート：動向、予測、競合分析 (2031年まで)

世界の大規模AIモデル市場の将来性は、教育、エネルギー、自動車、医療市場における機会で有望視されています。世界の大規模AIモデル市場は、2025年から2031年にかけてCAGR 28.5%で成長すると予測されています。この市場の主な促進要因は、複雑なタスクに対応する強力な大規模言語モデルに対する需要の高まり、AIエンジニアやデータサイエンティストの増加、医療・金融・自動車などの業界におけるこのモデルの利用の高まりです。

• Lucintel社は、種類別では自然言語処理基盤モデルが予測期間中に最も高い成長を遂げると予測しています。
• 用途別では、教育分野が最も高い成長が見込まれています。
• 地域別では、アジア太平洋が予測期間中に最も高い成長が見込まれます。

大規模AIモデル市場の戦略的成長機会

大規模AIモデル市場には、さまざまな用途で数多くの成長機会があります。これらの機会を特定し活用することで、イノベーションと競合優位性を促進することができます。ここでは、AIモデル市場における5つの主要な成長機会を紹介し、それぞれがさまざまな分野に影響を与える可能性があります。

• 医療診断と個別化医療：大規模AIモデルは、医療における診断と個別化医療に大きな可能性をもたらします。膨大な医療データを分析することで、これらのモデルは病気の早期発見、個別化治療計画、創薬を支援することができます。成長機会は、医療行為における精度と効率を高めるためにAIを医療システムに統合することにあります。
• 自律走行車とスマート交通：AIモデルは、自律走行車とスマート交通システムの開発に不可欠です。高度なモデルは、車両の知覚、ナビゲーション、意思決定プロセスを改善します。AIを活用して安全性を高め、交通管理を最適化し、交通インフラの革新を推進することで、モビリティの未来に貢献するチャンスがあります。
• 金融サービスとリスク管理：金融分野では、大規模AIモデルがリスク管理、不正検知、顧客サービスに変革をもたらしつつあります。金融取引や市場データを分析することで、AIはパターンや異常を特定し、より正確なリスク評価やパーソナライズされた金融サービスを可能にします。AIを導入して意思決定と業務効率を向上させることにこそチャンスがあります。
• 小売業と顧客体験：AIモデルは、顧客体験をパーソナライズし、在庫管理を最適化することで、小売業界を強化しています。大規模なモデルは、消費者の行動や嗜好を分析し、ターゲットを絞ったマーケティングを推進し、商品の推奨を改善することができます。成長機会は、AIを活用してより魅力的なショッピング体験を創造し、小売業務を合理化することにあります。
• 産業オートメーションと予知保全：AIモデルは、機器のデータを分析して故障を予測し、メンテナンス・スケジュールを最適化することで、産業オートメーションと予知保全を推進しています。このアプリケーションは業務効率を改善し、ダウンタイムを削減します。AIを産業プロセスに統合することで、生産性を向上させ、機器の寿命を延ばすことができます。

こうした戦略的成長機会は、様々な産業を変革する大規模AIモデルの可能性を浮き彫りにしています。医療・輸送・金融・小売・産業オートメーションなどのアプリケーションに注力することで、企業はイノベーションを推進し、大きな競争優位性を獲得することができます。AIモデルの継続的な開発と展開は、これらの分野の将来を形成し、成長のための新たな道を切り開くと思われます。

大規模AIモデル市場促進要因・課題

大規模AIモデル市場は、技術的進歩、経済的要因、規制上の考慮事項など、さまざまな促進要因・課題の影響を受けています。これらの要素を理解することは、市場をナビゲートし、機会を効果的に活用するために極めて重要です。ここでは、市場に影響を与える主な促進要因・課題を紹介します。

