The generative AI market is projected to grow from USD 71.36 billion in 2025 to USD 890.59 billion by 2032, at a CAGR of 43.4% during 2025-2032. The market is growing fast, driven by rising enterprise adoption, growing demand for multimodal AI solutions, and increased use of generative AI for automating content creation and other business tasks. Companies across industries are using generative AI to improve efficiency, reduce costs, and deliver better customer experiences. However, there are also some restraints. High infrastructure and computing costs make it harder for smaller businesses to adopt the technology. In addition, issues like AI models generating biased or incorrect content (known as hallucinations) raise concerns about reliability and trust. While the potential is high, vendors must address these restraints to unlock the full value of generative AI.
Scope of the Report
Years Considered for the Study
2020-2032
Base Year
2024
Forecast Period
2025-2032
Units Considered
USD (Billion)
Segments
Offering, Data Modality, Application, End User, and Region
Regions covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
"By end user, healthcare & life sciences segment to register fastest growth rate during forecast period"
The healthcare & life sciences segment within the generative AI market is expected to grow at a high CAGR during the forecast period. This growth is driven by the increasing use of generative AI for drug discovery, medical imaging, patient data analysis, and personalized treatment plans. Generative AI helps accelerate research by creating synthetic data and simulating complex biological processes, reducing time and costs. It also supports healthcare providers by improving diagnostics and automating routine tasks, enhancing patient care. With rising healthcare data and the need for efficient, accurate solutions, generative AI is becoming a vital tool in this industry, creating strong opportunities for vendors and innovators.
"By offering, software segment to account for largest market share by 2032"
The software segment is expected to hold the largest share of the generative AI market by 2032, overtaking gen AI infrastructure. This is because software forms the core of generative AI applications, enabling tasks like text generation, image creation, code generation, and virtual assistance. With the rise of user-friendly platforms, APIs, and pre-trained models, businesses across industries are adopting generative AI software to improve productivity, automate processes, and enhance customer engagement. Cloud-based deployment and easy integration with existing systems are further boosting software adoption. As demand grows for creative and intelligent applications, the software segment will eventually lead the market, offering strong opportunities for vendors and developers.
"By Region, North America to hold largest market share in 2025 and Asia Pacific to register fastest growth rate during forecast period"
North America is estimated to hold the largest share of the generative AI market in 2025. This is mainly due to the strong presence of leading technology companies such as Microsoft, Google, OpenAI, NVIDIA, and AWS, which are continuously advancing generative AI capabilities. The region also benefits from a mature digital infrastructure, high cloud adoption, and strong investments in AI research and innovation. Enterprises across sectors like healthcare, BFSI, retail, and media are increasingly adopting generative AI solutions to automate content creation, enhance customer experiences, and improve operational efficiency. In addition, favorable government support and a large talent pool contribute to early adoption and rapid innovation. In January 2025, the US Government enforced Executive Order 14179, aiming to enhance US leadership in AI by removing certain regulatory barriers and promoting AI development free from ideological bias. Additionally, Microsoft's USD 3.3 billion investment in an AI hub in Wisconsin underscores the region's ongoing commitment to Generative AI advancement.
The generative AI market is expected to register the highest CAGR in the Asia Pacific region during the forecast period. Countries like China, India, Japan, and South Korea are making strong investments in AI development and digital transformation. Growing demand for AI-driven automation in industries such as manufacturing, healthcare, and e-commerce is driving rapid adoption. Governments in the region are also introducing supportive policies and funding initiatives to boost AI research and adoption. Moreover, the rise of local tech startups and increased awareness among enterprises about the benefits of generative AI are creating new business opportunities. As digitalization spreads across both developed and developing countries in Asia Pacific, the region is set to become a key driver of generative AI growth globally.
Breakdown of Primaries
In-depth interviews were conducted with chief executive officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the generative AI market.
By Company: Tier I - 22%, Tier II - 31%, and Tier III - 47%
By Designation: C-Level Executives - 31%, D-Level Executives - 46%, and others - 23%
By Region: North America - 40%, Europe - 18%, Asia Pacific - 29%, Middle East & Africa - 5%, and Latin America - 8%
The report includes a study of key players offering generative AI solutions. It profiles major vendors in the generative AI market. The major players in the generative AI market include IBM (US), NVIDIA (US), OpenAI (US), Anthropic (US), Meta (US), HPE (US), AMD (US), Oracle (US), Innodata (US), iMerit (US), Salesforce (US), Telus Digital (US), Microsoft (US), Google (US), AWS (US), Adobe (US), Accenture (Ireland), Capgemini (France), Centific (US), Fractal Analytics (US), Tiger Analytics (US), Quantiphi (US), Databricks (US), Dialpad (US), Appen (Australia), Insilico Medicine (Hong Kong), Simplified (US), AI21 Labs (Israel), Hugging Face (US), Persado (US), Copy.ai (US), Synthesis AI (US), Hypotenuse AI (US), Together AI (US), Mistral AI (France), Adept (US), Stability AI (UK), Lightricks (Israel), Cohere (Canada), Writesonic (US), Inflection AI (US), Colossyan (UK), Jasper (US), Runway (US), Inworld AI (US), Typeface (US), Upstage (South Korea), H2O.ai (US), Speechify (US), Midjourney (US), Fireflies (US), Synthesia (UK), Mostly AI (Austria), Forethought (US), Character.ai (US), Cursor (US), DeepSeek (China), XAI (US), Abridge (US), Perplexity AI (US), SambaNova (US), Scale AI (US), Labelbox (US), and HQE Systems (US).
