The global market size in the 'Generative AI' segment of the artificial intelligence market was forecast to continuously increase between 2025 and 2031 by in total 375.2 billion U.S. dollars (+560.92 percent). After the tenth consecutive increasing year, the market size is estimated to reach 442.07 billion U.S. dollars and therefore a new peak in 2031. Notably, the market size of the 'Generative AI' segment of the artificial intelligence market was continuously increasing over the past years.Find further information concerning the market size change in the 'AI Robotics' segment of the artificial intelligence market in the world and the market size in the 'Natural Language Processing' segment of the artificial intelligence market in the world.The Statista Market Insights cover a broad range of additional markets.

The global number of AI tools users in the 'AI Tool Users' segment of the artificial intelligence market was forecast to continuously increase between 2025 and 2031 by in total 826.2 million (+238.59 percent). After the tenth consecutive increasing year, the number of AI tools users is estimated to reach 1.2 billion and therefore a new peak in 2031. Notably, the number of AI tools users of the 'AI Tool Users' segment of the artificial intelligence market was continuously increasing over the past years.Find more key insights for the number of AI tools users in countries and regions like the market size in the 'Generative AI' segment of the artificial intelligence market in Australia and the market size change in the 'Generative AI' segment of the artificial intelligence market in Europe.The Statista Market Insights cover a broad range of additional markets.

Introduction

Generative AI Statistics: In recent years, generative AI has quickly become a game-changer across multiple industries, powered by advancements in machine learning and neural networks. These innovations have greatly improved the efficiency and flexibility of AI systems, enabling them to produce high-quality results.

The growing availability of extensive datasets, along with enhanced computing capabilities, has further accelerated the progress of generative AI, fostering more precise and innovative applications. This shift is particularly evident in sectors such as healthcare, automotive, finance, and entertainment, where AI-driven solutions are revolutionizing business operations and enhancing customer experiences. As digital transformation continues, the demand for generative AI is set to skyrocket, fundamentally altering how businesses function and engage with their audiences.

A broad dataset providing insights into artificial intelligence statistics and trends for 2025, covering market growth, adoption rates across industries, impacts on employment, AI applications in healthcare, education, and more.

As of 2023, the majority of users engaging with generative artificial intelligence (Gen AI), or ** percent, was composed of young adults in between 18 and 24 years old. Most of the users are also male and with a college degree or higher.

During a late 2024 survey, ** percent of responding marketers from across the globe stated they used generative artificial intelligence (AI) for data analysis. Market research ranked second, cited by ** percent of respondents.

Business's use of Generative AI, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2024.

According to a 2023 study conducted with marketers in the United States, ** percent of respondents reported using generative artificial intelligence tools, such as chatbots, as a part of their company's work. Only*** percent of American marketing professionals were not using the generative AI tools.

Value or potential value created by Generative AI, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2024.

Global Generative Artificial Intelligence (AI) In Data Visualization market size is expected to reach $8.64 billion by 2029 at 14.6%, rising data volumes fuel growth in generative ai for data visualization

Data sets and generating R code for reproduction of the results in "The Use of Generative AI in Statistical Data Analysis"

As of 2024, three out of four people, around ** percent, used generative AI in their works. Additionally, ** percent of respondents stated that they started using AI less than 6 months ago.

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Generative Artificial Intelligence (AI) Market Size 2025-2029

The generative artificial intelligence (AI) market size is forecast to increase by USD 185.82 billion at a CAGR of 59.4% between 2024 and 2029.

The market is experiencing significant growth due to the increasing demand for AI-generated content. This trend is being driven by the accelerated deployment of large language models (LLMs), which are capable of generating human-like text, music, and visual content. However, the market faces a notable challenge: the lack of quality data. Despite the promising advancements in AI technology, the availability and quality of data remain a significant obstacle. To effectively train and improve AI models, high-quality, diverse, and representative data are essential. The scarcity and biases in existing data sets can limit the performance and generalizability of AI systems, posing challenges for businesses seeking to capitalize on the market opportunities presented by generative AI.
Companies must prioritize investing in data collection, curation, and ethics to address this challenge and ensure their AI solutions deliver accurate, unbiased, and valuable results. By focusing on data quality, businesses can navigate this challenge and unlock the full potential of generative AI in various industries, including content creation, customer service, and research and development.

