Product Code: GVR-4-68040-454-6
Market Size & Trends:
The global retrieval augmented generation market size was estimated at USD 1,042.7 million in 2023 and is projected to grow at a CAGR of 44.7% from 2024 to 2030. The market is growing rapidly due to advancements in natural language processing (NLP) and the increasing need for intelligent AI systems. Retrieval augmented generation (RAG) models, which combine retrieval-based approaches with generative capabilities, are becoming popular in industries such as customer service, content generation, and research. These models offer enhanced accuracy by accessing external data sources, allowing AI to generate more relevant, context-aware responses.
Companies are turning to RAG to automate complex workflows while maintaining a high level of content quality. The rise of generative AI tools such as ChatGPT has sparked interest in enhancing them with retrieval mechanisms. Retrieval augmented generation (RAG) is particularly suited for applications requiring precision, making it appealing for businesses. This demand is pushing research and development efforts to improve RAG frameworks for diverse use cases.
Enterprise adoption is a significant driver of RAG's expansion as businesses recognize its potential to handle specialized tasks in fields such as healthcare, finance, and legal services. RAG systems are proving valuable for retrieving and generating information from proprietary databases, allowing professionals to make real-time, data-driven decisions. Companies are investing in these models to improve customer experiences and internal operations by integrating them into chatbots, virtual assistants, and knowledge management systems. The availability of cloud-based AI platforms is also making it easier for enterprises to scale RAG solutions across various departments. As a result, more organizations are adopting these models to handle niche requirements. The rising quality and availability of domain-specific datasets further support this growth. The impact is profound, with RAG models improving decision-making and content delivery.
Competition in the retrieval augmented generation market is intensifying as established tech giants and startups alike develop advanced architectures to stay ahead. Cloud service providers are enhancing their RAG offerings by optimizing both retrieval and generation processes for speed and accuracy. There is also a rising interest in open-source RAG frameworks, allowing smaller companies and developers to customize their solutions based on specific needs. This innovation is accelerating RAG's adoption across industries and making it more accessible to a broader range of businesses. New features, such as real-time updating and the ability to pull from dynamic sources, are expanding RAG's use cases. The competitive landscape is fueling rapid innovation, with continuous improvements in RAG model performance. Overall, this market is set to experience substantial growth over the coming years as businesses increasingly recognize its value.
Global Retrieval Augmented Generation Market Report Segmentation
This report forecasts revenue growth at global, regional, and country levels and analyzes the latest industry trends in each of the sub-segments from 2020 to 2030. For this study, Grand View Research has segmented the global retrieval-augmented generation market report based on function, application, deployment, end-use, and region.
- Function Outlook (Revenue, USD Million, 2020 - 2030)
- Document Retrieval
- Response Generation
- Summarization & Reporting
- Recommendation Engines
- Application Outlook (Revenue, USD Million, 2020 - 2030)
- Knowledge Management
- Customer Support & Chatbots
- Legal & Compliance
- Marketing & Sales
- Research & Development
- Content Generation
- Deployment Outlook (Revenue, USD Million, 2020 - 2030)
- Cloud
- On-premises
- End-use Outlook (Revenue, USD Million, 2020 - 2030)
- Healthcare
- Financial Services
- Retail & E-commerce
- IT & Telecommunications
- Education
- Media & Entertainment
- Others
- Regional Outlook (Revenue, USD Million, 2020 - 2030)
- North America
- Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Latin America