Research Coverage
This research report categorizes the generative AI market by Offering (Infrastructure, Software, and Services), Data Modality (Text, Image, Video, Audio & Speech, and Multimodal), Application (Business Intelligence & Visualization, Content Management, Synthetic Data Management, Search & Discovery, Automation & Integration, and Other Applications), End User (Consumers and Enterprises [BFSI, Retail & E-commerce, Transportation & Logistics, Government & Defense, Healthcare & Life Sciences, Telecommunication, Energy & Utilities, Manufacturing, Software & Technology Providers, Media & Entertainment, and Other Enterprises]), and Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the generative AI market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions, and services; key strategies; contracts, partnerships, agreements, new product & service launches, and mergers & acquisitions; and recent developments associated with the generative AI market. This report covers a competitive analysis of upcoming startups in the generative AI market ecosystem.
Key Benefits of Buying the Report
The report would provide the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall generative AI market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights to better position their business and plan suitable go-to-market strategies. It also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (Innovation of cloud storage to enable easy access to data, Evolution of AI and deep learning, Rise in content creation and creative applications), restraints (High costs associated with training data preparation, Issues related to bias and inaccurately generated output, Risks associated with data breaches and sensitive information leakage), opportunities (Increase in deployment of large language models, Growth in interest of enterprises in commercializing synthetic images, Robust improvement in generative ML leading to human baseline performance), and challenges (Concerns regarding misuse of generative AI for illegal activities, Quality of output generated by generative AI models, Computational complexity and technical challenges of generative AI).
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the generative AI market.
Market Development: Comprehensive information about lucrative markets - the report analyses the generative AI market across varied regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the generative AI market.
Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players like IBM (US), NVIDIA (US), OpenAI (US), Anthropic (US), Meta (US), HPE (US), AMD (US), Oracle (US), Innodata (US), iMerit (US), Salesforce (US), Telus Digital (US), Microsoft (US), Google (US), AWS (US), Adobe (US), Accenture (Ireland), Capgemini (France), Centific (US), Fractal Analytics (US), Tiger Analytics (US), Quantiphi (US), Databricks (US), Dialpad (US), Appen (Australia), Insilico Medicine (Hong Kong), Simplified (US), AI21 Labs (Israel), Hugging Face (US), Persado (US), Copy.ai (US), Synthesis AI (US), Hypotenuse AI (US), Together AI (US), Mistral AI (France), Adept (US), Stability AI (UK), Lightricks (Israel), Cohere (Canada), Writesonic (US), Inflection AI (US), Colossyan (UK), Jasper (US), Runway (US), Inworld AI (US), Typeface (US), Upstage (South Korea), H2O.ai (US), Speechify (US), Midjourney (US), Fireflies (US), Synthesia (UK), Mostly AI (Austria), Forethought (US), Character.ai (US), Cursor (US), DeepSeek (China), XAI (US), Abridge (US), Perplexity AI (US), SambaNova (US), Scale AI (US), Labelbox (US), and HQE Systems (US), among others, in the generative AI market. The report also helps stakeholders understand the pulse of the generative AI market and provides them with information on key market drivers, restraints, challenges, and opportunities.
