Generative AI Market Size & Share Analysis - Growth Trends & Forecasts (2024 - 2029)

The Generative AI Market Report is Segmented by Offering (Solutions and Services), End-User Industry (BFSI, Healthcare, IT and Telecommunication, Government, Retail and Consumer Goods, and Other End-User Industries), and Geography (North America, Europe, Asia-Pacific, Latin America, and Middle East and Africa). The Report Offers Market Size and Forecasts in Value (USD) for all the Above Segments.

Generative AI Market Size

Generative AI Market Summary
Study Period 2019 - 2029
Market Size (2024) USD 36.06 Billion
Market Size (2029) USD 281.90 Billion
CAGR (2024 - 2029) 50.87 %
Fastest Growing Market Asia Pacific
Largest Market North America

Major Players

Generative AI Market Major Players

*Disclaimer: Major Players sorted in no particular order

Compare market size and growth of Generative AI Market with other markets in Technology, Media and Telecom Industry

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Generative AI Market Analysis

The Generative AI Market size is estimated at USD 36.06 billion in 2024, and is expected to reach USD 281.90 billion by 2029, growing at a CAGR of 50.87% during the forecast period (2024-2029).

  • The market is primarily propelled by the expanding information technology (IT) sector and the growing use of AI-integrated systems for improving productivity and agility. Besides this, generative AI's ever-increasing popularity for aiding chatbots in conducting effective conversations and enhancing consumer satisfaction also propels the market’s growth. Generative AI can construct personalized recommendations, tailored advertisements, and customized products based on individual choices and behavior. Moreover, the increasing utilization of generative AI for making virtual worlds in the metaverse, producing digital artworks using text-based descriptions, and generating unique and innovative content is also pushing the market forward. Furthermore, the market has drawn significant investments and funding from established businesses and venture capitalists.
  • Generative AI allows models to evolve multimodal, which implies they can process multiple modalities simultaneously, such as images and text, widening their application areas and improving their versatility. Generative AI enhances the connection to the globe where humans communicate with computers, utilizing natural language rather than programming languages. Generative AI can 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., an AI-based writing assistant, announced the launch of GrammarlyGo, a feature of generative AI that allows users to compose writing, edit, and personalize text.
  • GANs have found applications in numerous fields and enterprises, making them highly adaptable. They are utilized in image synthesis, style transfer, image-to-image translation, text generation, video generation, data augmentation, and more. The ability of GANs to develop new, diverse, and realistic models has made them a go-to choice for various generative tasks, driving the market studied. Moreover, the availability of open-source implementations and pre-trained GAN models have facilitated the adoption and usage of GANs. These resources, integrated with easy-to-use libraries and frameworks like PyTorch and TensorFlow, have lowered the obstacle to entry for designers and researchers, letting them leverage GANs for their applications without starting from scratch.
  • Medical research depends on accessing vast amounts of data on different health conditions. This data needs to be improved, especially regarding rare diseases. Such data is also expensive, and privacy laws govern its usage and sharing. Generative AI in medicine can produce synthetic data samples that augment real-life health datasets. These samples are not subject to privacy regulations, as healthcare data does not belong to particular individuals. Artificial intelligence can develop EHR data, scans, etc. For example, a team of German researchers built an AI-powered model, GANerAid, to generate synthetic patient data for clinical trials. This model is based on the GAN procedure and can create medical data with the desired properties even if the training dataset is limited.
  • Generative AI solutions allow organizations to understand their compliance-related issues and data management better. Software tools enable AI-enabled solutions to extract a large amount of data on time and produce accurate and complete data. There is a surge in the trend where a significant number of companies are increasingly demanding AI-based solutions. Moreover, multiple industries are witnessing a considerable increase in startups. These new players are highly attracted to adopting AI to automate and expand their businesses. AI-based solutions are mainly deployed due to their cost and time efficiency, improved user experience, ease of use, and new features with advanced technology.
  • On the contrary, artificial intelligence can potentially solve common business challenges. Still, privacy concerns are popping up, and firms feed consumer and vendor data into advanced, AI-fueled algorithms to create new sensitive information. Security and privacy concerns are among the key challenges in the digital transformation market. As firms rely more on digital technology, they collect and store enormous volumes of sensitive data, making them vulnerable to cyberattacks and data breaches. Furthermore, as the number of connected devices rises, hackers' attack surface expands, making it more challenging to secure these devices and the data they collect and transmit.

