GVR Report cover Generative AI Market Size, Share & Trends Report

Generative AI Market Size, Share & Trends Analysis Report By Component (Software, Service), By Application (Computer Vision, NLP), By End-use (BFSI, Healthcare), By Model, By Technology, By Region, And Segment Forecasts, 2023 - 2030

  • Report ID: GVR-4-68040-011-4
  • Number of Pages: 100
  • Format: Electronic (PDF)
  • Historical Range: 2017 - 2021
  • Industry: Technology

Report Overview

The global generative AI market size was valued at USD 10.14 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 35.6% from 2023 to 2030. Factors, such as rising applications of technologies, such as super-resolution, text-to-image conversion, & text-to-video conversion, and growing demand to modernize workflow across industries are driving demand for generative AI applications among industries. For instance, in March 2023, Microsoft Corporation, a technology company in U.S., launched a model, Visual ChatGPT, which comprises multiple visual foundation models and enables users to interact with ChatGPT through graphical user interfaces.

Asia Pacific Generative AI Market size and growth rate, 2023 - 2030

With this model, ChatGPT can handle user requests for image generation and editing. The COVID-19 pandemic had a positive impact on market as businesses shifted to online work model, increasing digitalization across industries. As per IBM’s Global AI Adoption Index 2022 report, over 53% of IT professionals commented that they have accelerated the roll-out of Artificial Intelligence (AI) in last 24 months as a part of their response to pandemic. Moreover, during pandemic advance diagnosing tools were developed using Artificial Intelligence (AI) to detect the COVID-19 virus and various other imaging systems.

Generative AI makes use of unsupervised learning algorithms for spam detection, image compression, and preprocessing data stage, such as removing noise from visual data, to improve picture quality. Moreover, supervised learning algorithms are used for medical imaging and image classification. Furthermore, it has applications in various industries, such as BFSI, healthcare, automotive & transportation, IT & telecommunications, media & entertainment, and others. Generative AI is a powerful tool that can be used to create new ideas, solve problems, and create new products. Moreover, it can help organizations save money and time, increase efficiency, and enhance quality of content generated.

Popular generative AI tools include ChatGPT, GPT-3.5, DALL-E, MidJourney, and Stable Diffusion. Generative AI is at a developing stage, which will require a skilled workforce and high investment in implementation for development. According to IBM’s global AI adoption index 2022 report, 34% of respondents believed that a lack of Artificial Intelligence (AI) skills, expertise, or knowledge was restricting the adoption of Artificial Intelligence (AI) for industries. Hence, the unavailability of a skilled workforce and high implementation costs are expected to slow down the pace of development of the market.

The revolution in cloud storage solutions has boosted generative AI market expansion by offering a strong ground for technology development and deployment. Cloud storage provides scalable computing power, enabling access to resource-intensive Generative AI model training for businesses without heavy capital spending. Furthermore, it guarantees high efficiency in data accessibility and collaboration, enabling storage and sharing of various datasets across global teams. The cost-effective pay-as-you-go model of cloud storage reduces economic restraints and accelerates secure management of sensitive Generative AI projects. Offerings of Pre-trained models and APIs by cloud providers simplify development procedures, while cloud-based infrastructure augments resource optimization and business agility. Subsequently, cloud storage solutions foster Generative AI innovation, enabling companies to explore creative avenues and fuel market growth.

Generative AI is poised to create a new wave of software revenue. The technology is being used to create specialized assistants, new infrastructure products, and copilots that accelerate coding. According to a recent survey, increasing demand for generative AI products is expected to create an upsurge of around USD 300 billion in new software revenue. The biggest beneficiaries of this trend are likely to be cloud computing companies. As enterprises shift more workloads to public cloud, they will be looking for generative AI solutions to help them automate tasks and improve efficiency. Cloud computing companies like Amazon Web Services, Microsoft, Google, and Nvidia are already well-positioned to capitalize on this demand.

