대규모 언어 모델 시장 : 제공, 유형, 모달리티, 전개, 용도, 산업 분야별 - 세계 예측(2025-2030년)

The Large Language Model Market was valued at USD 6.60 billion in 2023 and is projected to grow to USD 8.56 billion in 2024, with a CAGR of 31.92%, reaching USD 45.91 billion by 2030.

In recent years, large language models have rapidly emerged as a transformative force across diverse sectors. This report delves into the dynamic environment where advanced algorithms meet real-world applications and challenges. Market shifts and technological breakthroughs are reshaping industries that depend on automation, data-driven insights, and customer engagement. The integration of sophisticated natural language processing techniques has not only enhanced traditional workflows but has also opened up new avenues for innovation across disparate domains.

With growing investments in research and development, organizations are now able to leverage these models to streamline operations and unlock critical insights. This introductory narrative provides a foundational understanding of current market trends, underlying drivers, and the strategic imperatives influencing decision-making at the executive level. The evolving landscape is characterized by a global shift towards smarter, more efficient systems that work in tandem with human expertise.

As businesses aim to optimize customer interactions, enhance content generation capabilities, and innovate their service delivery, the importance of these models continues to rise. In this comprehensive overview, we explore not only the scientific and technological underpinnings but also the economic and strategic dimensions that are steering the market. The analysis presented herein has been carefully structured to enable stakeholders to gain a nuanced understanding of market dynamics essential for capitalizing on growth opportunities.

Transformative Shifts in the Large Language Models Landscape

The industry is witnessing unparalleled transformative shifts driven by rapid advancements in artificial intelligence and machine learning. Emerging trends have redefined traditional boundaries, prompting organizations to re-evaluate their strategies in response to volatile market conditions and intensifying global competition. The transition from rudimentary models to highly complex and versatile systems is reshaping market deployment and customer engagement models.

Innovative integrations in areas such as automated consulting, real-time support, and seamless content generation have become a cornerstone for businesses keen on maintaining a competitive edge. Technological disruption is not isolated to the evolution of algorithms; it has catalyzed an overall shift in business mindset, fostering an environment where continuous improvement and agile strategies are paramount. Providers of both services and software have recognized the potential for revolutionizing the way data is processed, analyzed, and monetized.

Stakeholders must address evolving business practices that now incorporate advanced analytics utilities, streamlined deployment models, and adaptable frameworks that support rapid prototyping. This seismic shift has also led to the redefinition of industry standards, simultaneously challenging established protocols while paving the way for new methodologies in deploying large language models. Forward-thinking businesses are increasingly prioritizing innovation-driven investments, ensuring that transformations in quality and performance are fully leveraged in a globally interconnected digital ecosystem.

Key Segmentation Insights in the Language Models Market

The comprehensive segmentation analysis provides a multifaceted view of the large language models market, delivering critical insights that help chart the future course of industry developments. The market has been analyzed based on offering, where both services and software play a pivotal role. The services segment includes consulting, development and integration, and support and maintenance, while the software segment is dissected further into closed-source and open-source large language models. Such differentiation allows for a granular understanding of the strengths and challenges inherent within each segment.

Furthermore, examination based on type is key, with specific attention paid to autoregressive language models, encoder-decoder models, multilingual models, pre-trained and fine-tuned models, and transformer-based models. This typology not only illuminates the functional intricacies of each category but also dictates varying use-case scenarios that influence adoption rates. Evaluating the market on the basis of modality uncovers critical insights related to audio, images, text, and video modalities. These modalities drive tailored applications that address sector-specific nuances and evolving consumer demands.

Deployment methods represent another significant segmentation, with cloud and on-premises solutions offering distinct operational paradigms. Analysis by application highlights diverse use cases, including chatbots and virtual assistants, code and content generation, customer service enhancement, language translation fidelity, and sentiment analysis accuracy. Lastly, the industry vertical segmentation spans banking, financial services and insurance, healthcare and life sciences, information technology and telecommunication, manufacturing, media and entertainment, and retail and e-commerce, offering a panoramic view of market penetration across sectors. This layered approach to segmentation uncovers insights that are crucial for strategic decision-making and long-term planning.

Based on Offering, market is studied across Services and Software. The Services is further studied across Consulting, Development & Integration, and Support & Maintenance. The Software is further studied across Closed-source LLM and Open-source LLM.

Based on Type, market is studied across Autoregressive Language Models, Encoder-Decoder Models, Multilingual Models, Pre-Trained & Fine-Tuned Models, and Transformer-Based Models.

