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, And Segment Forecasts, 2023 - 2030

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 the 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 the demand for generative AI applications among industries. For instance, in March 2023, Microsoft Corporation, a technology company in the U.S., launched a model, Visual ChatGPT, which comprises multiple visual foundation models and enables users to interact with ChatGPT through graphical user interfaces.

With this model, ChatGPT can handle user requests for image generation and editing. The COVID-19 pandemic had a positive impact on the market as businesses shifted to the 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 the last 24 months as a part of their response to the pandemic Moreover, during the 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 the 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 the high implementation costs are expected to slow down the pace of development of the market.

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 the 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 up 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.

Component Insights

Based on components, the market is further bifurcated into software and services. The software segment accounted for the largest revenue share of 64.8% in 2022 and is expected to continue to dominate the industry over the forecast period. The growth of the 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 the fastest growth rate of 36.5% during the forecast period. The segment growth can be attributed to the 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 the 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 the 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 the text data and converts the 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, the diffusion networks segment is expected to witness the fastest growth rate of 38.1% during the forecast period. To meet the 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. The other sub-segment further comprises 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 the media & entertainment industry.For instance, in January 2023, BuzzFeed, Inc., an internet media, news, and entertainment company in the 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 the fastest growth rate of 38.1% during the forecast period. The market growth in this segment is attributed to the 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 the 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 the 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 the economic benefits of computer vision systems. Moreover, the 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 the 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.

The multi-modal generative model is expected to witness the 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 the 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, the 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 the availability of large amounts of data for training generative models.

Asia Pacific is anticipated to grow at the fastest CAGR of 36.5% during the forecast period. Increasing number of government initiatives in AI in Asia Pacific and the growing adoption of AI applications are driving the growth of the market in the Asia Pacific region. The regional market growth is also attributed to the rapidly digitizing businesses, which strain cloud networks and data centers. Moreover, AI adoption assists the 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 the 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 the industrial and medical markets.

For instance, in April 2023, Microsoft Corp., a technology company in the 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 the 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

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 generative AI market 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 7 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