Generative AI Market Trends

BFSI is Expected to Hold a Significant Share of the Market

  • Generative AI can revolutionize banks' risk management over the next few years. It could permit processes to move away from task-oriented activities toward partnering with company lines on strategic risk prevention and having controls at the outset in new consumer journeys, often referred to as a "shift left" approach. That, in turn, would free up risk professionals to advise companies on new product development and strategic corporation decisions, explore emerging risk trends and scenarios, strengthen resilience, and enhance risk and control processes proactively.
  • Furthermore, generative AI models can enable banks to identify risk areas and preserve profitability by analyzing historical data patterns and market trends. By simulating different economic scenarios, GANs can allow banks to assess and mitigate risks, such as credit, market, and operational risks. For instance, Mastercard recently launched a new generative AI model to enable banks to better detect suspicious transactions on its network. According to Mastercard, the technology is poised to allow banks to improve their fraud detection rate by 20%, with rates reaching as much as 300% in some cases.
  • Customer service has always been a cornerstone of success. However, serving consumers' diverse requirements efficiently can be challenging. This is where generative AI-powered chatbots step in. AI-driven chatbots can engage consumers in natural, human-like conversations, providing instant assistance 24/7. These bots are not just rule-based; they understand context, sentiment, and nuances in language, making exchanges seamless and personalized. When a consumer has a query or needs assistance, the chatbot uses generative AI to examine the inquiry and provide relevant responses or solutions.
  • Similarly, wealth management is critical in banking, where customers entrust financial institutions to develop and safeguard their assets. Generative AI is pivotal in improving wealth management and portfolio optimization processes. Generative AI models can interpret financial data, economic indicators, market trends, and customer profiles. AI can utilize this data to generate predictive models that suggest optimal asset allocations and investment strategies. Based on varying market conditions and emerging opportunities, these models can adjust portfolios in real time. This dynamic method of wealth management allows banks to maximize returns while managing risk effectively.
  • According to Nvidia survey 2023, Data analytics was the most used AI-enabled application in the financial services industry in 2023. Based on the study, 43% of the respondents used AI for generative AI, and 69% of the respondents used AI for data analytics, followed by data processing and data processing. Other common AI use cases were natural language processing and large language models. The adoption of AI in financial businesses increased significantly since 2022, and it is anticipated to grow even further in the coming years. Such massive adoption of AI in the finance sector is expected to drive the demand for the market studied.
Generative AI Market: Most Popular AI Use Cases in Financial Services, in %, Worldwide, 2023

