Large Language Model Market
Large Language Model Market Forecasts to 2030 - Global Analysis By Offering (Software, Services and Other Offerings), Architecture (Autoregressive Language Models, Single-headed Autoregressive Language Models and Other Architectures), Modality, Application, End User and By Geography
|
Years Covered |
2021-2030 |
|
Estimated Year Value (2023) |
US $1.6 BN |
|
Projected Year Value (2030) |
US $13.08 BN |
|
CAGR (2023 - 2030) |
35% |
|
Regions Covered |
North America, Europe, Asia Pacific, South America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Mexico, Germany, UK, Italy, France, Spain, Japan, China, India, Australia, New Zealand, South Korea, Rest of Asia Pacific, South America, Argentina, Brazil, Chile, Middle East & Africa, Saudi Arabia, UAE, Qatar, and South Africa |
|
Largest Market |
North America |
|
Highest Growing Market |
Asia Pacific |
According to Stratistics MRC, the Global Large Language Model Market is accounted for $1.6 billion in 2023 and is expected to reach $13.08 billion by 2030 growing at a CAGR of 35.0% during the forecast period. A large language model (LLM) is a type of artificial intelligence designed to understand and generate human-like text based on the vast amount of data it has been trained on. These models, like GPT-3, are built on deep learning architectures, particularly transformers, enabling them to process and generate text at an impressive scale. LLMs excel at various language tasks such as translation, summarization, and question-answering, often achieving human or superhuman performance on benchmark tests. They learn patterns and relationships from the data they are trained on, allowing them to generate coherent and contextually relevant responses across a wide range of topics.
Market Dynamics:
Driver:
Advancements in AI and machine learning
Advancements in AI and machine learning have propelled the large language model (LLM) market by enhancing the capabilities and performance of these models. With breakthroughs in algorithms, data processing, and computational power, LLMs can now understand and generate human-like text with unprecedented accuracy and coherence. These advancements have led to applications in various fields, from natural language processing to content generation and translation. Additionally, the scalability and efficiency of LLMs have improved, enabling businesses to leverage them for diverse tasks such as customer service automation, data analysis, and personalized content creation.
Restraint:
Bias and fairness
Bias and fairness constraints in large language models pertain to ensuring equitable and unbiased outcomes in their applications. This involves identifying and mitigating inherent biases within the data used to train these models. Addressing bias involves techniques such as data preprocessing, algorithmic adjustments, and diverse representation in training datasets. Fairness restraints aim to prevent discriminatory outcomes in LLM applications, particularly in sensitive areas like hiring, lending, or content moderation. Implementing these constraints requires a multidisciplinary approach involving ethics, sociology, and computer science to foster responsible and equitable deployment of LLMs in society.
Opportunity:
Content generation and personalization
The Large Language Model market offers significant opportunities in content generation and personalization. With the ability to comprehend and generate human-like text, LLMs can automate content creation across various industries, from journalism to marketing. Additionally, LLMs enable personalized experiences by tailoring content to individual preferences, behaviors, and demographics. This level of customization enhances user engagement and satisfaction, driving higher conversion rates and brand loyalty. Moreover, LLMs can dynamically adapt content based on real-time data, ensuring relevance and timeliness. Leveraging these capabilities, businesses can efficiently scale content production while delivering highly targeted messaging to their audience.
Threat:
Job displacement
The emergence of Large Language Models poses a significant job displacement threat due to their ability to automate various tasks traditionally performed by humans. LLMs can swiftly process vast amounts of text, potentially replacing roles in content creation, translation, customer service, and more. As businesses adopt LLMs for efficiency gains, there's a risk of reducing the demand for human labor in these sectors. This displacement could lead to job losses, particularly for roles that involve repetitive or routine cognitive tasks. Adapting to this shift may require upskilling or transitioning to roles that complement LLM capabilities rather than compete with them.
Covid-19 Impact:
The COVID-19 pandemic significantly accelerated the demand for large language models (LLMs) in various sectors. With remote work and digital transformation becoming imperative, organizations increasingly rely on LLMs for automating tasks, enhancing customer service, and streamlining operations. This surge in demand led to increased investments in LLM research and development, as well as adoption across industries such as healthcare, finance, and education. However, supply chain disruptions and economic uncertainties caused by the pandemic also posed challenges for LLM manufacturers and developers.