Generative AI allows models to become multimodal, which means they can process multiple modalities simultaneously, such as images and text, broadening their application areas and increasing their versatility. Generative AI enhances connection to the world where humans communicate with computers using natural language rather than programming languages. Generative AI has the potential to transform businesses by opening new opportunities for automation, innovation, and personalization, all while lowering costs and improving customer experience. For instance, in March 2023, Grammarly, Inc., a U.S.-based AI-based writing assistant, announced the launch of GrammarlyGo, a feature of generative AI enabling users to compose writing, edit, and personalize text.

Market Dynamics

Generative AI is an AI technique that can improve the outcomes of Natural Language Processing (NLP), machine learning, computer vision, and speech processing, among other computer science technologies. Various applications of these technologies include super-resolution, text-to-image conversion, algorithm invention, and identity security. Various technology companies offer these solutions in their end products; for instance, Rephrase.ai offers a full text-to-video resolution solution used in the marketing industry to produce personalized or even modified sales pitches. The solution starts with models that determine how a person's face changes for each phoneme and then uses this data to generate hyper-personalized videos by feeding data to algorithms.

An increasing number of technology companies are investing in novel machine learning development techniques and artificial intelligence, including generative AI, for various applications. The growing applications of these technologies are one of the key factors driving the market. These technologies are being adopted across healthcare, media & entertainment, BFSI, IT & telecommunication, and automotive & transportation industries. For instance, U.S.-based technology company IBM uses generative AI models such as variational auto-encoders and generative adversarial networks to support its efforts in drug research and discovery. The generative models help virtual synthesis of speech, text, images, and image captions, offering benefits such as reduced time consumption and a reduction in the cost of drug discovery. Face detection has various applications, including face detection, crowd surveillance, attendance, and marketing.

Component Insights

Based on components, the market is further bifurcated into software and services. The software segment accounted for largest revenue share of 64.8% in 2022 and is expected to continue to dominate the industry over the forecast period. The growth of software segment can be attributed to factors, such as growing fraudulent activities, overestimation of capabilities, unexpected outcomes, and rising concerns over data privacy. Generative AI software is expected to play a significant role in various industries and sectors, including fashion, entertainment, and transportation, as it is becoming more powerful through robust ML models. For instance, Brands like H&M and Adidas have used generative AI to create clothing designs and custom sneakers. Moreover, this technology has also been used to generate unique patterns for fabrics and prints, saving designers time and effort.

The service segment is anticipated to witness fastest growth rate of 36.5% during the forecast period. The segment growth can be attributed to increasing concerns over the protection of data, fraud detection, trading prediction, and risk factor modeling. Cloud-based generative AI services are expected to gain popularity as they provide flexibility, scalability, and cost-effectiveness, propelling service segment's growth. For instance, in April 2023, Amazon Web Service (AWS), a U.S.-based IT service management company, announced Amazon Bedrock and multiple generative AI services. This service aims to provide AWS customers with a suite of generative AI tools for building chatbots, generating & summarizing text, and classifying images based on a prompt.

Technology Insights

Based on technology, the market is segmented into Generative Adversarial Networks (GANs), transformers, variational auto-encoders, and diffusion networks. The transformers segment held the largest revenue share of 41.5% in 2022. This can be attributed to increasing adoption of transformers applications, such as text-to-image AI, which envisages converting text to an image. For instance, DALL-E is a transformer that understands text data and converts data accordingly. For instance, GPT-3 is an example of a transformer built by the OpenAI team, a San Francisco-based artificial intelligence research laboratory. This model can generate text that appears to have been written by a human and compose poetry and emails.

On the other hand, diffusion networks segment is expected to witness fastest growth rate of 38.1% during the forecast period. To meet increasing demands of image synthesis, image generation has become essential for various industries, such as BFSI, healthcare, media& entertainment, automotive & transportation, defense, and many others, as they are equipped to provide high-value to businesses, government, and public. Moreover, diffusion networks address the drawbacks of Generative Adversarial Networks (GANs) by better handling noise and generating a significantly higher diversity of images with similar or higher quality while requiring little effort in training. Using diffusion networks for generative AI can help leverage various unique capabilities, including creating diverse images, rendering text in various artistic styles, and animation.