North America is Expected to Hold Significant Share of the Market

  • North America has a functional AI research community, with eminent institutions and researchers propelling advancements in generative AI. The region's foremost research centers and universities conduct advanced research, publish significant papers, and contribute to developing generative AI methods. The region's large population, high consumer spending, and advanced technology infrastructure also create a favorable environment for the adoption and commercialization of generative AI solutions. In addition, North America is expected to lead in AI research and development, with major players like Google, Microsoft, and IBM investing heavily in generative AI technologies. Moreover, the region's advanced infrastructure, favorable government initiatives, and early adoption of AI in sectors such as healthcare, finance, and automotive contribute to its market dominance.
  • The final report of the National Security Commission on Artificial Intelligence recommended increasing federal R&D funding for AI in the United States by a factor of two annually, up to USD 32 billion in fiscal 2026. The government decided to increase the federal R&D budget by 28% from FY 2021 authorized levels to more than USD 204 billion under the fiscal 2023 budget plan. The national AI research institutes, both new and established, were poised to get some of those funds. To address the difficulties of AI research and workforce development, these institutes bring together the commercial sector, organizations, academics, and federal, state, and municipal authorities. Such government initiatives are expected to create opportunities for the generative AI market to grow.
  • According to the Stanford AI Index Report, in 2023, 61 notable AI models originated from US-based institutions, far outpacing the European Union's 21 and China's 15. The number of AI-related regulations in the United States has risen significantly in 2023 and over the last five years. In 2023, there were 25 AI-related regulations, up from just one in 2016. In 2023, the number of AI-related regulations increased by 56.3%. Moreover, new research from the AI Index indicates a substantial lack of standardization in reliable AI reporting. Leading developers, including OpenAI, Google, and Anthropic, primarily test their models against various responsible AI benchmarks.
  • New market research commissioned by IBM reports that Canadian companies are increasingly adopting and deploying artificial intelligence (AI), with about 37% of enterprise-scale organizations (over 1,000 employees) saying their company uses it as part of their business operations. While AI adoption remained steady globally (42% since April 2023), Canada saw an uptick in enterprises deploying AI from 34% in April 2023 to 37% in November 2023. Early adopters are leading the way, with 35% of the enterprises already working with AI intending to accelerate and expand investment in the technology. Such a huge adoption of AI in the country is expected to create opportunities for growth for the market players in the region.
  • The players in the generative AI market are collaborating with Canadian enterprises to cater to their needs. For instance, in April 2024, IBM announced its new Cloud Multizone Region (MZR) in Montreal, Quebec. It will be designed to help clients address their evolving regulatory requirements and leverage technology such as generative AI with a secured enterprise cloud platform. Building on the opening of IBM Cloud's Toronto MZR in 2021 and existing data centers in Montreal, the new Montreal MZR is planned for the first half of 2025. IBM's expanded presence in Canada is expected to help clients throughout the country manage their emerging and existing regulatory demands, including geographic requirements around sovereignty, while driving innovation.
Generative AI Market : Market CAGR (%), By Region, Global

Generative AI Industry Overview

The global generative AI market is semi-consolidated, with a few prominent players, such as Google LLC, IBM Corporation, Microsoft Corporation, Adobe Inc., Amazon Web Services, and others. To increase market share, corporations continually spend on strategic partnerships or acquisitions and solution and services development. For instance,

  • In May 2024, Sainsbury’s agreed a five-year partnership deal with Microsoft to incorporate generative AI into the supermarket chain’s operations. The British retail giant will use Microsoft generative AI to “improve customers’ search experience” for online shopping and AI customer support. Sainsbury’s said it will also use Microsoft AI to improve the efficiency of in-store staff, with AI guiding workers to shelves that need restocking.
  • In May 2024, IBM and SAP SE announced their vision for the next era of their collaboration, which includes new generative AI capabilities and industry-specific cloud solutions that can assist clients in unlocking business value. The companies are exploring opportunities to build new generative AI capabilities for RISE with SAP and infuse AI into SAP business processes across industry-specific cloud solutions and lines of business applications. Initially, IBM plans to extend AI capabilities across SAP’s cloud solutions and applications, all underpinned by the SAP Business Technology Platform (SAP BTP).

Generative AI Market Leaders

  1. Google LLC

  2. IBM Corporation

  3. Microsoft Corporation

  4. Adobe Inc

  5. Amazon Web Services

*Disclaimer: Major Players sorted in no particular order

Generative AI Market Concentration
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Generative AI Market News

  • April 2024: Cognizant expanded its collaboration with Microsoft to bring Microsoft’s generative AI capabilities to its employees and a million users across its 2,000 global clients. The professional services business has purchased 25,000 Microsoft 365 Copilot seats for its associates, 500 Sales Copilot seats, and 500 Services Copilot seats to enhance productivity, workflows, and customer experiences. Cognizant will also work to deploy Microsoft 365 Copilot to its customers.
  • February 2024: Stack Overflow and Google Cloud reported a strategic collaboration that will deliver new-gen AI-powered abilities to developers through the Stack Overflow platform, Google Cloud Console, and Gemini for Google Cloud. Through the partnership, Stack Overflow will work with Google Cloud to bring new AI-powered features to its widely adopted developer knowledge platform. Google Cloud will integrate Gemini for Google Cloud with Stack Overflow, enabling it to surface important knowledge base information and coding assistance capabilities to developers.

