Global Generative AI Market Size is valued at USD 20.10 billion in 2024 and is predicted to reach USD 415.45 billion by the year 2031 at a 35.5% CAGR during the forecast period for 2025-2034.
Any computer-generated voice can sound like a real person using generative AI. One of the most well-known and influential AI text-to-speech generators is Synthesis, and anyone may use it to produce a professional AI voiceover or video quickly.
The desire to minimize size while enhancing vehicle performance and the rising need for sophisticated manufacturing with complicated designs are anticipated to fuel the expansion of the worldwide generative AI market. It forces automakers to spend more on R&D and employ generative design, which promotes market expansion. Factors associated with the developing uses of technologies like super-resolution, text-to-image conversion, and text-to-video conversion, as well as the growing need to modernize workflow across organizations, are driving an increase in the need for generative AI applications across industries.
The growing product usage of 3D printing technologies to make a variety of products, including organic molecules and prosthetic limbs, from scratch is a significant growth-inducing element in the healthcare sector.
Additionally, the market is being propelled forward by the growing use of generative AI, which aids chatbots in having fruitful dialogues with users and raising their satisfaction levels. An open-domain application called a generative chatbot creates unique phrase combinations rather than choosing from pre-written responses. Due to the numerous companies continuously creating and experimenting with incorporating generative AI into their services and products, the industry is predicted to have exciting growth potential. The increased use of generative AI for creating virtual worlds in the metaverse will boost the growth of the worldwide generative AI industry.
The Generative AI market is segmented by type, technology, offering and application. Based on type, the market is segmented into visual, audio, text-based, and others. Technology segment includes generative adversarial network (GAN), variational autoencoder (VAE), transformer, and diffusion network. The offering segment includes natural language processing (NLP), machine learning-based predictive modeling, computer vision, robotics and automation, and augmented reality (AR) and virtual reality (VR). Application segment includes content creation and marketing, human resource management, research and development, and finance.
The North American generative AI market is expected to record the highest market share in revenue shortly. This can be attributed to the strong focus on the environment in the region, with the increasing adoption of generative AI in different industries, including food & beverages, personal care, packaging, automotive, and others. In addition, the region's chemical industry is focusing on producing generative AI to develop sustainable and environmentally friendly solutions.
Growing demand for bio-based components across industries and widespread adoption of generative AI in the production of intermediate chemicals in the region are factors increasing the growth of the target market in the region. In addition, Asia Pacific is projected to grow rapidly in the global generative AI market. Due to the expanding use of pseudo-imagination and banking frauds, the trend is anticipated to continue during the projection period. Additionally, businesses like Meta, Google LLC, and Microsoft are projected to propel the growth of the generative AI industry.
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Report Attribute |
Specifications |
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Market size value in 2024 |
USD 20.10 Bn |
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Revenue Forecast in 2034 |
USD 415.45 Bn |
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Growth rate CAGR |
CAGR of 35.5% from 2025 to 2034 |
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Quantitative units |
Representation of revenue in US$ billion and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market statistics, growth prospects, and trends |
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Segments Covered |
By Type, Technology, Offering and Application |
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Regional scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South Korea; Southeast Asia |
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Competitive Landscape |
OpenAI, Google DeepMind, Amazon.com, Inc., Adobe, IBM, Microsoft, Meta, Salesforce, Inc., Intel Corporation, Synthesia Limited., SAMSUNG, NVIDIA Corporation, Cohere, Anthropic PBC, Inflection, Other Prominent Players. |
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Customization scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing and available payment methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Generative AI Market Snapshot
Chapter 4. Global Generative AI Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Type Estimates & Trend Analysis
5.1. by Type & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Type:
5.2.1. Visual
5.2.2. Audio
5.2.3. Text-Based
5.2.4. Others
Chapter 6. Market Segmentation 2: by Technology Estimates & Trend Analysis
6.1. by Technology & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Technology:
6.2.1. Generative Adversarial Network (GAN)
6.2.2. Variational Autoencoder (VAE)
6.2.3. Transformer
6.2.4. Diffusion Network
Chapter 7. Market Segmentation 3: by Offering Estimates & Trend Analysis
7.1. by Offering & Market Share, 2024 & 2034
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Offering:
7.2.1. Natural Language Processing (NLP)
7.2.2. Machine Learning-Based Predictive Modeling
7.2.3. Computer Vision
7.2.4. Robotics and Automation
7.2.5. Augmented Reality (AR) and Virtual Reality (VR)
Chapter 8. Market Segmentation 4: by Application Estimates & Trend Analysis
8.1. by Application & Market Share, 2024 & 2034
8.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Application:
8.2.1. Content Creation and Marketing
8.2.2. Human Resource Management
8.2.3. Research and Development
8.2.4. Finance
Chapter 9. Generative AI Market Segmentation 5: Regional Estimates & Trend Analysis
9.1. North America
9.1.1. North America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.1.2. North America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2024-2031
9.1.3. North America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2024-2031
9.1.4. North America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.1.5. North America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.2. Europe
9.2.1. Europe Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.2.2. Europe Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2024-2031
9.2.3. Europe Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2024-2031
9.2.4. Europe Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.2.5. Europe Generative AI Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.3. Asia Pacific
9.3.1. Asia Pacific Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.3.2. Asia Pacific Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2024-2031
9.3.3. Asia-Pacific Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2024-2031
9.3.4. Asia-Pacific Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.3.5. Asia Pacific Generative AI Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.4. Latin America
9.4.1. Latin America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.4.2. Latin America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2024-2031
9.4.3. Latin America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2024-2031
9.4.4. Latin America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.4.5. Latin America Generative AI Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
9.5. Middle East & Africa
9.5.1. Middle East & Africa Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Type, 2024-2031
9.5.2. Middle East & Africa Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Technology, 2024-2031
9.5.3. Middle East & Africa Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Offering, 2024-2031
9.5.4. Middle East & Africa Generative AI Market Revenue (US$ Million) Estimates and Forecasts by Application, 2024-2031
9.5.5. Middle East & Africa Generative AI Market Revenue (US$ Million) Estimates and Forecasts by country, 2024-2031
Chapter 10. Competitive Landscape
10.1. Major Mergers and Acquisitions/Strategic Alliances
10.2. Company Profiles
10.2.1. OpenAI
10.2.2. Google DeepMind
10.2.3. Amazon.com, Inc.
10.2.4. Adobe
10.2.5. IBM
10.2.6. Microsoft
10.2.7. Meta
10.2.8. Salesforce, Inc.
10.2.9. Intel Corporation
10.2.10. Synthesia Limited.
10.2.11. SAMSUNG
10.2.12. NVIDIA Corporation
10.2.13. Cohere
10.2.14. Anthropic PBC
10.2.15. Inflection
10.2.16. Other Prominent Players
Generative AI Market- By type
Generative AI Market- By Technology
Generative AI Market- By Offering
Generative AI Market- By Application
By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
