Summary

Generative AI Market Growth & Trends

The global generative AI market size is anticipated to reach USD 109.37 billion by 2030, according to a new report by Grand View Research, Inc., registering a CAGR of 36.5% from 2024 to 2030. Growing demand to modernize workflow across industries is expected to drive the demand for generative AI applications among industries. Other factors that propel the market growth include the evolution of AI and deep learning, a rise of creative applications & content creation, and innovation of cloud storage, allowing easy data access. Moreover, the introduction of AI-powered gaming that provides more high-level visuals and graphics, interactivity, and a more realistic feel is projected to boost market growth in the coming years.

The COVID-19 pandemic had a positive impact on the market. Many organizations adopted AI & Machine Learning (ML) as a response to the pandemic. Many key players, such as Microsoft, IBM, Google LLC, and Amazon Web Services, Inc., witnessed a growth in sales of AI-based technology during the pandemic. Moreover, the accelerated advancement of digital platforms empowered the adoption of generative AI applications. For instance, in June 2020, Amazon Web Services, Inc. announced the addition of a new generative AI algorithm, Autoregressive Convolutional Neural Network (AR-CNN), to its AWS DeepComposer suite of products, allowing developers to create excellent music digitally.

AWS DeepComposer also provides learning capsules to developers to learn the basics of algorithms. Many generative AI market players offer solutions for numerous applications, such as text-to-image, image-to-image, and super-resolution. For instance, in March 2023, Microsoft Corporation, a software company in the U.S., launched Microsoft 365 Copilot, an AI assistant feature for Microsoft 365 services and applications. Microsoft 365 Copilot can benefit businesses by saving time, streamlining and automating their IT processes, and increasing productivity. Moreover, these industry players are researching generative AI technology for advanced image resolution, face aging, and video resolution technologies.

For instance, U.S.-based Tesla is developing autonomous algorithms using data from car sensors. Also, the neural networks are further trained to perform object detection and semantic segmentation. Investment in the AI and ML sectors to support the market will drive the North America regional market. The presence of tech players in the U.S. and Canada provides lucrative growth opportunities for the regional market. For instance, big tech companies like Microsoft Corporation, Google LLC, and Amazon Web Service are investing in generative AI startups and technology. Asia Pacific is expected to grow at a considerable CAGR from 2024 to 2030 owing to the expansion of end-user industries in countries, such as China and Japan.

Generative AI Market Report Highlights

• The software segment accounted for the highest revenue share of 64.5% in 2023 and is expected to retain its position over the forecast period. Rising use of generative AI-based software owing to its benefits, such as better image resolution, reduced conversion time, enhanced performance, and quick availability of output is attributed to market growth

• The transformers technology segment dominated the market with a share of 41.3% in 2023 and is expected to grow at a significant CAGR from 2024 to 2030. This can be attributed to the rising adoption of transformer applications worldwide that focus on predicting text and analyzing words. The diffusion networks segment is expected to grow at the fastest CAGR of 39.1% from 2024 to 2030 due to the variety and penetration of diffusion network applications to deliver generative models that generate realistic output

• The media & entertainment segment accounted for the maximum revenue share of 22.6% in 2023 due to the increasing adoption of generative AI for creating better advertisement campaigns and generative AI-based digital platforms for shopping. The BFSI segment is likely to grow at the fastest CAGR from 2024 to 2030

• North America held the largest share of 40.2% in 2023 and is expected to grow at a significant CAGR from 2024 to 2030. This can be attributed to the presence of a large number of key players as well as technology organizations. Asia Pacific is anticipated to register a CAGR of over 37.5% from 2024 to 2030 owing to developing technology infrastructure and government initiatives

• In March 2022, Google LLC, announced the acquisition of Mandiant, a cybersecurity firm, for USD 5.4 billion. This acquisition would help Google LLC provide better advisory services and security operations suites, which will help customers resolve their most critical security challenges