大規模AIモデル市場を牽引する要因は以下の通りである：

• 技術進歩：計算能力とモデルアーキテクチャの進歩が大規模AIモデルの成長を促進しています。トランスフォーマーネットワークや分散型学習技術などの革新により、より洗練された高性能なモデルが可能になります。このような技術的向上により、性能が強化され、AIの潜在的用途が拡大するため、市場の成長が促進され、投資が誘致されます。
• データ可用性の向上：データの利用可能性が飛躍的に高まることで、大規模AIモデルを訓練するための豊富なリソースが提供されます。多様で広範なデータセットへのアクセスは、モデルの精度と能力を向上させます。この促進要因は、より効果的なAIソリューションの開発をサポートし、医療、金融、小売を含む様々な分野でのイノベーションを加速させます。
• 自動化需要の高まり：製造、金融、物流などの業界における自動化需要の高まりは、AIモデル採用の主要な促進要因です。自動化は効率を高め、コストを削減し、さまざまなプロセスの精度を向上させます。大規模AIモデルは、高度な自動化ソリューションを実現する上で重要な役割を果たし、市場の拡大と応用を促進します。
• 投資と資金調達：官民双方からの多額の投資と資金調達が、大規模AIモデルの進歩に拍車をかけています。ベンチャーキャピタル、政府助成金、企業投資は研究開発を支援し、最先端AI技術の開発と展開を加速させています。このような財政的支援は、市場成長の大きな原動力となっています。
• 世界の競合情勢：AI市場の競合情勢はイノベーションと開発を促進します。企業や各国は、競争力を維持し技術の進歩をリードするため、大規模AIモデルに投資しています。この圧力は、継続的な改善と、より高度で有能なAIソリューションの創出を促します。

大規模AIモデル市場における課題は以下の通り：

• 規制と倫理的懸念：規制と倫理的な懸念は、大規模AIモデル市場に大きな課題を突きつけています。データのプライバシー、アルゴリズムの偏り、透明性などの問題が精査されており、厳しい規制や倫理的ガイドラインの開発につながっています。こうした規制の遵守は、イノベーションのスピードに影響を与え、運用の複雑性を高める可能性があります。
• 高い計算コスト：大規模AIモデルの開発と展開には膨大な計算リソースが必要であり、これは高コストにつながります。強力なハードウェアと膨大なエネルギー消費が必要となるため、財政的・環境的課題が生じます。持続可能でスケーラブルなAIソリューションを確保するためには、これらのコストに対処することが不可欠です。
• 人材不足：熟練したAI専門家の不足が市場の課題となっています。大規模AIモデルの開発の複雑さには、機械学習、データサイエンス、エンジニアリングの専門知識が必要です。この人材ギャップは、イノベーションのペースを制限し、組織がAIテクノロジーを十分に活用する能力を妨げる可能性があります。

概説した市場促進要因・課題は、大規模AIモデル市場のダイナミックな性質を浮き彫りにしています。技術の進歩、データの利用可能性、自動化需要の高まりが成長を後押しする一方で、規制上の懸念、高コスト、人材不足が大きなハードルとなっています。これらの要因を理解することは、市場をナビゲートし、新たな機会を活用する上で極めて重要です。

目次

第1章 エグゼクティブサマリー

第2章 世界の大規模AIモデル市場：市場力学

• イントロダクション、背景、分類
• サプライチェーン
• 業界の促進要因と課題

第3章 市場動向と予測分析 (2019年～2031年)

• マクロ経済動向 (2019～2024年) と予測 (2025～2031年)
• 世界の大規模AIモデル市場の動向 (2019～2024年) と予測 (2025～2031年)
• 世界の大規模AIモデル市場：種類別
  • 自然言語処理基礎モデル
  • コンピュータビジョン基盤モデル
  • マルチモーダル基盤モデル
  • その他
• 世界の大規模AIモデル市場：用途別
  • 教育
  • エネルギー
  • 自動車
  • 医療
  • その他

第4章 地域別の市場動向と予測分析 (2019年～2031年)

• 世界の大規模AIモデル市場：地域別
• 北米の大規模AIモデル市場
• 欧州の大規模AIモデル市場
• アジア太平洋の大規模AIモデル市場
• その他地域の大規模AIモデル市場

第5章 競合分析

• 製品ポートフォリオ分析
• 運用統合
• ポーターのファイブフォース分析

第6章 成長機会と戦略分析

• 成長機会分析
  • 世界の大規模AIモデル市場の成長機会：種類別
  • 世界の大規模AIモデル市場の成長機会：用途別
  • 世界の大規模AIモデル市場の成長機会：地域別
• 世界の大規模AIモデル市場の新たな動向
• 戦略的分析
  • 新製品の開発
  • 世界の大規模AIモデル市場の生産能力拡大
  • 世界の大規模AIモデル市場における企業合併・買収 (M&A)、合弁事業
  • 認証とライセンシング

第7章 主要企業のプロファイル

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

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.

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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