The services segment is expected to be the largest during the forecast period
The services segment in the large language model market is experiencing robust growth due to several factors. As organizations increasingly recognize the value of LLMs in improving efficiency and decision-making, there's a rising demand for specialized services to implement and customize these models to specific business needs. The complexity of LLM technology necessitates ongoing support and maintenance, driving the need for consulting, training, and managed services. Additionally, as LLMs become more integral to various industries, service providers are expanding their offerings to include domain-specific expertise, such as healthcare or finance, further fueling market growth.
The data analysis and business intelligence segment is expected to have the highest CAGR during the forecast period
The growth of the Data Analysis and Business Intelligence segment is driven by the increasing demand for advanced data processing and interpretation capabilities. LLMs offer powerful tools for extracting insights from vast datasets, enabling businesses to make data-driven decisions with greater precision and efficiency. As companies across industries recognize the value of harnessing data for competitive advantage, the adoption of LLMs for data analysis and business intelligence is on the rise. The evolution of natural language processing techniques within LLMs enhances their ability to understand and interpret complex data, further fueling market growth.
Region with largest share:
The growth of the Large Language Model market in North America can be attributed to the region’s presence of several tech giants and leading AI research institutions, fostering innovation and development in language modeling technologies. The increasing demand for natural language processing applications across various sectors, such as healthcare, finance, and customer service, is driving the adoption of LLMs. North America boasts a robust infrastructure for cloud computing and data centers, facilitating the deployment and scalability of LLMs. Additionally, the presence of a skilled workforce and favorable government policies supporting AI research and development further propel the growth of the LLM market in the region.
Region with highest CAGR:
The Asia-Pacific region has seen a significant surge in the adoption and growth of large language models (LLMs) in recent years. This growth can be attributed to several factors, including the region's increasing technological infrastructure, burgeoning demand for AI-driven solutions across various industries such as finance, healthcare, and e-commerce, as well as a growing pool of skilled AI talent. Government initiatives aimed at promoting AI research and development have further fueled the expansion of the LLM market in the Asia Pacific. Furthermore, the cultural diversity and vast linguistic landscape of the region present unique challenges that LLMs are well-equipped to address, driving their widespread adoption.
Key players in the market
Some of the key players in Large Language Model market include AI21 Labs, Alibaba, Amazon, Anthropic, Baidu, Cohere, Crowdworks, Google, Huawei, Meta, Microsoft, Naver, NEC, OpenAI, Technology Innovation Institute (TII), Tencent and Yandex.
Key Developments:
In April 2024, Google is currently working on a centralized location-sharing feature for Android users. This new feature, known as ""Google Location Sharing,"" was recently discovered in updates to Google Play Services. The primary objective of this development is to consolidate all active location-sharing services associated with a user's Google account, into one accessible page within the Settings menu.
In April 2023, Microsoft announced that it will invest US$2.9 billion over the next two years to increase its hyperscale cloud computing and AI infrastructure in Japan. It will also expand its digital skilling programs with the goal of providing AI skilling to more than 3 million people over the next three years by opening its first Microsoft Research Asia lab in Japan, and deepening its cybersecurity collaboration with the Government of Japan.
Offerings Covered:
• Software
• Services
• Other Offerings
Architectures Covered:
• Autoregressive Language Models
• Single-headed Autoregressive Language Models
• Multi-headed Autoregressive Language Models
• Autoencoding Language Models
• Vanilla Autoencoding Language Models
• Optimized Autoencoding Language Models
• Hybrid Language Models
• Text-to-Text Language Models
• Pretraining-finetuning Models
• Other Architectures
Modalities Covered:
• Text
• Code
• Image
• Video
