Global Generative AI Market 2025 by Company, Regions, Type and Application, Forecast to 2031

According to our (Global Info Research) latest study, the global Generative AI market size was valued at US$ 34260 million in 2024 and is forecast to a readjusted size of USD 213320 million by 2031 with a CAGR of 31.8% during review period.

Generative AI, that is, using deep learning models and probabilistic modeling techniques to generate new content similar to training data by learning the distribution characteristics of a large amount of data. Its core goal is to generate new samples or content (such as text, images, audio, etc.) by capturing the potential structure or pattern of the data, which looks indistinguishable from real data in some aspects.

Generative AI is based on deep learning models and is trained through neural networks to learn the statistical characteristics and inherent laws of data. Generative AI predicts the generation process of data based on probabilistic models and attempts to learn the conditional probability distribution of a certain type of data. In many generative AI models, data is mapped to a lower-dimensional latent space, which represents the high-dimensional feature compression of the data and is a high-level semantic representation learned by the model.

Generative AI can automatically generate corresponding answers based on user questions to realize intelligent customer service systems or intelligent assistants. At the same time, it can also automatically write news reports, advertising copy, etc. to improve writing efficiency and quality. In addition, in terms of literary creation, generative AI can generate literary works such as novels, poems, and scripts to assist writers and screenwriters in the creative process. Generative AI can automatically generate corresponding codes based on natural language descriptions. It can also automatically supplement missing code snippets based on existing codes to improve coding efficiency. Generative AI can automatically identify and classify objects or scenes in images based on image content to achieve image classification and segmentation tasks. In industrial design, it can assist industrial designers in designing products and generate 3D models and rendered images that meet the requirements. In addition, generative AI can also generate images of artworks or commercial products based on the creativity of artists or designers. Generative AI can synthesize realistic human voices for use in news broadcasts, audiobooks and other fields. It can also convert one voice into another to achieve voice editing and translation tasks. In terms of film and television content analysis and editing, generative AI can analyze film and television content, automatically generate editing and editing suggestions, and improve post-production efficiency. In addition, it can also automatically generate music works or video clips based on music style or video theme. Generative AI can automatically generate movie special effects, game scenes and animation clips to improve production efficiency and quality. It can also assist architects and designers in designing buildings and furniture and generate 3D models and rendered images that meet the requirements.

With the optimization and upgrading of the economic structure, the demand for efficiency and innovation in various industries continues to grow, providing a broad market space for the application of generative AI. Generative AI can help enterprises improve production efficiency, reduce costs, and enhance competitiveness, thereby promoting its rapid development.

The public's attention to generative AI continues to rise, and the younger generation is more receptive to new technologies. At the same time, with the improvement of education level and the strengthening of popular science work, more and more people are beginning to understand and recognize the value and significance of generative AI.

AI technology has gone through several stages of development, and the advent of the era of large models has made the application of generative AI more extensive. Different large models have their own advantages in various fields, which has promoted the continuous innovation and breakthroughs of generative AI technology. In addition, the rapid development of technologies such as cloud computing and big data has also provided powerful computing resources and data support for generative AI.

Generative AI has broad application prospects in many fields such as text generation, code generation, and image generation. As people's demand for personalized and customized services continues to increase, generative AI can better meet these needs, thereby promoting its rapid development.

This report is a detailed and comprehensive analysis for global Generative AI market. Both quantitative and qualitative analyses are presented by company, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.

Key Features:

Global Generative AI market size and forecasts, in consumption value ($ Million), 2020-2031

Global Generative AI market size and forecasts by region and country, in consumption value ($ Million), 2020-2031

Global Generative AI market size and forecasts, by Type and by Application, in consumption value ($ Million), 2020-2031

Global Generative AI market shares of main players, in revenue ($ Million), 2020-2025

The Primary Objectives in This Report Are:

To determine the size of the total market opportunity of global and key countries

To assess the growth potential for Generative AI

To forecast future growth in each product and end-use market

To assess competitive factors affecting the marketplace

This report profiles key players in the global Generative AI market based on the following parameters - company overview, revenue, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include Google, Meta, OpenAI, Stability AI, Baidu, Microsoft, Anthropic, IBM Watson, Amazon Web Services (AWS), Cohere, etc.

This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.

Market segmentation

Generative AI market is split by Type and by Application. For the period 2020-2031, the growth among segments provides accurate calculations and forecasts for Consumption Value by Type and by Application. This analysis can help you expand your business by targeting qualified niche markets.

Market segment by Type

Desktop Application

Mobile Application

Market segment by Application

Text Generation

Image Generation

Code Generation

Audio Generation

Others

Market segment by players, this report covers

Google

Meta

OpenAI

Stability AI

Baidu

Microsoft

Anthropic

IBM Watson

Amazon Web Services (AWS)

Cohere

Mistral

Replika

Jasper

Market segment by regions, regional analysis covers

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia, Italy and Rest of Europe)

Asia-Pacific (China, Japan, South Korea, India, Southeast Asia and Rest of Asia-Pacific)

South America (Brazil, Rest of South America)

Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)

The content of the study subjects, includes a total of 13 chapters:

Chapter 1, to describe Generative AI product scope, market overview, market estimation caveats and base year.

Chapter 2, to profile the top players of Generative AI, with revenue, gross margin, and global market share of Generative AI from 2020 to 2025.

Chapter 3, the Generative AI competitive situation, revenue, and global market share of top players are analyzed emphatically by landscape contrast.

Chapter 4 and 5, to segment the market size by Type and by Application, with consumption value and growth rate by Type, by Application, from 2020 to 2031

Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2020 to 2025.and Generative AI market forecast, by regions, by Type and by Application, with consumption value, from 2026 to 2031.

Chapter 11, market dynamics, drivers, restraints, trends, Porters Five Forces analysis.

Chapter 12, the key raw materials and key suppliers, and industry chain of Generative AI.

Chapter 13, to describe Generative AI research findings and conclusion.