Based on Modality, market is studied across Audio, Images, Text, and Video.

Based on Deployment, market is studied across Cloud and On-premises.

Based on Application, market is studied across Chatbots & Virtual Assistant, Code Generation, Content Generation, Customer Service, Language Translation, and Sentiment Analysis.

Based on Industry Vertical, market is studied across Banking, Financial Services & Insurance, Healthcare & Life Sciences, Information Technology & Telecommunication, Manufacturing, Media & Entertainment, and Retail & E-commerce.

Key Regional Insights in the Development and Adoption of Language Models

Geographical analysis underscores the diverse trends observed across different regions. In the Americas, rapid digital transformation is fostering innovation and accelerated adoption of advanced models in industries ranging from financial services to healthcare. The region's strong emphasis on research and technological breakthroughs is driving substantial investments in both public and private sectors.

In Europe, the Middle East, and Africa, regulatory frameworks and strategic partnerships form the bedrock of advancements in large language models. Organizations within these territories are balancing innovation with compliance, reflecting an environment where cutting-edge technology must align with robust legal and ethical standards. Collaboration between governments and private entities is facilitating the development of bespoke solutions that cater to local needs while also contributing to global technological dialogues.

The Asia-Pacific region is emerging as a powerhouse in the technological arena, with significant contributions to both hardware and software advancements. High consumer demand combined with supportive government policies has spurred massive developments in AI infrastructure. This diverse landscape reflects a blend of rapidly developing urban centers and burgeoning research communities that continuously push the boundaries of what these models can achieve. Collectively, these regional insights offer a rich contextual backdrop, illuminating how cultural, regulatory, and economic factors uniquely shape the market's evolution in different parts of the world.

Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

Key Insights Pertaining to Leading Players in the Market

The market is characterized by a constellation of influential companies that continue to redefine the competitive landscape. Leading the charge are innovators such as AI21 Labs Ltd. and Alibaba Group Holding Limited, whose research and innovation are setting new industry standards. Amazon Web Services, Inc., Anthropic PBC, and Baidu, Inc. are also pivotal in driving both infrastructural and strategic advancements, contributing to a paradigm shift in service delivery and market operations.

Notable contributions also arise from entities like Cerence Inc. and Cloudflare, Inc. which are actively developing integrated solutions that span critical segments of the market. Cognizant Technology Solutions Corporation stands out with its expansive portfolio that addresses consulting and development needs. Emerging players such as Cohere Inc. and Eden AI, Inc., alongside established names like Elastic N.V. and Google LLC by Alphabet Inc., ensure rigorous competitive dynamics.

Additional key participants including Huawei Technologies Co., Ltd., Hugging Face, Inc., and iGenius LLC, as well as industry stalwarts such as International Business Machines Corporation and Meta Platforms, Inc., add further depth to the competitive environment. Microsoft Corporation, Mistral AI, and Nippon Telegraph and Telephone Corporation contribute robust technological solutions, while Numenta, Inc., Nvidia Corporation, and OpenAI Inc. have consistently pushed the frontier with cutting-edge innovations. Other significant companies including Rakuten Group, Inc., Salesforce, Inc., Tencent Holdings Ltd., Vectara, Inc., Weights and Biases, Inc., and Zeta Alpha Vector BV underscore the breadth and diversity of market players. Their collective efforts are instrumental in driving technological convergence and establishing new benchmarks in the development and deployment of large language models.

The report delves into recent significant developments in the Large Language Model Market, highlighting leading vendors and their innovative profiles. These include AI21 Labs Ltd., Alibaba Group Holding Limited, Amazon Web Services, Inc., Anthropic PBC, Baidu, Inc., Cerence Inc., Cloudflare, Inc., Cognizant Technology Solutions Corporation, Cohere Inc., Eden AI, Inc., Elastic N.V., Google LLC by Alphabet Inc., Huawei Technologies Co., Ltd., Hugging Face, Inc., iGenius LLC, International Business Machines Corporation, Lexlegis, Luka, Inc., Meta Platforms, Inc., Microsoft Corporation, Mistral AI, Nippon Telegraph and Telephone Corporation, Numenta, Inc., Nvidia Corporation, OpenAI Inc., Rakuten Group, Inc., Salesforce, Inc., Tencent Holdings Ltd., Vectara, Inc., Weights and Biases, Inc., and Zeta Alpha Vector BV. Actionable Strategies for Thriving in the Transformed Language Model Environment

For industry leaders aiming to maintain a competitive edge in the rapidly evolving landscape of large language models, embracing a multifaceted approach to innovation is crucial. It is imperative that organizations invest in continuous research and development to explore the latest modeling techniques and deployment frameworks. By staying ahead of the curve, companies can discern emerging trends and adjust their strategies in real time to capture new market opportunities.