• Other Modalities
Applications Covered:
• Information Retrieval
• Language Translation And Localization
• Content Generation And Curation
• Code Generation
• Customer Service Automation
• Data Analysis And Business Intelligence
• Other Applications
End Users Covered:
• Information Technology (IT)
• Healthcare & Life Sciences
• Law Firms
• Manufacturing
• Education
• Retail
• Media & Entertainment
• Other End-users
Regions Covered:
• North America
o US
o Canada
o Mexico
• Europe
o Germany
o UK
o Italy
o France
o Spain
o Rest of Europe
• Asia Pacific
o Japan
o China
o India
o Australia
o New Zealand
o South Korea
o Rest of Asia Pacific
• South America
o Argentina
o Brazil
o Chile
o Rest of South America
• Middle East & Africa
o Saudi Arabia
o UAE
o Qatar
o South Africa
o Rest of Middle East & Africa
What our report offers:
- Market share assessments for the regional and country-level segments
- Strategic recommendations for the new entrants
- Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
- Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
- Strategic recommendations in key business segments based on the market estimations
- Competitive landscaping mapping the key common trends
- Company profiling with detailed strategies, financials, and recent developments
- Supply chain trends mapping the latest technological advancements
Free Customization Offerings:
All the customers of this report will be entitled to receive one of the following free customization options:
• Company Profiling
o Comprehensive profiling of additional market players (up to 3)
o SWOT Analysis of key players (up to 3)
• Regional Segmentation
o Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances
Table of Contents
1 Executive Summary
2 Preface
2.1 Abstract
2.2 Stake Holders
2.3 Research Scope
2.4 Research Methodology
2.4.1 Data Mining
2.4.2 Data Analysis
2.4.3 Data Validation
2.4.4 Research Approach
2.5 Research Sources
2.5.1 Primary Research Sources
2.5.2 Secondary Research Sources
2.5.3 Assumptions
3 Market Trend Analysis
3.1 Introduction
3.2 Drivers
3.3 Restraints
3.4 Opportunities
3.5 Threats
3.6 Application Analysis
3.7 End User Analysis
3.8 Emerging Markets
3.9 Impact of Covid-19
4 Porters Five Force Analysis
4.1 Bargaining power of suppliers
4.2 Bargaining power of buyers
4.3 Threat of substitutes
4.4 Threat of new entrants
4.5 Competitive rivalry
5 Global Large Language Model Market, By Offering
5.1 Introduction
5.2 Software
5.3 Services
5.3.1 Consulting
5.3.2 LLM Development
5.3.3 Integration
5.3.4 LLM Fine-tuning
5.3.4.1 Full Fine-tuning
5.3.4.2 Retrieval-augmented Generation (RAG)
5.3.4.3 Adapter-based Parameter Efficient Tuning
5.3.5 LLM-backed App Development
5.3.6 Prompt Engineering
5.3.7 Support and Maintenance
5.4 Other Offerings
6 Global Large Language Model Market, By Architecture
6.1 Introduction
6.2 Autoregressive Language Models
6.3 Single-headed Autoregressive Language Models
6.4 Multi-headed Autoregressive Language Models
6.5 Autoencoding Language Models
6.6 Vanilla Autoencoding Language Models
6.7 Optimized Autoencoding Language Models
6.8 Hybrid Language Models
6.9 Text-to-Text Language Models
6.10 Pretraining-finetuning Models
6.11 Other Architectures
7 Global Large Language Model Market, By Modality
7.1 Introduction
7.2 Text
7.3 Code
7.4 Image
7.5 Video
7.6 Other Modalities
8 Global Large Language Model Market, By Application
8.1 Introduction
8.2 Information Retrieval
8.3 Language Translation And Localization
8.3.1 Multilingual Translation
8.3.2 Localization Services
8.4 Content Generation And Curation
8.4.1 Automated Journalism And Article Writing
8.4.2 Creative Writing
8.5 Code Generation
8.6 Customer Service Automation
8.6.1 Chatbots And Virtual Assistants
8.6.2 Sales And Marketing Automation
8.6.3 Personalized Recommendation
8.7 Data Analysis And Business Intelligence
8.7.1 Sentiment Analysis
8.7.2 Business Reporting And Market Analysis
8.8 Other Applications
9 Global Large Language Model Market, By End User
9.1 Introduction
9.2 Information Technology (IT)
9.3 Healthcare & Life Sciences
9.4 Law Firms
9.5 Manufacturing
9.6 Education
9.7 Retail
9.8 Media & Entertainment
9.9 Other End-users
10 Global Large Language Model Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 Europe
10.3.1 Germany
10.3.2 UK
10.3.3 Italy
10.3.4 France
10.3.5 Spain
10.3.6 Rest of Europe
10.4 Asia Pacific
10.4.1 Japan
10.4.2 China
10.4.3 India
10.4.4 Australia
10.4.5 New Zealand
10.4.6 South Korea
10.4.7 Rest of Asia Pacific
10.5 South America
10.5.1 Argentina
10.5.2 Brazil
10.5.3 Chile
10.5.4 Rest of South America
10.6 Middle East & Africa
10.6.1 Saudi Arabia
10.6.2 UAE
10.6.3 Qatar
10.6.4 South Africa
10.6.5 Rest of Middle East & Africa