What will be the Size of the Generative Artificial Intelligence (AI) Market during the forecast period?

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The market continues to evolve, driven by advancements in foundation models and large language models. These models undergo constant refinement through prompt engineering and model safety measures, ensuring they deliver personalized experiences for various applications. Research and development in open-source models, language modeling, knowledge graph, product design, and audio generation propel innovation. Neural networks, machine learning, and deep learning techniques fuel data analysis, while model fine-tuning and predictive analytics optimize business intelligence. Ethical considerations, responsible AI, and model explainability are integral parts of the ongoing conversation.
Model bias, data privacy, and data security remain critical concerns. Transformer models and conversational AI are transforming customer service, while code generation, image generation, text generation, video generation, and topic modeling expand content creation possibilities. Ongoing research in natural language processing, sentiment analysis, and predictive analytics continues to shape the market landscape.

How is this Generative Artificial Intelligence (AI) Industry segmented?

The generative artificial intelligence (AI) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Software
  Services


Technology

  Transformers
  Generative adversarial networks (GANs)
  Variational autoencoder (VAE)
  Diffusion networks


Application

  Computer Vision
  NLP
  Robotics & Automation
  Content Generation
  Chatbots & Intelligent Virtual Assistants
  Predictive Analytics
  Others


End-Use

  Media & Entertainment
  BFSI
  IT & Telecommunication
  Healthcare
  Automotive & Transportation
  Gaming
  Others


Model

  Large Language Models
  Image & Video Generative Models
  Multi-modal Generative Models
  Others


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    Spain
    The Netherlands
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period.

Generative Artificial Intelligence (AI) is revolutionizing the tech landscape with its ability to create unique and personalized content. Foundation models, such as GPT-4, employ deep learning techniques to generate human-like text, while large language models fine-tune these models for specific applications. Prompt engineering and model safety are crucial in ensuring accurate and responsible AI usage. Businesses leverage these technologies for various purposes, including content creation, customer service, and product design. Research and development in generative AI is ongoing, with open-source models and transformer models leading the way. Neural networks and deep learning power these models, enabling advanced capabilities like audio generation, data analysis, and predictive analytics.

Natural language processing, sentiment analysis, and conversational AI are essential applications, enhancing business intelligence and customer experiences. Ethical co

Discover more about the size and trends of the rapidly expanding generative AI market.

Creativity is core to being human. Generative AI—made readily available by powerful large language models (LLMs)—holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on generative AI ideas. We study the causal impact of generative AI ideas on the production of short stories in an online experiment where some writers obtained story ideas from an LLM. We find that access to generative AI ideas causes stories to be evaluated as more creative, better written, and more enjoyable, especially among less creative writers. However, generative AI-enabled stories are more similar to each other than stories by humans alone. These results point to an increase in individual creativity at the risk of losing collective novelty. This dynamic resembles a social dilemma: with generative AI, writers are individually better off, but collectively a narrower scope of novel content is produced. Our results have implications for researchers, policy-makers, and practitioners interested in bolstering creativity. Methods This dataset is based on a pre-registered, two-phase experimental online study. In the first phase of our study, we recruited a group of N=293 participants (“writers”) who are asked to write a short, eight sentence story. Participants are randomly assigned to one of three conditions: Human only, Human with 1 GenAI idea, and Human with 5 GenAI ideas. In our Human only baseline condition, writers are assigned the task with no mention of or access to GenAI. In the two GenAI conditions, we provide writers with the option to call upon a GenAI technology (OpenAI’s GPT-4 model) to provide a three-sentence starting idea to inspire their own story writing. In one of the two GenAI conditions (Human with 5 GenAI ideas), writers can choose to receive up to five GenAI ideas, each providing a possibly different inspiration for their story. After completing their story, writers are asked to self-evaluate their story on novelty, usefulness, and several emotional characteristics. In the second phase, the stories composed by the writers are then evaluated by a separate group of N=600 participants (“evaluators”). Evaluators read six randomly selected stories without being informed about writers being randomly assigned to access GenAI in some conditions (or not). All stories are evaluated by multiple evaluators on novelty, usefulness, and several emotional characteristics. After disclosing to evaluators whether GenAI was used during the creative process, we ask evaluators to rate the extent to which ownership and hypothetical profits should be split between the writer and the AI. Finally, we elicit evaluators’ general views on the extent to which they believe that the use of AI in producing creative output is ethical, how story ownership and hypothetical profits should be shared between AI creators and human creators, and how AI should be credited in the involvement of the creative output. The data was collected on the online study platform Prolific. The data was then cleaned, processed and analyzed with Stata. For the Writer Study, of the 500 participants who began the study, 169 exited the study prior to giving consent, 22 were dropped for not giving consent, and 13 dropped out prior to completing the study. Three participants in the Human only condition admitted to using GenAI during their story writing exercise and—as per our pre-registration—they were therefore dropped from the analysis, resulting in a total number of writers and stories of 293. For the Evaluator Study, each evaluator was shown 6 stories (2 stories from each topic). The evaluations associated with the writers who did not complete the writer study and those in the Human only condition who acknowledged using AI to complete the story were dropped. Thus, there are a total of 3,519 evaluations of 293 stories made by 600 evaluators. Four evaluations remained for five evaluators, five evaluations remained for 71, and all six remained for 524 evaluators.