Leaders are advised to adopt a proactive stance on integration strategies that bridge the gap between advanced technologies and business functions. These strategies may include establishing partnerships with tech innovators, investing in modular systems that facilitate both cloud-based and on-premises deployments, and actively engaging in industry consortia to share best practices. A focus on operational agility, bolstered by state-of-the-art analytics and robust data management practices, can significantly enhance decision-making processes and drive efficiency.

Furthermore, strategic prioritization of training programs is essential to ensure that teams are well-versed in the nuances of modern language models. Executives should foster a culture where continuous learning and technological adaptation are core values. This includes not only leveraging internal expertise but also collaborating with external experts to gain vantage points on areas such as regulatory compliance and ethical considerations. An integrated approach that combines technological advancement with strong governance frameworks will help organizations scale efficiently while minimizing operational risks. Executives and decision-makers are strongly encouraged to incorporate these action steps to transform their operational landscapes and secure long-term success in a competitive market.

Concluding Remarks on the Future of Large Language Models

Summarizing the insights presented in this comprehensive overview, it is clear that the evolution of large language models is set to redefine both market structures and operational paradigms across multiple industries. The confluence of technological innovation, strategic segmentation, and robust competitive dynamics sets a new standard for how organizations approach data-driven decision-making and operational integration.

This detailed analysis not only encapsulates the transformative shifts and regional diversities influencing the market but also highlights the critical role of key players and rapidly developing application areas. From improving consumer experiences to enhancing operational efficiencies, the profound impact of advanced language models resonates across every facet of business strategy.

The revised landscape demands that decision-makers stay committed to continuous innovation while also balancing the need for regulatory compliance and ethical deployment. In doing so, companies not only secure a tactical advantage in the global marketplace but also contribute to the broader evolution of technological capabilities. As such, the convergence of insights and strategic actions presented here forms a road map for sustainable growth and pioneering progress in the years ahead.

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Surging adoption of AI-driven solutions in customer service and experience management
    • 5.1.1.2. Government policies and regulations encouraging AI development in both developed and emerging markets
  • 5.1.2. Restraints
    • 5.1.2.1. High operational costs and technical difficulties associated with deploying large-scale language models
  • 5.1.3. Opportunities
    • 5.1.3.1. Advancement in multilingual capabilities to enhance large language models
    • 5.1.3.2. Collaborations and partnerships between tech gaints to accelerate AI innovation
  • 5.1.4. Challenges
    • 5.1.4.1. Data privacy issues and regulatory hurdles confronting large language model implementation
• 5.2. Market Segmentation Analysis
  • 5.2.1. Offering: Foundational role in LLM deployment and utilization drives usage of software
  • 5.2.2. Type: The efficacy of transformer-based models due to their ability to capture long-range dependencies and context
  • 5.2.3. Modality: Widespread adoption of text modality due to its versatile and consistent integration across platforms and devices
  • 5.2.4. Deployment: Preference for cloud is largely driven by its scalability, flexibility, and cost-effectiveness
  • 5.2.5. Application: Accelerated digital transformation drives chatbot and virtual sssistant adoption across various industries
  • 5.2.6. Industry Vertical: Impact of large language models on the IT & telecommunication sector driven by their extensive range of applications
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. Large Language Model Market, by Offering

• 6.1. Introduction
• 6.2. Services
  • 6.2.1. Consulting
  • 6.2.2. Development & Integration
  • 6.2.3. Support & Maintenance
• 6.3. Software
  • 6.3.1. Closed-source LLM
  • 6.3.2. Open-source LLM

7. Large Language Model Market, by Type

• 7.1. Introduction
• 7.2. Autoregressive Language Models
• 7.3. Encoder-Decoder Models
• 7.4. Multilingual Models
• 7.5. Pre-Trained & Fine-Tuned Models
• 7.6. Transformer-Based Models

8. Large Language Model Market, by Modality

• 8.1. Introduction
• 8.2. Audio
• 8.3. Images
• 8.4. Text
• 8.5. Video

9. Large Language Model Market, by Deployment

• 9.1. Introduction
• 9.2. Cloud
• 9.3. On-premises

10. Large Language Model Market, by Application

• 10.1. Introduction
• 10.2. Chatbots & Virtual Assistant
• 10.3. Code Generation
• 10.4. Content Generation
• 10.5. Customer Service
• 10.6. Language Translation
• 10.7. Sentiment Analysis