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 MARKET SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 STAKEHOLDERS
1.6 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
2.1.2.1 Breakup of primary profiles
2.1.2.2 Key industry insights
2.2 MARKET BREAKUP AND DATA TRIANGULATION
2.3 MARKET SIZE ESTIMATION
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
2.4 MARKET FORECAST
2.5 RESEARCH ASSUMPTIONS
2.6 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN GENERATIVE AI MARKET
4.2 GENERATIVE AI MARKET: TOP THREE DATA MODALITIES
4.3 NORTH AMERICA: GENERATIVE AI MARKET, BY OFFERING AND END USER
4.4 GENERATIVE AI MARKET: BY REGION
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Innovation of cloud storage to enable easy data access
5.2.1.2 Evolution of AI and deep learning
5.2.1.3 Rise in content creation and creative applications
5.2.2 RESTRAINTS
5.2.2.1 High costs associated with training data preparation
5.2.2.2 Issues related to bias and inaccurately generated output
5.2.2.3 Risks associated with data breaches and sensitive information leakage
5.2.3 OPPORTUNITIES
5.2.3.1 Increasing deployment of large language models
5.2.3.2 Growing interest of enterprises in commercializing synthetic images
5.2.3.3 Robust improvement in generative AI models leading to human baseline performance
5.2.4 CHALLENGES
5.2.4.1 Use of generative AI for illegal activities
5.2.4.2 Quality of output generated by generative AI models
5.2.4.3 Computational complexity and technical challenges of generative AI
5.3 EVOLUTION OF GENERATIVE AI
5.4 GENERATIVE AI MATURITY CURVE
5.5 SUPPLY CHAIN ANALYSIS
5.6 ECOSYSTEM ANALYSIS
5.6.1 GENERATIVE AI INFRASTRUCTURE PROVIDERS
5.6.2 GENERATIVE AI SOFTWARE PROVIDERS
5.6.3 GENERATIVE AI SERVICE PROVIDERS
5.7 IMPACT OF 2025 US TARIFF - GENERATIVE AI MARKET
5.7.1 INTRODUCTION
5.7.2 KEY TARIFF RATES
5.7.3 PRICE IMPACT ANALYSIS
5.7.3.1 Strategic shifts and emerging trends
5.7.4 IMPACT ON COUNTRY/REGION
5.7.4.1 US
5.7.4.2 China
5.7.4.3 Europe
5.7.4.4 Asia Pacific (excluding China)
5.7.5 IMPACT ON END-USE INDUSTRIES
5.7.5.1 BFSI
5.7.5.2 Telecommunications
5.7.5.3 Government & Public Sector
5.7.5.4 Healthcare & Life Sciences
5.7.5.5 Manufacturing
5.7.5.6 Media & Entertainment
5.7.5.7 Retail & E-commerce
5.7.5.8 Software & Technology Providers
5.8 INVESTMENT AND FUNDING SCENARIO
5.9 CASE STUDY ANALYSIS
5.9.1 FORTUNE ANALYTICS - AI-DRIVEN BUSINESS INSIGHTS THROUGH ACCENTURE TECHNOLOGY
5.9.2 VODAFONE GROUP PLC UNCOVERED KEY TRENDS AND RICH INSIGHTS THROUGH PERSADO'S MOTIVATION AI
5.9.3 WPP PARTNERED WITH SYNTHESIA - TRAINED 50,000 EMPLOYEES WITH AI VIDEOS
5.9.4 OPPLUS & INBENTA - AI-DRIVEN CUSTOMER SERVICE TRANSFORMATION FOR BBVA
5.9.5 CISCO SCALED VIDEO CONTENT LOCALIZATION USING LUMEN5
5.10 TECHNOLOGY ANALYSIS
5.10.1 KEY TECHNOLOGIES
5.10.1.1 Foundation models
5.10.1.2 Transformer architectures
5.10.1.3 Diffusion models
5.10.1.4 Generative adversarial networks (GANs)
5.10.1.5 Reinforcement learning with human feedback (RLHF)
5.10.2 COMPLEMENTARY TECHNOLOGIES
5.10.2.1 High-performance computing (HPC)
5.10.2.2 Vector databases
5.10.2.3 Retrieval-augmented generation (RAG)
5.10.2.4 MLOps & LLMOps
5.10.2.5 Model monitoring & governance
5.10.3 ADJACENT TECHNOLOGIES
5.10.3.1 Natural language processing (NLP)
5.10.3.2 Computer vision
5.10.3.3 Causal AI
5.10.3.4 Knowledge graphs
5.10.3.5 Speech recognition & synthesis
5.11 TARIFF AND REGULATORY LANDSCAPE
5.11.1 TARIFF RELATED TO PROCESSORS AND CONTROLLERS (HSN: 854231)
5.11.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
5.11.3 REGULATIONS
5.11.3.1 North America
5.11.3.1.1 SCR 17: Artificial Intelligence Bill (California)
5.11.3.1.2 S1103: Artificial Intelligence Automated Decision Bill (Connecticut)
5.11.3.1.3 National Artificial Intelligence Initiative Act (NAIIA) (US)
5.11.3.1.4 Artificial Intelligence and Data Act (AIDA) (Canada)
5.11.3.2 Europe
5.11.3.2.1 European Union (EU) - Artificial Intelligence Act (AIA)
5.11.3.2.2 General Data Protection Regulation (Europe)
5.11.3.3 Asia Pacific
5.11.3.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services (China)
5.11.3.3.2 National AI Strategy (Singapore)
5.11.3.3.3 Hiroshima AI Process Comprehensive Policy Framework (Japan)
5.11.3.4 Middle East & Africa
5.11.3.4.1 National Strategy for Artificial Intelligence (UAE)
5.11.3.4.2 National Artificial Intelligence Strategy (Qatar)
5.11.3.4.3 AI Ethics Principles and Guidelines (Dubai)