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Table of Contents

Table of Contents

Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.2. Segment Definitions
1.2.1. Component
1.2.2. Technology
1.2.3. End-use
1.2.4. Application
1.2.5. Model
1.2.6. Regional scope
1.2.7. Estimates and forecasts timeline
1.3. Research Methodology
1.4. Information Procurement
1.4.1. Purchased database
1.4.2. GVR’s internal database
1.4.3. Secondary sources
1.4.4. Primary research
1.4.5. Details of primary research
1.4.5.1. Data for primary interviews in North America
1.4.5.2. Data for primary interviews in Europe
1.4.5.3. Data for primary interviews in Asia Pacific
1.4.5.4. Data for primary interviews in Latin America
1.4.5.5. Data for Primary interviews in MEA
1.5. Information or Data Analysis
1.5.1. Data analysis models
1.6. Market Formulation & Validation
1.7. Model Details
1.7.1. Commodity flow analysis (Model 1)
1.7.2. Approach 1: Commodity flow approach
1.7.3. Volume price analysis (Model 2)
1.7.4. Approach 2: Volume price analysis
1.8. List of Secondary Sources
1.9. List of Primary Sources
1.10. Objectives
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Component
2.2.2. Technology outlook
2.2.3. End-use outlook
2.2.4. Application outlook
2.2.5. Model outlook
2.3. Competitive Insights
Chapter 3. Generative AI Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.1.1. Rising applications of novel technologies
3.2.1.2. Growing demand to modernize workflow across industries
3.2.2. Market restraint analysis
3.2.2.1. Lack of skilled workforce and high implementation cost
3.2.3. Market opportunity analysis
3.2.3.1. Increasing research and development activities in technology companies
3.3. Generative AI Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Supplier power
3.3.1.2. Buyer power
3.3.1.3. Substitution threat
3.3.1.4. Threat of new entrant
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political landscape
3.3.2.2. Economic landscape
3.3.2.3. Social landscape
3.3.2.4. Technological landscape
3.3.2.5. Environmental landscape
3.3.2.6. Legal landscape
Chapter 4. Generative AI Market: Component Estimates & Trend Analysis
4.1. Component Market Share, 2023 & 2030
4.2. Segment Dashboard
4.3. Global Generative AI Market by Component Outlook
4.4. Market Size & Forecasts and Trend Analyses, 2017 to 2030 for the following
4.4.1. Software
4.4.1.1. Market estimates and forecasts 2017 to 2030 (USD Million)
4.4.2. Services
4.4.2.1. Market estimates and forecasts 2017 to 2030 (USD Million)
Chapter 5. Generative AI Market: Technology Estimates & Trend Analysis
5.1. Technology Market Share, 2023 & 2030
5.2. Segment Dashboard
5.3. Global Generative AI Market by Technology Outlook
5.4. Market Size & Forecasts and Trend Analyses, 2017 to 2030 for the following
5.4.1. Generative Adversarial Networks (GANs)
5.4.1.1. Market estimates and forecasts 2017 to 2030 (USD Million)
5.4.2. Transformers
5.4.2.1. Market estimates and forecasts 2017 to 2030 (USD Million)
5.4.3. Variational Auto-encoders
5.4.3.1. Market estimates and forecasts 2017 to 2030 (USD Million)
5.4.4. Diffusion Networks
5.4.4.1. Market estimates and forecasts 2017 to 2030 (USD Million)
Chapter 6. Generative AI Market: End-use Estimates & Trend Analysis
6.1. End-use Market Share, 2023 & 2030
6.2. Segment Dashboard
6.3. Global Generative AI Market by Application Outlook
6.4. Market Size & Forecasts and Trend Analyses, 2017 to 2030 for the following
6.4.1. Media & Entertainment
6.4.1.1. Market estimates and forecasts 2017 to 2030 (USD million)
6.4.2. BFSI
6.4.2.1. Market estimates and forecasts 2017 to 2030 (USD Million)
6.4.3. IT & Telecommunication
6.4.3.1. Market estimates and forecasts 2017 to 2030 (USD Million)