End-use Insights

Based on end-use, the market is segmented into media & entertainment, BFSI, IT & telecommunications, healthcare, automotive & transportation, and others. Other sub-segment further comprise security, aerospace & defense. The media & entertainment segment accounted for the largest revenue of USD 2.30 billion in 2022 and is projected to grow at a CAGR of 34.7% over the forecast period. The increasing adoption of generative AI for creating better advertisement campaigns is likely to drive the demand for this technology in media & entertainment industry. For instance, in January 2023, BuzzFeed, Inc., an internet media, news, and entertainment company in U.S., announced a plan to use AI tools provided by Open AI, a U.S.-based AI company, to enhance and personalize specific content offerings.

The BFSI segment is expected to witness fastest growth rate of 38.1% during the forecast period. The market growth in this segment is attributed to increasing implementation of AI & Machine Learning (ML) in the sector to prevent fraudulent activities, secure data, and meet the dynamic needs of various stakeholders in financial services. Generative AI benefited banking industry by creating marketing images and text and generating data to make ML applications more efficient and accurate. Moreover, generative AI in commercial banking can accelerate back-office tasks, such as answering real-time questions about a customer’s financial performance in complex scenarios.

Application Insights

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. These models significantly enhanced the accuracy and efficiency of NLP-based generative AI applications, propelling growth of the segment.

The computer vision segment is anticipated to grow at a CAGR of 38.1% during the forecast period. The rapid adoption of computer vision systems in the transportation and automotive sectors drives segment growth. One of the major factors driving the computer vision market includes quicker processing and higher accuracy, combined with economic benefits of computer vision systems. Moreover, growing use of computer vision in non-industrial applications, such as surveillance, healthcare, and monitoring, creates a lucrative opportunity for the computer vision market trends.

Model Insights

The large language model segment dominated the market with a share of 33.6% in 2022 and is projected to grow at a CAGR of 35.0% over the forecast period. The segment growth can be attributed to various applications, ranging from chatbots capable of holding conversations with users to content-generation tools that can write product descriptions or articles. Large language models may help in reduction of time and cost associated with the development of NLP applications. Large language models, such as ChatGPT, have become popular in NLP. These models can comprehend and generate human-like language, making them useful in various applications.

Global Generative AI Market share and size, 2022

The multi-modal generative model is expected to witness fastest growth rate of 41.6% during the forecast period. The multi-modal generative model can achieve greater accuracy and robustness by combining data from multiple modalities, propelling segment’s growth. Image & video model will grow at a significant rate as it can assist in rapidly creating high-quality, realistic images & videos, which are difficult or impossible to achieve using traditional methods. Moreover, image synthesis is also being used to develop more realistic and immersive virtual worlds for entertainment and gaming purposes.

Regional Insights

North America dominated the industry with a share of 40.2% in 2022 and is projected to grow at a CAGR of 35.6% over the forecast period due to factors, such as rising pseudo-imagination & medical care and increasing banking frauds. Also, presence of prominent market players, such as U.S.-based Meta, Microsoft, and Google LLC, developed technology organizations, and the presence of experts are likely to drive the regional market growth. The regional market is also driven by factors, including increasing demand for AI-generated content in the media & entertainment, healthcare, and other industries and availability of large amounts of data for training generative models.

Generative AI Market Trends by Region, 2023 - 2030

Asia Pacific is anticipated to grow at a fastest CAGR of 36.5% during the forecast period. Increasing number of government initiatives in AI in Asia Pacific and growing adoption of AI applications are driving the growth of market in Asia Pacific region. The regional market growth is also attributed to rapidly digitizing businesses, which strain cloud networks and data centers. Moreover, AI adoption assists organizations in enabling civil society members to be responsible and informed users of AI devices.

