Generative AI Market Size, Share And Growth Report, 2030

Generative AI Industry Size, Share, Growth, Trend Analysis 2023 To 2032 by maya sara

In the bottom-up approach, the adoption rate of generative AI solutions and services among different end users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of generative AI solutions and services among industries, Yakov Livshits along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in different regions for the market size calculation. Asia Pacific is anticipated to grow at the fastest CAGR of 36.5% during the forecast period.

The proliferation of digital devices, social media, and the internet has resulted in an explosion of data. Generative AI algorithms require large amounts of data to learn and create new content. Moreover, more data allows generative AI models to capture a broader range of patterns and variations present in the real world. For example, in computer vision, a larger dataset of images can help generative AI models produce more visually convincing and detailed images. Besides, the increasing volume of generated data can be used for data augmentation and synthesis purposes.

Segments Covered in Report

This tool can understand questions like a human mind, answer follow-up questions, challenge incorrect premises, admit mistakes, and reject inappropriate requests. “However, we anticipate a rapid expansion of the market overall, with some sectors advancing faster than others. Overall, we think the impact of generative AI will be huge and change the way we work with language, images, code, audio and video.” By creating simulations, scenarios, or alternate options, generative AI can help in decision-making processes. It can produce artificial data for training algorithms, simulate outcomes in different circumstances, or produce different product design concepts. Generative AI assists decision-makers in making well-informed decisions by offering these insights and options.

  • The increasing investment in artificial intelligence is providing huge opportunities to the market.
  • Europe is a leader in research and development for artificial intelligence because of its creative businesses, industrialists, and digital start-ups based on scientific discoveries.
  • In terms of growth, the Asia-Pacific region will obtain the highest growth rate from 2022 to 2030.
  • The market for generative AI is expected to grow significantly due to increasing demand for personalized content and the growing need for automation in various industries.
  • The global generative AI market is segmented based on component, end-use, technology, application, model, and region.

It can be used in many ways, from producing images and writing blog posts to writing codes or composing music. Generative AI is forecasted to make up about 10 to 12% of total IT hardware, software services, ad spending, and gaming markets by 2032, compared to less than 1% currently, Bloomberg Intelligence’s report suggests. The release of AI tools like ChatGPT and Google Bard has created an explosion of interest in the generative AI industry, which could see revenues grow to over $1.3 trillion in the next decade, according to a report by Bloomberg Intelligence viewed by Insider. The legal implications of Generative AI are multifaceted, covering issues such as ownership of input data, private and corporate data usage, and generated outputs.


High capital investment– A considerable investment is required to install generative AI operations in large corporate offices. In addition to this, regularly scheduled updates and preventive maintenance are necessary for such software, which leads to the additional cost being added to the overall cost that the Yakov Livshits company is spending. Therefore, substantial initial investment and maintenance cost is one of the critical factors that may hinder the market’s growth over the forecast period. The generative AI market is divided into multiple segments, including auto-encoders, GANs, diffusion networks, and transformers.

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They are taught to understand the language or image, to learn classification tasks, and to generate texts or images from large datasets. If the training data is biased or incomplete, it can lead to biased or inaccurate outputs. The production of representative & diverse training datasets is a challenge as it requires careful data curation & pre-processing.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

Generative AI: Exploring Market Size, Trends, and Statistics (2023–

In terms of end-use, media & entertainment category registered the highest revenue share in 2022 due to the major use of generative AI to create and develop attractive and better advertisement campaigns. Also, increasing adoption of virtual creation and demand for creating high-definition visuals and real-time virtual worlds is propelling the segment growth. In addition, the incorporation of AI improves analytics, which aids companies in using sentiment analysis, visual recognition, and dialogue capabilities to boost segment growth.

generative ai market size

Natural Language synthesis (NLG), which enables coherent and contextually appropriate text synthesis for chatbots, content creation, and automated reporting, stands out in this field. Avatars in social media feeds and the prevalence of text-to-image tools have helped generative AI gained public attention in APAC. The region is projected to be over USD 22 billion market by 2028 in terms of Generative AI revenue. Japanese pharma companies are experts in wet lab research, and are eyeing on taking advantage of high-performance computing and generative AI on a large scale. By region, North America attained the highest market share in the generative AI market in 2022.

Generative AI: A Disruptive Technology with Boundless Potential and Perilous Pitfalls

Crucially, it’s imperative to recognize that the caliber of outputs produced by a given generative model hinges on the excellence of the underlying datasets or training sets. Biases inherent in these sets can be manifested within a specific model’s results, potentially perpetuating biases if present within the training data. This phenomenon imparts a direct impact on both the excellence and dependability of the outputs.

generative ai market size

The global generative ai market size was valued at USD 8.2 Billion in 2021, and is projected to reach USD 126.5 Billion by 2031, growing at a CAGR of 32% from 2022 to 2031. AI-powered tools also assist in software development, handling tasks such as composing user stories, editing and reviewing code, identifying bugs, and testing software. These tools contribute to more efficient workflows, heightened productivity, and expedited time-to-market. Some applications of Generative AI encompass text-to-code generation, code auto-completion, and code summarisation or explanation.

Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the generative AI market’s regional penetration. With the data triangulation procedure and data validation through primaries, the exact values of the overall and segments’ size were determined and confirmed using the study. The Natural Language Processing (NLP) segment dominated the market with a share of 22.5% in 2022 and is projected to grow at a CAGR of 35.9% over the forecast period. NLP is a powerful generative AI tool with numerous text and speech generation applications. Deep learning advances have resulted in the development of neural NLP models, such as Recurrent Neural Networks (RNNs), and transformer models, such as BERT, developed by researchers at Google AI Language and GPT-3, developed by OpenAI, a U.S.-based AI company.

generative ai market size

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