6.4.4. Healthcare
6.4.4.1. Market estimates and forecasts 2017 to 2030 (USD Million)
6.4.5. Automotive & Transportation
6.4.5.1. Market estimates and forecasts 2017 to 2030 (USD Million)
6.4.6. Gaming
6.4.6.1. Market estimates and forecasts 2017 to 2030 (USD Million)
6.4.7. Others
6.4.7.1. Market estimates and forecasts 2017 to 2030 (USD Million)
Chapter 7. Generative AI Market: Application Estimates & Trend Analysis
7.1. Application Market Share, 2023 & 2030
7.2. Segment Dashboard
7.3. Global Generative AI Market by Application Outlook
7.4. Market Size & Forecasts and Trend Analyses, 2017 to 2030 for the following
7.4.1. Computer Vision
7.4.1.1. Market estimates and forecasts 2017 to 2030 (USD million)
7.4.2. NLP
7.4.2.1. Market estimates and forecasts 2017 to 2030 (USD Million)
7.4.3. Robotics and Automation
7.4.3.1. Market estimates and forecasts 2017 to 2030 (USD Million)
7.4.4. Content Generation
7.4.4.1. Market estimates and forecasts 2017 to 2030 (USD Million)
7.4.5. Chatbots and Intelligent Virtual Assistants
7.4.5.1. Market estimates and forecasts 2017 to 2030 (USD Million)
7.4.6. Predictive Analytics
7.4.6.1. Market estimates and forecasts 2017 to 2030 (USD Million)
7.4.7. Others
7.4.7.1. Market estimates and forecasts 2017 to 2030 (USD Million)
Chapter 8. Generative AI Market: Model Estimates & Trend Analysis
8.1. Model Market Share, 2023 & 2030
8.2. Segment Dashboard
8.3. Global Generative AI Market by Model Outlook
8.4. Market Size & Forecasts and Trend Analyses, 2017 to 2030 for the following
8.4.1. Large Language Models
8.4.1.1. Market estimates and forecasts 2017 to 2030 (USD million)
8.4.2. Image & Video Generative Models
8.4.2.1. Market estimates and forecasts 2017 to 2030 (USD Million)
8.4.3. Multi-modal Generative Models
8.4.3.1. Market estimates and forecasts 2017 to 2030 (USD Million)
8.4.4. Others
8.4.4.1. Market estimates and forecasts 2017 to 2030 (USD Million)
Chapter 9. Generative AI Market: Regional Estimates & Trend Analysis
9.1. Regional Market Share Analysis, 2023 & 2030
9.2. Regional Market Dashboard
9.3. Global Regional Market Snapshot
9.4. Market Size, & Forecasts Trend Analysis, 2017 to 2030:
9.5. North America
9.5.1. U.S.
9.5.1.1. Key country dynamics
9.5.1.2. Regulatory framework/ reimbursement structure
9.5.1.3. Competitive scenario
9.5.1.4. U.S. market estimates and forecasts 2017 to 2030 (USD Million)
9.5.2. Canada
9.5.2.1. Key country dynamics
9.5.2.2. Regulatory framework/ reimbursement structure
9.5.2.3. Competitive scenario
9.5.2.4. Canada market estimates and forecasts 2017 to 2030 (USD Million)
9.6. Europe
9.6.1. UK
9.6.1.1. Key country dynamics
9.6.1.2. Regulatory framework/ reimbursement structure
9.6.1.3. Competitive scenario
9.6.1.4. UK market estimates and forecasts 2017 to 2030 (USD Million)
9.6.2. Germany
9.6.2.1. Key country dynamics
9.6.2.2. Regulatory framework/ reimbursement structure
9.6.2.3. Competitive scenario
9.6.2.4. Germany market estimates and forecasts 2017 to 2030 (USD Million)
9.6.3. France
9.6.3.1. Key country dynamics
9.6.3.2. Regulatory framework/ reimbursement structure
9.6.3.3. Competitive scenario
9.6.3.4. France market estimates and forecasts 2017 to 2030 (USD Million)
9.6.4. Italy
9.6.4.1. Key country dynamics
9.6.4.2. Regulatory framework/ reimbursement structure
9.6.4.3. Competitive scenario
9.6.4.4. Italy market estimates and forecasts 2017 to 2030 (USD Million)
9.7. Asia Pacific
9.7.1. Japan
9.7.1.1. Key country dynamics
9.7.1.2. Regulatory framework/ reimbursement structure
9.7.1.3. Competitive scenario
9.7.1.4. Japan market estimates and forecasts 2017 to 2030 (USD Million)
9.7.2. China
9.7.2.1. Key country dynamics
9.7.2.2. Regulatory framework/ reimbursement structure
