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U.S. Generative AI Market Size, Share & Trends Analysis Report By Component (Software, Services), By Technology, By End-use, By Application, By Model, And Segment Forecasts, 2024 - 2030

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    Report

  • 80 Pages
  • February 2024
  • Region: United States
  • Grand View Research
  • ID: 5943913
Description Jump to:
The U.S. generative AI market size is anticipated to reach USD 33.78 billion by 2030. The market is expected to expand at a CAGR of 36.3% from 2024 to 2030. Increasing data across diverse sectors such as finance, healthcare, and entertainment provides excellent resources for generative AI models, empowering them to generate more precise and varied outputs, thus contributing significantly to the expansion of generative AI in the U.S.

COVID 19 had a positive impact on the U.S. generative AI market. The pandemic accelerated digital transformation across industries as organizations aimed at technological solutions to adapt to remote work, virtual collaboration, and shifting consumer behaviors. Increased reliance on digital platforms and automation created a demand for advanced AI technologies, including generative AI, to streamline processes, personalize customer experiences, and optimize operations. As businesses looked for innovative ways to stay competitive in the face of uncertainty, investment in generative AI solutions surged, thus driving the growth of the U.S. generative AI market growth.

The expansion of the AI tool ecosystem is a significant factor fueling the growth of the generative AI market. As the field of artificial intelligence continues to evolve, various specialized tools and platforms are emerging to support the development and deployment of generative AI models. These tools offer developers and researchers a variety of capabilities, ranging from model training and optimization to deployment and monitoring. Many established companies are funding companies providing such tools to accelerate the advancement of generative AI technology. This investment not only signifies the market potential of generative AI but also underscores the strategic importance of having access to advanced tools and platforms in driving innovation and gaining a competitive edge. For instance, in June 2023, Runway, an AI research company developing next-gen creative tools, raised USD 141 million in its series C from Salesforce Ventures, Google, NVIDIA, and other existing shareholders. The company intends to utilize these funds to enhance its in-house research endeavors, enlarge its highly skilled team, and persist in delivering advanced multi-modal AI systems to the market while developing innovative and user-friendly product offerings.

Investment in the machine learning and artificial intelligence sectors to support the generative AI market will drive the U.S. market. As investors recognize the transformative potential of generative AI across industries, they are increasingly allocating capital to startups, research institutions, and established companies developing cutting-edge technologies and solutions.

U.S. Generative AI Market Report Highlights

  • Based on components, the software segment accounted for the highest revenue share of 64.8% in 2023 and is expected to retain its position over the forecast period. The segment's growth is attributed to the rising need for automation, increased investment in artificial intelligence, and favorable regulatory environments in the region
  • Based on technology, the transformers segment dominated the market in 2023 and is expected to grow at a significant CAGR of 35.6% over the forecast period. It can be attributed to the increasing application of transformers for various applications, such as text-to-image AI, which transforms textual input into visual output, contributing to this trend
  • Regarding end-use, the media & entertainment segment accounted for the maximum revenue share in 2023. The increased utilization of generative AI to enhance campaign and advertising journalism is expected to drive the segment's growth
  • In February 2024, Google LLC launched ImageFX, an AI-powered tool for image creation. This GenAI model that Google’s DeepMind team designed offers a prompt-based UI to edit or create images. It creates images with simple text prompts and modifies them using expressive chips


