TABLE OF CONTENTS
1. EXECUTIVE SUMMARY
1.1. Market Attractiveness Analysis
1.1.1. Global Generative AI Market, by Component
1.1.2. Global Generative AI Market, by Technology
1.1.3. Global Generative AI Market, by End Use
1.1.4. Global Generative AI Market, by Industry Vertical
1.1.5. Global Generative AI Market, by Region
2. MARKET INTRODUCTION
2.1. Definition
2.2. Scope of the Study
2.3. Market Structure
2.4. Key Buying Criteria
2.5. Macro Factor Indicator Analysis
3. RESEARCH METHODOLOGY
3.1. Research Process
3.2. Primary Research
3.3. Secondary Research
3.4. Market Size Estimation
3.5. Forecast Model
3.6. List of Assumptions
4. MARKET DYNAMICS
4.1. Introduction
4.2. Drivers
4.2.1. Increasing use of machine learning across business verticals
4.2.2. Offering shortened versions of conversations, articles, emails, and webpages
4.2.3. Drivers Impact Analysis
4.3. Restraints
4.3.1. Lack of skilled professionals
4.3.2. High capital investment
4.3.3. Restraints Impact Analysis
4.4. Opportunities
4.4.1. Rising adoption of data-centric production approach
4.4.2. Increase revenue, reduce costs, improve productivity, and better manage risk
4.5. Challenges
4.5.1. Not designed to be compliant with General Data Protection Regulation (GDPR) and other copyright laws
4.5.2. Generative AI and ChatGPT models are unpredictable
4.5.3. Generative AI systems sometimes produce inaccurate and fabricated answers.
4.5.4. There are currently no verifiable data governance and protection assurances regarding confidential enterprise information
5. MARKET FACTOR ANALYSIS
5.1. PESTEL Analysis
5.2. SWOT Analysis
5.3. Value Chain Analysis/Supply Chain Analysis
5.4. Porter’s Five Forces Model
5.5. Bargaining Power of Suppliers
5.6. Bargaining Power of Buyers
5.7. Threat of New Entrants
5.8. Threat of Substitutes
5.9. Intensity of Rivalry
6. GLOBAL GENERATIVE AI MARKET, BY COMPONENT
6.1. Introduction
6.2. Software
6.3. Solution
7. GLOBAL GENERATIVE AI MARKET, BY TECHNOLOGY
7.1. Introduction
7.2. Generative Adversarial Networks (GANs)
7.3. Transformers
7.4. Variational Auto-encoders (VAEs)
7.5. Diffusion
7.6. NeRFs
8. GLOBAL GENERATIVE AI MARKET, BY END USE
8.1. Introduction
8.2. Large Language Model (LLM)
8.3. Content Generation
8.4. Code Generation
8.5. Video Creation
8.6. Image and Art Generation
8.7. Others
9. GLOBAL GENERATIVE AI MARKET, BY INDUSTRY VERTICAL
9.1. Introduction
9.2. Manufacturing
9.3. IT & Telecommunication
9.4. Healthcare
9.5. Automotive & Transportation
9.6. Gaming
9.7. Academic and Research Institutions
9.8. BFSI
9.9. Aerospace & Defence
9.10. Others
10. GLOBAL GENERATIVE AI MARKET SIZE ESTIMATION & FORECAST, BY REGION
10.1. Introduction
10.2. North America
10.2.1. Market Estimates & Forecast, by Country, 2019-2030
10.2.2. Market Estimates & Forecast, by Component, 2019-2030
10.2.3. Market Estimates & Forecast, by Technology, 2019-2030
10.2.4. Market Estimates & Forecast, by End Use, 2019-2030
10.2.5. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.2.6. US
10.2.6.1. Market Estimates & Forecast, by Component, 2019-2030
10.2.6.2. Market Estimates & Forecast, by Technology, 2019-2030
10.2.6.3. Market Estimates & Forecast, by End Use, 2019-2030
10.2.6.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.2.7. Canada
10.2.7.1. Market Estimates & Forecast, by Component, 2019-2030
10.2.7.2. Market Estimates & Forecast, by Technology, 2019-2030
10.2.7.3. Market Estimates & Forecast, by End Use, 2019-2030
10.2.7.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.2.8. Mexico
10.2.8.1. Market Estimates & Forecast, by Component, 2019-2030
10.2.8.2. Market Estimates & Forecast, by Technology, 2019-2030
10.2.8.3. Market Estimates & Forecast, by End Use, 2019-2030
10.2.8.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.3. Europe
10.3.1. Market Estimates & Forecast, by Country, 2019-2030
10.3.2. Market Estimates & Forecast, by Component, 2019-2030
10.3.3. Market Estimates & Forecast, by Technology, 2019-2030
10.3.4. Market Estimates & Forecast, by End Use, 2019-2030
10.3.5. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.3.6. UK
10.3.6.1. Market Estimates & Forecast, by Component, 2019-2030
10.3.6.2. Market Estimates & Forecast, by Technology, 2019-2030
10.3.6.3. Market Estimates & Forecast, by End Use, 2019-2030
10.3.6.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.3.7. Germany
10.3.7.1. Market Estimates & Forecast, by Component, 2019-2030
10.3.7.2. Market Estimates & Forecast, by Technology, 2019-2030
10.3.7.3. Market Estimates & Forecast, by End Use, 2019-2030
10.3.7.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.3.8. France
10.3.8.1. Market Estimates & Forecast, by Component, 2019-2030
10.3.8.2. Market Estimates & Forecast, by Technology, 2019-2030