11. Large Language Model Market, by Industry Vertical

• 11.1. Introduction
• 11.2. Banking, Financial Services & Insurance
• 11.3. Healthcare & Life Sciences
• 11.4. Information Technology & Telecommunication
• 11.5. Manufacturing
• 11.6. Media & Entertainment
• 11.7. Retail & E-commerce

12. Americas Large Language Model Market

• 12.1. Introduction
• 12.2. Argentina
• 12.3. Brazil
• 12.4. Canada
• 12.5. Mexico
• 12.6. United States

13. Asia-Pacific Large Language Model Market

• 13.1. Introduction
• 13.2. Australia
• 13.3. China
• 13.4. India
• 13.5. Indonesia
• 13.6. Japan
• 13.7. Malaysia
• 13.8. Philippines
• 13.9. Singapore
• 13.10. South Korea
• 13.11. Taiwan
• 13.12. Thailand
• 13.13. Vietnam

14. Europe, Middle East & Africa Large Language Model Market

• 14.1. Introduction
• 14.2. Denmark
• 14.3. Egypt
• 14.4. Finland
• 14.5. France
• 14.6. Germany
• 14.7. Israel
• 14.8. Italy
• 14.9. Netherlands
• 14.10. Nigeria
• 14.11. Norway
• 14.12. Poland
• 14.13. Qatar
• 14.14. Russia
• 14.15. Saudi Arabia
• 14.16. South Africa
• 14.17. Spain
• 14.18. Sweden
• 14.19. Switzerland
• 14.20. Turkey
• 14.21. United Arab Emirates
• 14.22. United Kingdom

15. Competitive Landscape

• 15.1. Market Share Analysis, 2023
• 15.2. FPNV Positioning Matrix, 2023
• 15.3. Competitive Scenario Analysis
  • 15.3.1. Italy's iGenius has introduced Colosseum 355B, a large language model powered by Nvidia
  • 15.3.2. Cerence AI expands collaboration with NVIDIA to advance its cerence automotive large language model (CaLLM) family
  • 15.3.3. Rakuten unveils new AI large language models optimized for Japanese
  • 15.3.4. SAP continues to expand its partnership with Mistral AI by introducing Mistral Large 2
  • 15.3.5. Fujitsu and Cohere launch Takane, a secure Japanese focused large language model for enterprises
  • 15.3.6. Accenture invests in Martian to enhance AI systems with dynamic large language model routing
  • 15.3.7. Lexlegis.ai launch of first large language model to tackle case backlog
  • 15.3.8. Convin enhances Indian contact centers with 7-billion parameter large language model
  • 15.3.9. ISA launches an AI-powered large-language model
  • 15.3.10. Cognizant and Google Cloud through partnership introduces healthcare large language model solutions
• 15.4. Strategy Analysis & Recommendation
  • 15.4.1. Microsoft Corporation
  • 15.4.2. NVIDIA Corporation
  • 15.4.3. Meta Platforms, Inc.
  • 15.4.4. Google LLC by Alphabet Inc.

Companies Mentioned

• 1. AI21 Labs Ltd.
• 2. Alibaba Group Holding Limited
• 3. Amazon Web Services, Inc.
• 4. Anthropic PBC
• 5. Baidu, Inc.
• 6. Cerence Inc.
• 7. Cloudflare, Inc.
• 8. Cognizant Technology Solutions Corporation
• 9. Cohere Inc.
• 10. Eden AI, Inc.
• 11. Elastic N.V.
• 12. Google LLC by Alphabet Inc.
• 13. Huawei Technologies Co., Ltd.
• 14. Hugging Face, Inc.
• 15. iGenius LLC
• 16. International Business Machines Corporation
• 17. Lexlegis
• 18. Luka, Inc.
• 19. Meta Platforms, Inc.
• 20. Microsoft Corporation
• 21. Mistral AI
• 22. Nippon Telegraph and Telephone Corporation
• 23. Numenta, Inc.
• 24. Nvidia Corporation
• 25. OpenAI Inc.
• 26. Rakuten Group, Inc.
• 27. Salesforce, Inc.
• 28. Tencent Holdings Ltd.
• 29. Vectara, Inc.
• 30. Weights and Biases, Inc.
• 31. Zeta Alpha Vector BV