BCC Research Report: Dive into generative ai market report includes global revenue for base year data of 2023 and estimated data for the forecast period 2024 through 2029.

The functions related to IT and cybersecurity are where most of the generative AI (GenAI) adoption is concentrated in global organizations. Nearly **** of the surveyed professionals in the area claim to make use of GenAI in a limited or at-scale implementation in their companies.

During a 2023 survey conducted among professionals in the United States, it was found that 37 percent of those working in advertising or marketing had used artificial intelligence (AI) to assist with work-related tasks. Healthcare, however, had the lowest rate of AI usage with only 15 percent of those asked having used it at work. The rate of adoption in marketing and advertising is understandable, as it is the industry that most weaves together art and creative mediums in its processes.

Generative AI linked to education

Those positions that require a higher level of education are most at risk of being automated with generative AI in the U.S. This is simply because those jobs that require less formal education are rarely digital positions and are more reliant on physical labor. Jobs that require tertiary education, however, are still the least likely to be automated overall, even with the added influence of generative AI.

ChatGPT has competitors

While the OpenAI-developed ChatGPT is the most well-known AI program and the currently most advanced large language model, - other competitors are catching up. While just over half of respondents in the U.S. had heard of or used ChatGPT, nearly half of respondents had also heard of or used Bing Chat. Google’s Bard was slightly behind, with only around a third of Americans having heard of or used it.

Introduction

The Global Generative AI in Construction Market size is expected to be worth around USD 2,855.1 Million by 2033, from USD 142 Million in 2023, growing at a CAGR of 35% during the forecast period from 2024 to 2033.

This remarkable growth can be attributed to several factors that are driving the adoption of generative AI technologies within the construction industry. Firstly, the need for enhanced efficiency and productivity in construction projects is a significant driver. Generative AI can automate design processes, optimize resource allocation, and improve project planning, leading to reduced construction time and cost savings. Furthermore, the increasing demand for personalized and complex building designs has fueled the adoption of generative AI, as it enables architects and engineers to explore a wider range of design possibilities more quickly and with less effort.

However, the integration of generative AI in construction also faces challenges. The high initial investment required for the adoption of AI technologies and the lack of skilled professionals who can effectively use these tools are notable barriers. Additionally, concerns regarding data security and privacy continue to be significant issues that the industry must address. Despite these challenges, the potential benefits of generative AI, such as increased innovation, improved safety through predictive analytics, and the ability to manage complex projects more efficiently, suggest a promising future for its role in the construction industry. As stakeholders continue to recognize the value of generative AI, its adoption is expected to rise, driving substantial growth in the global market over the next decade.

The generative artificial intelligence (AI) market is expected to rise significantly, from ** billion U.S. dollars in 2020 to nearly *** billion U.S. dollars in 2024 and more than *** trillion U.S. dollars in 2032. This is due to an explosion of generative AI tools in recent years such as Bard by Google, ChatGPT by OpenAI, and Midjourney by Midjourney, Inc.