- Middle East and Africa (MEA)
Table of Contents
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation and Scope
- 1.2. Market Definition
- 1.3. Research Methodology
- 1.3.1. Information Procurement
- 1.3.2. Information or Data Analysis
- 1.3.3. Market Formulation & Data Visualization
- 1.3.4. Data Validation & Publishing
- 1.4. Research Scope and Assumptions
- 1.4.1. List of Data Sources
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.3. Competitive Insights
Chapter 3. Retrieval Augmented Generation (RAG) Market Variables, Trends, & Scope
- 3.1. Market Introduction/Lineage Outlook
- 3.2. Market Dynamics
- 3.2.1. Market Driver Analysis
- 3.2.2. Market Restraint Analysis
- 3.2.3. Industry Challenge
- 3.3. Retrieval Augmented Generation (RAG) Market Analysis Tools
- 3.3.1. Porter's Analysis
- 3.3.2. PESTEL Analysis
Chapter 4. Retrieval Augmented Generation (RAG) Market: Function Estimates & Trend Analysis
- 4.1. Segment Dashboard
- 4.2. Retrieval Augmented Generation (RAG) Market: Function Movement Analysis, 2023 & 2030 (USD Million)
- 4.3. Document Retrieval
- 4.3.1. Document Retrieval Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 4.4. Response Generation
- 4.4.1. Response Generation Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 4.5. Summarization & Reporting
- 4.5.1. Summarization & Reporting Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 4.6. Recommendation Engines
- 4.6.1. Recommendation Engines Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
Chapter 5. Retrieval Augmented Generation (RAG) Market: Application Estimates & Trend Analysis
- 5.1. Segment Dashboard
- 5.2. Retrieval Augmented Generation (RAG) Market: Application Movement Analysis, 2023 & 2030 (USD Million)
- 5.3. Knowledge Management
- 5.3.1. Knowledge Management Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 5.4. Customer Support & Chatbots
- 5.4.1. Customer Support & Chatbots Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 5.5. Legal & Compliance
- 5.5.1. Legal & Compliance Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 5.6. Customer Support & Chatbots
- 5.6.1. Customer Support & Chatbots Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 5.7. Marketing & Sales
- 5.7.1. Marketing & Sales Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 5.8. Research & Development
- 5.8.1. Research & Development Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 5.9. Content Generation
- 5.9.1. Content Generation Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
Chapter 6. Retrieval Augmented Generation (RAG) Market: Deployment Estimates & Trend Analysis
- 6.1. Segment Dashboard
- 6.2. Retrieval Augmented Generation (RAG) Market: Deployment Movement Analysis, 2023 & 2030 (USD Million)
- 6.3. Cloud
- 6.3.1. Cloud Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 6.4. On-premises
- 6.4.1. On-premises Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
Chapter 7. Retrieval Augmented Generation (RAG) Market: End Use Estimates & Trend Analysis
- 7.1. Segment Dashboard
- 7.2. Retrieval Augmented Generation (RAG) Market: End Use Movement Analysis, 2023 & 2030 (USD Million)
- 7.3. Healthcare
- 7.3.1. Healthcare Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 7.4. Financial Services
- 7.4.1. Financial Services Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 7.5. Retail & E-commerce
- 7.5.1. Retail & E-commerce Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 7.6. IT & Telecommunications
- 7.6.1. IT & Telecommunications Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 7.7. Education
- 7.7.1. Education Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 7.8. Media & Entertainment
- 7.8.1. Media & Entertainment Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
- 7.9. Others
- 7.9.1. Others Retrieval Augmented Generation (RAG) Market Revenue Estimates and Forecasts, 2020 - 2030 (USD Million)
Chapter 8. Retrieval Augmented Generation (RAG) Market: Regional Estimates & Trend Analysis
- 8.1. Retrieval Augmented Generation (RAG) Market Share, By Region, 2023 & 2030 (USD Million)
- 8.2. North America
- 8.2.1. North America Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.2.2. U.S.