Generative AI Market Report - Table of Contents

1. INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Market Ecosystem Analysis
  • 4.3 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.3.1 Bargaining Power of Buyers
    • 4.3.2 Bargaining Power of Suppliers
    • 4.3.3 Threat of New Entrants
    • 4.3.4 Threat of Substitutes
    • 4.3.5 Intensity of Competitive Rivalry
  • 4.4 Impact of Macro Economic Factors on the Market
  • 4.5 Case Study Analysis

5. MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Use of AI-Integrated System across Multiple Industries
    • 5.1.2 Increase in Demand for Customization and Personalization Needs
  • 5.2 Market Restrains
    • 5.2.1 Privacy and Ethical Concerns
  • 5.3 Impact of Technologies
    • 5.3.1 Generative Adversarial Network (GANs)
    • 5.3.2 Transformer
    • 5.3.3 Variational Autoencoder (VAE)
    • 5.3.4 Diffusion Networks

6. MARKET SEGMENTATION

  • 6.1 By Component
    • 6.1.1 Software
    • 6.1.2 Services
  • 6.2 By End User
    • 6.2.1 BFSI
    • 6.2.2 Healthcare
    • 6.2.3 IT and Telecommunication
    • 6.2.4 Government
    • 6.2.5 Retail and Consumer Goods
    • 6.2.6 Other End-user Industries
  • 6.3 By Geography***
    • 6.3.1 North America
    • 6.3.2 Europe
    • 6.3.3 Asia
    • 6.3.4 Australia and New Zealand
    • 6.3.5 Latin America
    • 6.3.6 Middle East and Africa

7. COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles*
    • 7.1.1 Google LLC
    • 7.1.2 IBM Corporation
    • 7.1.3 Microsoft Corporation
    • 7.1.4 Adobe Inc
    • 7.1.5 Amazon Web Services
    • 7.1.6 Cohere
    • 7.1.7 Nvidia Corporation
    • 7.1.8 SAP SE
    • 7.1.9 Rephrase AI
    • 7.1.10 Konverge AI

8. INVESTMENT ANALYSIS

9. MARKET OUTLOOK AND FUTURE OF THE MARKET

** Subject To Availablity
**Subject to Availability
*** In the Final Report Asia, Australia and New Zealand will be Studied Together as 'Asia Pacific'
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Generative AI Industry Segmentation

Generative AI is a set of algorithms that generate seemingly new, realistic content such as text, images, or audio from the training data. The most potent generative AI algorithms are built on foundation models trained on a vast quantity of unlabeled data in a self-supervised way to determine underlying patterns for a wide range of tasks.

The generative AI market is segmented by offering (solutions and services), end-user industry (BFSI, healthcare, IT and telecommunication, government, retail and consumer goods, and other end-user industries), and geography (North America, Europe, Asia-Pacific, Latin America, and Middle East and Africa). The report offers market size and forecasts in value (USD) for all the above segments.

By Component Software
Services
By End User BFSI
Healthcare
IT and Telecommunication
Government
Retail and Consumer Goods
Other End-user Industries
By Geography*** North America
Europe
Asia
Australia and New Zealand
Latin America
Middle East and Africa
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Generative AI Market Research FAQs

The Generative AI Market size is expected to reach USD 36.06 billion in 2024 and grow at a CAGR of 50.87% to reach USD 281.90 billion by 2029.

In 2024, the Generative AI Market size is expected to reach USD 36.06 billion.

Google LLC, IBM Corporation, Microsoft Corporation, Adobe Inc and Amazon Web Services are the major companies operating in the Generative AI Market.

Asia Pacific is estimated to grow at the highest CAGR over the forecast period (2024-2029).

In 2024, the North America accounts for the largest market share in Generative AI Market.

In 2023, the Generative AI Market size was estimated at USD 17.72 billion. The report covers the Generative AI Market historical market size for years: 2019, 2020, 2021, 2022 and 2023. The report also forecasts the Generative AI Market size for years: 2024, 2025, 2026, 2027, 2028 and 2029.

Generative AI Industry Report

Statistics for the 2024 Generative AI market share, size and revenue growth rate, created by Mordor Intelligence™ Industry Reports. Generative AI analysis includes a market forecast outlook for 2024 to 2029 and historical overview. Get a sample of this industry analysis as a free report PDF download.

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Generative AI Market Size & Share Analysis - Growth Trends & Forecasts (2024 - 2029)