Key Companies & Market Share Insights

The market is characterized by strong competition, with a few major worldwide competitors owning a significant industry share. The major focus is on developing new products and collaboration among key players. For instance, in March 2021, Bel Fuse Inc., an electronic connector manufacturing company, acquired EOS Power India Pvt. Ltd. for $7 million cash from funds on hand. This acquisition is intended to expand Bel Fuse Inc.’s offerings in industrial and medical markets.

For instance, in April 2023, Microsoft Corp., a technology company in U.S., collaborated with Epic Systems, an American healthcare software company, to incorporate large language model tools and AI into Epic’s electronic health record software. This partnership aims to use generative AI to help healthcare providers increase productivity while reducing administrative burden. Some of the prominent players in global generative AI market include:

  • Adobe Inc.

  • Amazon Web Services, Inc.

  • D-ID

  • Genie AI Ltd.

  • Google LLC

  • International Business Machines Corp.

  • Microsoft Corp.

  • MOSTLY AI Inc.

  • Rephrase.ai

  • Synthesia

Generative AI Market Report Scope

Report Attribute


Market size value in 2023

USD 13.00 billion

Revenue forecast in 2030

USD 109.37 billion

Growth rate

CAGR of 35.6% from 2023 to 2030

Base year for estimation


Historical data

2017 - 2021

Forecast period

2023 - 2030

Report updated

September 2023

Quantitative units

Market revenue in USD billion, and CAGR from 2023 to 2030

Report coverage

Revenue forecast, company ranking, competitive landscape, growth factors, and trends

Segments covered

Component, technology, end-use, application, model, region

Regional scope

North America; Europe; Asia Pacific; Latin America; MEA

Country scope

U.S.; Canada; UK; Germany; France; Italy; China; India; Japan; Australia; Brazil; Mexico; Chile; Argentina; UAE; Saudi Arabia; South Africa

Key companies profiled

Adobe Inc.; Amazon Web Services, Inc.; D-ID; Genie AI Ltd.; Google LLC; International Business Machines Corp.; Microsoft Corp.; MOSTLY AI Inc.; Rephrase.ai; Synthesia

Customization scope

Free report customization (equivalent up to 8 analysts working days) with purchase. Addition or alteration to country, regional, and segment scope

Pricing and purchase options

Avail customized purchase options to meet your exact research needs. Explore purchase options


Global Generative AI Market Segmentation

This report forecasts revenue growth and provides an analysis of the latest trends in each of the sub-segments from 2017 to 2030. For this report, Grand View Research has segmented the global generative AI market report based on component, technology, end-use, application, model, and region:

  • Component Outlook (Revenue, USD Billion, 2017 - 2030)

    • Software

    • Service

  • Technology Outlook (Revenue, USD Billion, 2017 - 2030)

    • Generative Adversarial Networks (GANs)

    • Transformers

    • Variational Auto-encoders

    • Diffusion Networks

  • End-use Outlook (Revenue, USD Billion, 2017 - 2030)

    • Media & Entertainment

    • BFSI

    • IT & Telecommunication

    • Healthcare

    • Automotive & Transportation

    • Gaming

    • Others

  • Application Outlook (Revenue, USD Billion, 2017 - 2030)

    • Computer Vision

    • NLP

    • Robotics And Automation

    • Content Generation

    • Chatbots & Intelligent Virtual Assistants

    • Predictive Analytics

    • Others

  • Model Outlook (Revenue, USD Billion, 2017 - 2030)

    • Large Language Models

    • Image & Video Generative Models

    • Multi-modal Generative Models

    • Others

  • Regional Outlook (Revenue, USD Billion, 2017 - 2030)

    • North America

      • U.S.

      • Canada

    • Europe

      • U.K.

      • Germany

      • France

      • Italy

    • Asia Pacific

      • China

      • India

      • Japan

      • Australia

    • Latin America

      • Brazil

      • Mexico

      • Chile

      • Argentina

    • Middle East and Africa

      • UAE

      • Saudi Arabia

      • South Africa

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