9.7.2.3. Competitive scenario
9.7.2.4. China market estimates and forecasts 2017 to 2030 (USD Million)
9.7.3. India
9.7.3.1. Key country dynamics
9.7.3.2. Regulatory framework/ reimbursement structure
9.7.3.3. Competitive scenario
9.7.3.4. India market estimates and forecasts 2017 to 2030 (USD Million)
9.7.4. Australia
9.7.4.1. Key country dynamics
9.7.4.2. Regulatory framework/ reimbursement structure
9.7.4.3. Competitive scenario
9.7.4.4. Australia market estimates and forecasts 2017 to 2030 (USD Million)
9.7.5. South Korea
9.7.5.1. Key country dynamics
9.7.5.2. Regulatory framework/ reimbursement structure
9.7.5.3. Competitive scenario
9.7.5.4. South Korea market estimates and forecasts 2017 to 2030 (USD Million)
9.8. Latin America
9.8.1. Brazil
9.8.1.1. Key country dynamics
9.8.1.2. Regulatory framework/ reimbursement structure
9.8.1.3. Competitive scenario
9.8.1.4. Brazil market estimates and forecasts 2017 to 2030 (USD Million)
9.8.2. Mexico
9.8.2.1. Key country dynamics
9.8.2.2. Regulatory framework/ reimbursement structure
9.8.2.3. Competitive scenario
9.8.2.4. Mexico market estimates and forecasts 2017 to 2030 (USD Million)
9.8.3. Argentina
9.8.3.1. Key country dynamics
9.8.3.2. Regulatory framework/ reimbursement structure
9.8.3.3. Competitive scenario
9.8.3.4. Argentina market estimates and forecasts 2017 to 2030 (USD Million)
9.9. MEA
9.9.1. South Africa
9.9.1.1. Key country dynamics
9.9.1.2. Regulatory framework/ reimbursement structure
9.9.1.3. Competitive scenario
9.9.1.4. South Africa market estimates and forecasts 2017 to 2030 (USD Million)
9.9.2. Saudi Arabia
9.9.2.1. Key country dynamics
9.9.2.2. Regulatory framework/ reimbursement structure
9.9.2.3. Competitive scenario
9.9.2.4. Saudi Arabia market estimates and forecasts 2017 to 2030 (USD Million)
9.9.3. UAE
9.9.3.1. Key country dynamics
9.9.3.2. Regulatory framework/ reimbursement structure
9.9.3.3. Competitive scenario
9.9.3.4. UAE market estimates and forecasts 2017 to 2030 (USD Million)
Chapter 10. Competitive Landscape
10.1. Recent Developments & Impact Analysis, By Key Market Participants
10.2. Company/Competition Categorization
10.3. Vendor Landscape
10.3.1. List of key distributors and channel partners
10.3.2. Key customers
10.4. Company Profiles
10.4.1. Adobe Inc.
10.4.1.1. Company overview
10.4.1.2. Financial performance
10.4.1.3. Product benchmarking
10.4.1.4. Strategic initiatives
10.4.2. Amazon Web Services, Inc.
10.4.2.1. Company overview
10.4.2.2. Financial performance
10.4.2.3. Product benchmarking
10.4.2.4. Strategic initiatives
10.4.3. D-ID
10.4.3.1. Company overview
10.4.3.2. Financial performance
10.4.3.3. Product benchmarking
10.4.3.4. Strategic initiatives
10.4.4. Genie AI Ltd.
10.4.4.1. Company overview
10.4.4.2. Financial performance
10.4.4.3. Product benchmarking
10.4.4.4. Strategic initiatives
10.4.5. Google LLC
10.4.5.1. Company overview
10.4.5.2. Financial performance
10.4.5.3. Product benchmarking
10.4.5.4. Strategic initiatives
10.4.6. International Business Machines Corporation
10.4.6.1. Company overview
10.4.6.2. Financial performance
10.4.6.3. Product benchmarking
10.4.6.4. Strategic initiatives
10.4.7. Microsoft Corporation
10.4.7.1. Company overview
10.4.7.2. Financial performance
10.4.7.3. Product benchmarking
10.4.7.4. Strategic initiatives
10.4.8. MOSTLY AI Inc.
10.4.8.1. Company overview
10.4.8.2. Financial performance
10.4.8.3. Product benchmarking
10.4.8.4. Strategic initiatives
10.4.9. Rephrase.ai
10.4.9.1. Company overview
10.4.9.2. Financial performance
10.4.9.3. Product benchmarking
10.4.9.4. Strategic initiatives
10.4.10. Synthesia
10.4.10.1. Company overview
10.4.10.2. Financial performance
10.4.10.3. Product benchmarking
10.4.10.4. Strategic initiatives