11 Key Developments
11.1 Agreements, Partnerships, Collaborations and Joint Ventures
11.2 Acquisitions & Mergers
11.3 New Product Launch
11.4 Expansions
11.5 Other Key Strategies
12 Company Profiling
12.1 AI21 Labs
12.2 Alibaba
12.3 Amazon
12.4 Anthropic
12.5 Baidu
12.6 Cohere
12.7 Crowdworks
12.8 Google
12.9 Huawei
12.10 Meta
12.11 Microsoft
12.12 Naver
12.13 NEC
12.14 OpenAI
12.15 Technology Innovation Institute (TII)
12.16 Tencent
12.17 Yandex
List of Tables
1 Global Large Language Model Market Outlook, By Region (2021-2030) ($MN)
2 Global Large Language Model Market Outlook, By Offering (2021-2030) ($MN)
3 Global Large Language Model Market Outlook, By Software (2021-2030) ($MN)
4 Global Large Language Model Market Outlook, By Services (2021-2030) ($MN)
5 Global Large Language Model Market Outlook, By Consulting (2021-2030) ($MN)
6 Global Large Language Model Market Outlook, By LLM Development (2021-2030) ($MN)
7 Global Large Language Model Market Outlook, By Integration (2021-2030) ($MN)
8 Global Large Language Model Market Outlook, By LLM Fine-tuning (2021-2030) ($MN)
9 Global Large Language Model Market Outlook, By Full Fine-tuning (2021-2030) ($MN)
10 Global Large Language Model Market Outlook, By Retrieval-augmented Generation (RAG) (2021-2030) ($MN)
11 Global Large Language Model Market Outlook, By Adapter-based Parameter Efficient Tuning (2021-2030) ($MN)
12 Global Large Language Model Market Outlook, By LLM-backed App Development (2021-2030) ($MN)
13 Global Large Language Model Market Outlook, By Prompt Engineering (2021-2030) ($MN)
14 Global Large Language Model Market Outlook, By Support and Maintenance (2021-2030) ($MN)
15 Global Large Language Model Market Outlook, By Other Offerings (2021-2030) ($MN)
16 Global Large Language Model Market Outlook, By Architecture (2021-2030) ($MN)
17 Global Large Language Model Market Outlook, By Autoregressive Language Models (2021-2030) ($MN)
18 Global Large Language Model Market Outlook, By Single-headed Autoregressive Language Models (2021-2030) ($MN)
19 Global Large Language Model Market Outlook, By Multi-headed Autoregressive Language Models (2021-2030) ($MN)
20 Global Large Language Model Market Outlook, By Autoencoding Language Models (2021-2030) ($MN)
21 Global Large Language Model Market Outlook, By Vanilla Autoencoding Language Models (2021-2030) ($MN)
22 Global Large Language Model Market Outlook, By Optimized Autoencoding Language Models (2021-2030) ($MN)
23 Global Large Language Model Market Outlook, By Hybrid Language Models (2021-2030) ($MN)
24 Global Large Language Model Market Outlook, By Text-to-Text Language Models (2021-2030) ($MN)
25 Global Large Language Model Market Outlook, By Pretraining-finetuning Models (2021-2030) ($MN)
26 Global Large Language Model Market Outlook, By Other Architectures (2021-2030) ($MN)
27 Global Large Language Model Market Outlook, By Modality (2021-2030) ($MN)
28 Global Large Language Model Market Outlook, By Text (2021-2030) ($MN)
29 Global Large Language Model Market Outlook, By Code (2021-2030) ($MN)
30 Global Large Language Model Market Outlook, By Image (2021-2030) ($MN)
31 Global Large Language Model Market Outlook, By Video (2021-2030) ($MN)
32 Global Large Language Model Market Outlook, By Other Modalities (2021-2030) ($MN)
33 Global Large Language Model Market Outlook, By Application (2021-2030) ($MN)
34 Global Large Language Model Market Outlook, By Information Retrieval (2021-2030) ($MN)
35 Global Large Language Model Market Outlook, By Language Translation And Localization (2021-2030) ($MN)
36 Global Large Language Model Market Outlook, By Multilingual Translation (2021-2030) ($MN)
37 Global Large Language Model Market Outlook, By Localization Services (2021-2030) ($MN)
38 Global Large Language Model Market Outlook, By Content Generation And Curation (2021-2030) ($MN)
39 Global Large Language Model Market Outlook, By Automated Journalism And Article Writing (2021-2030) ($MN)
40 Global Large Language Model Market Outlook, By Creative Writing (2021-2030) ($MN)
41 Global Large Language Model Market Outlook, By Code Generation (2021-2030) ($MN)
42 Global Large Language Model Market Outlook, By Customer Service Automation (2021-2030) ($MN)
43 Global Large Language Model Market Outlook, By Chatbots And Virtual Assistants (2021-2030) ($MN)
44 Global Large Language Model Market Outlook, By Sales And Marketing Automation (2021-2030) ($MN)
45 Global Large Language Model Market Outlook, By Personalized Recommendation (2021-2030) ($MN)
46 Global Large Language Model Market Outlook, By Data Analysis And Business Intelligence (2021-2030) ($MN)
47 Global Large Language Model Market Outlook, By Sentiment Analysis (2021-2030) ($MN)