10.3.8.3. Market Estimates & Forecast, by End Use, 2019-2030
10.3.8.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.3.9. Rest of Europe
10.3.9.1. Market Estimates & Forecast, by Component, 2019-2030
10.3.9.2. Market Estimates & Forecast, by Technology, 2019-2030
10.3.9.3. Market Estimates & Forecast, by End Use, 2019-2030
10.3.9.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.4. Asia-Pacific
10.4.1. Market Estimates & Forecast, by Country, 2019-2030
10.4.2. Market Estimates & Forecast, by Component, 2019-2030
10.4.3. Market Estimates & Forecast, by Technology, 2019-2030
10.4.4. Market Estimates & Forecast, by End Use, 2019-2030
10.4.5. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.4.6. China
10.4.6.1. Market Estimates & Forecast, by Component, 2019-2030
10.4.6.2. Market Estimates & Forecast, by Technology, 2019-2030
10.4.6.3. Market Estimates & Forecast, by End Use, 2019-2030
10.4.6.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.4.7. Japan
10.4.7.1. Market Estimates & Forecast, by Component, 2019-2030
10.4.7.2. Market Estimates & Forecast, by Technology, 2019-2030
10.4.7.3. Market Estimates & Forecast, by End Use, 2019-2030
10.4.7.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.4.8. India
10.4.8.1. Market Estimates & Forecast, by Component, 2019-2030
10.4.8.2. Market Estimates & Forecast, by Technology, 2019-2030
10.4.8.3. Market Estimates & Forecast, by End Use, 2019-2030
10.4.8.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.4.9. Rest of Asia-Pacific
10.4.9.1. Market Estimates & Forecast, by Component, 2019-2030
10.4.9.2. Market Estimates & Forecast, by Technology, 2019-2030
10.4.9.3. Market Estimates & Forecast, by End Use, 2019-2030
10.4.9.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.5. Rest of the World
10.5.1. Middle East & Africa
10.5.1.1. Market Estimates & Forecast, by Component, 2019-2030
10.5.1.2. Market Estimates & Forecast, by Technology, 2019-2030
10.5.1.3. Market Estimates & Forecast, by End Use, 2019-2030
10.5.1.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
10.5.2. South America
10.5.2.1. Market Estimates & Forecast, by Component, 2019-2030
10.5.2.2. Market Estimates & Forecast, by Technology, 2019-2030
10.5.2.3. Market Estimates & Forecast, by End Use, 2019-2030
10.5.2.4. Market Estimates & Forecast, by Industry Vertical, 2019-2030
11. COMPETITIVE LANDSCAPE
11.1. Introduction
11.2. Key Developments & Growth Strategies
11.3. Competitor Benchmarking
11.4. Vendor Share Analysis, 2022 (% Share)
12. COMPANY PROFILES
12.1. Microsoft (US)
12.2. IBM (US)
12.3. Google (US)
12.4. AWS (US)
12.5. META (US)
12.6. Adobe (US)
12.7. OpenAI (US)
12.8. Simplified (US)
12.9. Insilico Medicine (Hong Kong)
12.10. Genie AI (UK)
12.11. Lightricks (Israel)
12.12. Lumen5 (Canada)
12.13. GIPHY (US)
12.14. Dialpad (US)
12.15. Persado (US)
12.16. Codacy (Portugal)
12.17. Paige.AI (US)
12.18. Riffusion (US)
12.19. Play.ht (India)
12.20. Speechify (US)
12.21. Media.io (France)
12.22. Midjourney (US)
12.23. FireFlies (US)
12.24. Brandmark.io (Netherlands)
12.25. Morphis Technologies (Portugal)
12.26. Synthesia (UK)
12.27. Mostly Al (Austria)
12.28. Veesual (France)
12.29. Deep AI (US)
12.30. Galileo (US)
12.31. Excel Formula Bot (Florida)
12.32. JetBrains (Czech Republic)
12.33. Character.AI (US)
12.34. GFP-GAN (US)
12.35. Fontjoy (Italy)
12.36. Eleuther AI (US)
12.37. Starry AI (US)
12.38. Magic Studio (US)
12.38.1. Company Overview
12.38.2. Financial Overview
12.38.3. Solution/Services Offered
12.38.4. Key Developments
12.38.5. SWOT Analysis
12.38.6. Key Strategies
NOTE:
This table of content is tentative and subject to change as the research progresses.
ï‚¡ In section 12, only the top 10 companies will be profiled. Each company will be profiled based on the Market Overview, Financials, Service Portfolio, Business Strategies, and Recent Developments parameters.
 The companies are selected based on two broad criteria¬– strength of product portfolio and excellence in business strategies.
 Key parameters considered for evaluating strength of the vendor’s product portfolio are industry experience, product capabilities/features, innovations/R&D investment, flexibility to customize the product, ability to integrate with other Platforms, pre- and post-sale services, and customer ratings/feedback.
 Key parameters considered for evaluating a vendor’s excellence in business strategy are its market share, global presence, customer base, partner ecoPlatform (technology alliances/resellers/distributors), acquisitions, and marketing strategies/investments.
ï‚¡ The financial details of the company cannot be provided if the information is not available in the public domain and or from reliable sources.