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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. Estimates and forecasts timeline
1.3. Research Methodology
1.4. Information Procurement
1.4.1. Purchased database
1.4.2. 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 U.S.
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. U.S. 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. Increasing adoption of digital technologies across industries
3.2.1.2. Growing focus on digital transformation and industry 4.0
3.2.2. Market restraint analysis
3.2.2.1. Increasing data privacy and security concerns
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. U.S. Generative AI Market: Component Estimates & Trends Analysis
4.1. Component Market Share, 2023 & 2030
4.2. Segment Dashboard
4.3. U.S. Generative AI Market by Component Outlook
4.4. Market Size & Forecasts and Trends Analysis, 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. U.S. Generative AI Market: Technology Estimates & Trends Analysis
5.1. Technology Market Share, 2023 & 2030
5.2. Segment Dashboard
5.3. U.S. Generative AI Market by Technology Outlook
5.4. Market Size & Forecasts and Trends Analysis, 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. U.S. Generative AI Market: End-use Estimates & Trends Analysis
6.1. End-use Market Share, 2023 & 2030
6.2. Segment Dashboard
6.3. U.S. Generative AI Market by End-use Outlook
6.4. Market Size & Forecasts and Trends Analysis, 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. U.S. Generative AI Market: Application Estimates & Trends Analysis
7.1. Application Market Share, 2023 & 2030
7.2. Segment Dashboard
7.3. U.S. Generative AI Market by Application Outlook
7.4. Market Size & Forecasts and Trends Analysis, 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. U.S. Generative AI Market: Model Estimates & Trends Analysis
8.1. Model Market Share, 2023 & 2030
8.2. Segment Dashboard
8.3. U.S. Generative AI Market by Model Outlook
8.4. Market Size & Forecasts and Trends Analysis, 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. Competitive Landscape
9.1. Recent Developments & Impact Analysis, By Key Market Participants
9.2. Company/Competition Categorization
9.3. Vendor Landscape
9.3.1. List of key distributors and channel partners
9.3.2. Key customers
9.4. Company Profiles
9.4.1. Google LLC
9.4.1.1. Company overview
9.4.1.2. Financial performance
9.4.1.3. Product benchmarking
9.4.1.4. Strategic initiatives
9.4.2. Amazon Web Services, Inc.
9.4.2.1. Company overview
9.4.2.2. Financial performance
9.4.2.3. Product benchmarking
9.4.2.4. Strategic initiatives
9.4.3. IBM
9.4.3.1. Company overview
9.4.3.2. Financial performance
9.4.3.3. Product benchmarking
9.4.3.4. Strategic initiatives
9.4.4. Microsoft
9.4.4.1. Company overview
9.4.4.2. Financial performance
9.4.4.3. Product benchmarking
9.4.4.4. Strategic initiatives
9.4.5. Hugging Face
9.4.5.1. Company overview
9.4.5.2. Financial performance
9.4.5.3. Product benchmarking
9.4.5.4. Strategic initiatives
9.4.6. Cohere
9.4.6.1. Company overview
9.4.6.2. Financial performance
9.4.6.3. Product benchmarking
9.4.6.4. Strategic initiatives
9.4.7. Tome.App
9.4.7.1. Company overview
9.4.7.2. Financial performance
9.4.7.3. Product benchmarking
9.4.7.4. Strategic initiatives
9.4.8. AssemblyAI
9.4.8.1. Company overview
9.4.8.2. Financial performance
9.4.8.3. Product benchmarking
9.4.8.4. Strategic initiatives
9.4.9. Midjourney
9.4.9.1. Company overview
9.4.9.2. Financial performance
9.4.9.3. Product benchmarking
9.4.9.4. Strategic initiatives
9.4.10. Klaviyo
9.4.10.1. Company overview
9.4.10.2. Financial performance
9.4.10.3. Product benchmarking
9.4.10.4. Strategic initiatives
List of Tables
Table 1 List of abbreviations
Table 2 U.S. generative AI market, by component, 2017 - 2030 (USD Million)
Table 3 U.S. generative AI market, by technology, 2017 - 2030 (USD Million)
Table 4 U.S. generative AI market, by end-use, 2017 - 2030 (USD Million)
Table 5 U.S. generative AI market, by application, 2017 - 2030 (USD Million)
Table 6 U.S. generative AI market, by model, 2017 - 2030 (USD Million)
List of Figures
Fig. 1 Market research process
Fig. 2 U.S. generative AI market segmentation
Fig. 3 U.S. generative AI technology landscape
Fig. 4 Information procurement