48 Global Large Language Model Market Outlook, By Business Reporting And Market Analysis (2021-2030) ($MN)
49 Global Large Language Model Market Outlook, By Other Applications (2021-2030) ($MN)
50 Global Large Language Model Market Outlook, By End User (2021-2030) ($MN)
51 Global Large Language Model Market Outlook, By Information Technology (IT) (2021-2030) ($MN)
52 Global Large Language Model Market Outlook, By Healthcare & Life Sciences (2021-2030) ($MN)
53 Global Large Language Model Market Outlook, By Law Firms (2021-2030) ($MN)
54 Global Large Language Model Market Outlook, By Manufacturing (2021-2030) ($MN)
55 Global Large Language Model Market Outlook, By Education (2021-2030) ($MN)
56 Global Large Language Model Market Outlook, By Retail (2021-2030) ($MN)
57 Global Large Language Model Market Outlook, By Media & Entertainment (2021-2030) ($MN)
58 Global Large Language Model Market Outlook, By Other End-users (2021-2030) ($MN)
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
List of Figures
RESEARCH METHODOLOGY
We at ‘Stratistics’ opt for an extensive research approach which involves data mining, data validation, and data analysis. The various research sources include in-house repository, secondary research, competitor’s sources, social media research, client internal data, and primary research.
Our team of analysts prefers the most reliable and authenticated data sources in order to perform the comprehensive literature search. With access to most of the authenticated data bases our team highly considers the best mix of information through various sources to obtain extensive and accurate analysis.
Each report takes an average time of a month and a team of 4 industry analysts. The time may vary depending on the scope and data availability of the desired market report. The various parameters used in the market assessment are standardized in order to enhance the data accuracy.
Data Mining
The data is collected from several authenticated, reliable, paid and unpaid sources and is filtered depending on the scope & objective of the research. Our reports repository acts as an added advantage in this procedure. Data gathering from the raw material suppliers, distributors and the manufacturers is performed on a regular basis, this helps in the comprehensive understanding of the products value chain. Apart from the above mentioned sources the data is also collected from the industry consultants to ensure the objective of the study is in the right direction.
Market trends such as technological advancements, regulatory affairs, market dynamics (Drivers, Restraints, Opportunities and Challenges) are obtained from scientific journals, market related national & international associations and organizations.
Data Analysis
From the data that is collected depending on the scope & objective of the research the data is subjected for the analysis. The critical steps that we follow for the data analysis include:
- Product Lifecycle Analysis
- Competitor analysis
- Risk analysis
- Porters Analysis
- PESTEL Analysis
- SWOT Analysis
The data engineering is performed by the core industry experts considering both the Marketing Mix Modeling and the Demand Forecasting. The marketing mix modeling makes use of multiple-regression techniques to predict the optimal mix of marketing variables. Regression factor is based on a number of variables and how they relate to an outcome such as sales or profits.
Data Validation
The data validation is performed by the exhaustive primary research from the expert interviews. This includes telephonic interviews, focus groups, face to face interviews, and questionnaires to validate our research from all aspects. The industry experts we approach come from the leading firms, involved in the supply chain ranging from the suppliers, distributors to the manufacturers and consumers so as to ensure an unbiased analysis.
We are in touch with more than 15,000 industry experts with the right mix of consultants, CEO's, presidents, vice presidents, managers, experts from both supply side and demand side, executives and so on.
The data validation involves the primary research from the industry experts belonging to:
- Leading Companies
- Suppliers & Distributors
- Manufacturers
- Consumers
- Industry/Strategic Consultants
Apart from the data validation the primary research also helps in performing the fill gap research, i.e. providing solutions for the unmet needs of the research which helps in enhancing the reports quality.
For more details about research methodology, kindly write to us at info@strategymrc.com
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