- 8.2.2.1. U.S. Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.2.3. Canada
- 8.2.3.1. Canada Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.2.4. Mexico
- 8.2.4.1. Mexico Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.3. Europe
- 8.3.1. Europe Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.3.2. UK
- 8.3.2.1. UK Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.3.3. Germany
- 8.3.3.1. Germany Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.3.4. France
- 8.3.4.1. France Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.4. Asia Pacific
- 8.4.1. Asia Pacific Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.4.2. China
- 8.4.2.1. China Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.4.3. Japan
- 8.4.3.1. Japan Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.4.4. India
- 8.4.4.1. India Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.4.5. South Korea
- 8.4.5.1. South Korea Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.4.6. Australia
- 8.4.6.1. Australia Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.5. Latin America
- 8.5.1. Latin America Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.5.2. Brazil
- 8.5.2.1. Brazil Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.6. Middle East and Africa
- 8.6.1. Middle East and Africa Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.6.2. KSA
- 8.6.2.1. KSA Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.6.3. UAE
- 8.6.3.1. UAE Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
- 8.6.4. South Africa
- 8.6.4.1. South Africa Retrieval Augmented Generation (RAG) Market Estimates and Forecasts, 2020 - 2030 (USD Million)
Chapter 9. Competitive Landscape
- 9.1. Company Categorization
- 9.2. Company Market Positioning
- 9.3. Participant's Overview
- 9.4. Financial Performance
- 9.5. Function Benchmarking
- 9.6. Company Heat Map Analysis
- 9.7. Strategy Mapping
- 9.8. Company Profiles/Listing
- 9.8.1. Anthropic
- 9.8.1.1. Participant's Overview
- 9.8.1.2. Financial Performance
- 9.8.1.3. Product Benchmarking
- 9.8.1.4. Recent Developments
- 9.8.2. Amazon Web Services Inc.
- 9.8.2.1. Participant's Overview
- 9.8.2.2. Financial Performance
- 9.8.2.3. Product Benchmarking
- 9.8.2.4. Recent Developments
- 9.8.3. Clarifai
- 9.8.3.1. Participant's Overview
- 9.8.3.2. Financial Performance
- 9.8.3.3. Product Benchmarking
- 9.8.3.4. Recent Developments
- 9.8.4. Cohere
- 9.8.4.1. Participant's Overview
- 9.8.4.2. Financial Performance
- 9.8.4.3. Product Benchmarking
- 9.8.4.4. Recent Developments
- 9.8.5. Google DeepMind
- 9.8.5.1. Participant's Overview
- 9.8.5.2. Financial Performance
- 9.8.5.3. Product Benchmarking
- 9.8.5.4. Recent Developments
- 9.8.6. Hugging Face
- 9.8.6.1. Participant's Overview
- 9.8.6.2. Financial Performance
- 9.8.6.3. Product Benchmarking
- 9.8.6.4. Recent Developments
- 9.8.7. IBM Watson
- 9.8.7.1. Participant's Overview
- 9.8.7.2. Financial Performance
- 9.8.7.3. Product Benchmarking
- 9.8.7.4. Recent Developments
- 9.8.8. Informatica
- 9.8.8.1. Participant's Overview
- 9.8.8.2. Financial Performance
- 9.8.8.3. Product Benchmarking
- 9.8.8.4. Recent Developments
- 9.8.9. Meta AI (Facebook AI)
- 9.8.9.1. Participant's Overview
- 9.8.9.2. Financial Performance
- 9.8.9.3. Product Benchmarking
- 9.8.9.4. Recent Developments
- 9.8.10. Microsoft
- 9.8.10.1. Participant's Overview
- 9.8.10.2. Financial Performance
- 9.8.10.3. Product Benchmarking
- 9.8.10.4. Recent Developments
- 9.8.11. Neeva
- 9.8.11.1. Participant's Overview
- 9.8.11.2. Financial Performance
- 9.8.11.3. Product Benchmarking
- 9.8.11.4. Recent Developments
- 9.8.12. OpenAI
- 9.8.12.1. Participant's Overview
- 9.8.12.2. Financial Performance
- 9.8.12.3. Product Benchmarking
- 9.8.12.4. Recent Developments
- 9.8.13. Semantic Scholar (AI2)
- 9.8.13.1. Participant's Overview
- 9.8.13.2. Financial Performance
- 9.8.13.3. Product Benchmarking
- 9.8.13.4. Recent Developments