Fig. 5 Data analysis models
Fig. 6 Market formulation and validation
Fig. 7 Data validating & publishing
Fig. 8 Market snapshot
Fig. 9 Segment snapshot (1/2)
Fig. 10 Segment snapshot (2/2)
Fig. 11 Competitive landscape snapshot
Fig. 12 U.S. generative AI market size and growth prospects (USD Million)
Fig. 13 U.S. generative AI Market: Industry value chain analysis
Fig. 14 U.S. generative AI Market: Market dynamics
Fig. 15 U.S. generative AI Market: PORTER's Analysis
Fig. 16 U.S. generative AI Market: PESTEL Analysis
Fig. 17 U.S. generative AI market: Component movement analysis
Fig. 18 U.S. generative AI market: Component outlook and key takeaways
Fig. 19 Software market estimates and forecasts, 2017 - 2030
Fig. 20 Service estimates and forecasts, 2017 - 2030
Fig. 21 U.S. generative AI Market: Technology movement analysis
Fig. 22 U.S. generative AI market: Technology outlook and key takeaways
Fig. 23 Generative Adversarial Networks (GANs) market estimates and forecasts, 2017 - 2030
Fig. 24 Transformers market estimates and forecasts, 2017 - 2030
Fig. 25 Variational auto-encoders market estimates and forecasts, 2017 - 2030
Fig. 26 Diffusion networks market estimates and forecasts, 2017 - 2030
Fig. 27 U.S. generative AI market: End-use movement analysis
Fig. 28 U.S. generative AI market: End-use outlook and key takeaways
Fig. 29 Media & entertainment market estimates and forecasts, 2017 - 2030
Fig. 30 BFSI market estimates and forecasts, 2017 - 2030
Fig. 31 IT & Telecommunication market estimates and forecasts, 2017 - 2030
Fig. 32 Healthcare market estimates and forecasts, 2017 - 2030
Fig. 33 Automotive & transportation market estimates and forecasts, 2017 - 2030
Fig. 34 Gaming market estimates and forecasts, 2017 - 2030
Fig. 35 Others market estimates and forecasts, 2017 - 2030
Fig. 36 U.S. generative AI market: Application movement analysis
Fig. 37 U.S. generative AI market: Application outlook and key takeaways
Fig. 38 Computer vision market estimates and forecasts, 2017 - 2030
Fig. 39 NLP market estimates and forecasts, 2017 - 2030
Fig. 40 Robotics and automation market estimates and forecasts, 2017 - 2030
Fig. 41 Content generation market estimates and forecasts, 2017 - 2030
Fig. 42 Chatbots and intelligent virtual assistants market estimates and forecasts, 2017 - 2030
Fig. 43 Predictive analytics market estimates and forecasts, 2017 - 2030
Fig. 44 Others market estimates and forecasts, 2017 - 2030
Fig. 45 U.S. generative AI Market: Model movement analysis
Fig. 46 U.S. generative AI market: Model outlook and key takeaways
Fig. 47 Large language models market estimates and forecasts, 2017 - 2030
Fig. 48 Image & video generative models market estimates and forecasts, 2017 - 2030
Fig. 49 Multi-modal generative models market estimates and forecasts, 2017 - 2030
Fig. 50 Others market estimates and forecasts, 2017 - 2030
Fig. 51 Key company categorization
Fig. 52 Company market positioning
Fig. 53 Key company market share analysis, 2023
Fig. 54 Strategic framework

Companies Mentioned

  • Google LLC
  • Amazon Web Services, Inc.
  • IBM
  • Microsoft
  • Hugging Face
  • Cohere
  • Tome.App
  • AssemblyAI
  • Midjourney
  • Klaviyo

Methodology

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About the Generative AI Market

The Generative AI market is a subset of Artificial Intelligence (AI) that focuses on the development of algorithms and models that can generate new data from existing data. Generative AI is used to create new data from existing data, such as images, text, and audio. This technology is used to create new data that can be used for various applications, such as natural language processing, image recognition, and machine learning. Generative AI can also be used to create new data from existing data, such as images, text, and audio. Generative AI is used in a variety of industries, such as healthcare, finance, and retail. Generative AI can be used to create new data from existing data, such as images, text, and audio. This technology can also be used to create new data from existing data, such as images, text, and audio. Some companies in the Generative AI market include Google, Microsoft, IBM, Amazon, and OpenAI. Show Less Read more

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