Generative AI Market by Software (Foundation Models, Model Enablement & Orchestration Tools, Gen AI SaaS), Modality (Text, Code, Video, Image, Multimodal), Application (Content Management, BI & Visualization, Search & Discovery) - Global Forecast to 2032
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.
“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.
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.
“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%
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.
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)
5.11.3.5 Latin America
5.11.3.5.1 Santiago Declaration (Chile)
5.11.3.5.2 Brazilian Artificial Intelligence Strategy (EBIA)
5.12 TRADE ANALYSIS
5.12.1 EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
5.12.2 IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
5.13 PATENT ANALYSIS
5.13.1 METHODOLOGY
5.13.2 PATENTS FILED, BY DOCUMENT TYPE
5.13.3 INNOVATION AND PATENT APPLICATIONS
5.14 PRICING ANALYSIS
5.14.1 AVERAGE SELLING PRICE OF OFFERING, BY KEY PLAYER, 2025
5.14.2 AVERAGE SELLING PRICE, BY APPLICATION, 2025
5.15 KEY CONFERENCES AND EVENTS
5.16 PORTER’S FIVE FORCES ANALYSIS
5.16.1 THREAT OF NEW ENTRANTS
5.16.2 THREAT OF SUBSTITUTES
5.16.3 BARGAINING POWER OF SUPPLIERS
5.16.4 BARGAINING POWER OF BUYERS
5.16.5 INTENSITY OF COMPETITION RIVALRY
5.17 KEY STAKEHOLDERS AND BUYING CRITERIA
5.17.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.17.2 BUYING CRITERIA
5.18 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
6 GENERATIVE AI MARKET, BY OFFERING
6.1 INTRODUCTION
6.1.1 OFFERING: GENERATIVE AI MARKET DRIVERS
6.2 INFRASTRUCTURE
6.2.1 COMPUTE
6.2.1.1 Compute power drives model training and inference
6.2.1.2 Graphics processing units (GPUs)
6.2.1.3 Central processing units (CPUs)
6.2.1.4 Field-programmable gate arrays (FPGAs)
6.2.2 MEMORY
6.2.2.1 High-performance memory to sustain AI workload demands
6.2.2.2 Double data rate (DDR)
6.2.2.3 High bandwidth memory (HBM)
6.2.3 NETWORKING HARDWARE
6.2.3.1 Fast, scalable connectivity to support distributed AI systems
6.2.3.2 NIC/Network adapters
6.2.3.2.1 Ethernet
6.2.3.2.2 InfiniBand
6.2.3.3 Interconnects
6.2.4 STORAGE
6.2.4.1 Storage systems built for speed, scale, and AI readiness
6.3 SOFTWARE
6.3.1 FOUNDATION MODELS
6.3.1.1 Foundation models power diverse, scalable generative AI applications
6.3.2 MODEL ENABLEMENT & ORCHESTRATION TOOLS
6.3.2.1 Tooling ecosystem critical to operationalizing generative AI at scale
6.3.2.2 Model hosting & access platforms
6.3.2.3 LLMOps & prompt engineering tools
6.3.2.4 Model fine-tuning tools
6.3.2.5 Model monitoring & evaluation tools
6.3.2.6 Governance & risk platforms
6.3.3 GEN AI SAAS
6.3.3.1 Packaged generative AI SaaS unlocks business value across functions
6.3.3.2 Code generators
6.3.3.3 Generative design & prototyping tools
6.3.3.4 Synthetic data generators
6.3.3.5 Generative AI agents
6.3.3.6 Domain-specific Gen AI tools
6.4 SERVICES
6.4.1 GEN AI TRAINING & CONSULTING SERVICES
6.4.1.1 Empowering enterprises with strategic generative AI advisory and training programs
6.4.2 MODEL DEVELOPMENT & FINE-TUNING SERVICES
6.4.2.1 Delivering customized generative AI models through development and fine-tuning expertise
6.4.3 PROMPT ENGINEERING SERVICES
6.4.3.1 Optimizing generative AI outcomes with advanced prompt engineering techniques
6.4.4 INTEGRATION & DEPLOYMENT SERVICES
6.4.4.1 Accelerating enterprise transformation through seamless generative AI integration and deployment
6.4.5 SUPPORT & MAINTENANCE SERVICES
6.4.5.1 Ensuring reliability and compliance with ongoing generative AI support and maintenance
6.4.6 GEN AI TRAINING DATA SERVICES
6.4.6.1 Enabling high-performance generative AI with curated and domain-specific training data services
6.4.7 MANAGED GEN AI SERVICES
6.4.7.1 Simplifying AI operations with comprehensive managed generative AI solutions
7 GENERATIVE AI MARKET, BY DATA MODALITY
7.1 INTRODUCTION
7.1.1 DATA MODALITY: GENERATIVE AI MARKET DRIVERS
7.2 TEXT
7.2.1 TEXT-BASED AI POWERS HUMAN-LIKE CONTENT CREATION
7.3 IMAGE
7.3.1 TRANSFORMING DESIGN AND MARKETING WITH GENERATIVE IMAGES
7.4 VIDEO
7.4.1 COMPLEX VIDEO GENERATION THROUGH AI
7.5 AUDIO & SPEECH
7.5.1 ENHANCING HUMAN-MACHINE DIALOGUE THROUGH SPEECH AI
7.6 CODE
7.6.1 ACCELERATING SOFTWARE DEVELOPMENT THROUGH EXECUTABLE OUTPUT GENERATION
7.7 MULTIMODAL
7.7.1 MERGING TEXT, IMAGE, AND AUDIO FOR RICHER AI EXPERIENCES
8 GENERATIVE AI MARKET, BY APPLICATION
8.1 INTRODUCTION
8.1.1 APPLICATION: GENERATIVE AI MARKET DRIVERS
8.2 BUSINESS INTELLIGENCE & VISUALIZATION
8.2.1 ENABLING SMARTER INSIGHTS ACROSS BUSINESS FUNCTIONS
8.2.2 SALES INTELLIGENCE
8.2.3 MARKETING INTELLIGENCE
8.2.4 HUMAN RESOURCE INTELLIGENCE
8.2.5 FINANCE INTELLIGENCE
8.2.6 OPERATIONS & SUPPLY CHAIN INTELLIGENCE
8.3 CONTENT MANAGEMENT
8.3.1 ACCELERATING DIGITAL CONTENT WORKFLOWS THROUGH AI
8.3.2 CONTENT GENERATION
8.3.3 CONTENT CURATION, TAGGING, & CATEGORIZATION
8.3.4 DIGITAL MARKETING
8.3.5 MEDIA EDITING
8.4 SYNTHETIC DATA MANAGEMENT
8.4.1 AI-GENERATED DATA FOR FASTER, FAIRER MODEL TRAINING
8.4.2 SYNTHETIC DATA AUGMENTATION
8.4.3 SYNTHETIC DATA TRAINING
8.5 SEARCH & DISCOVERY
8.5.1 INTELLIGENT INFORMATION ACCESS THROUGH GENERATIVE MODELS
8.5.2 GENERAL SEARCH
8.5.3 INSIGHT GENERATION
8.6 AUTOMATION & INTEGRATION
8.6.1 CONNECTING SYSTEMS AND AUTOMATING WORKFLOWS USING
GENERATIVE AI
8.6.2 PERSONALIZATION & RECOMMENDATION SYSTEMS
8.6.3 CUSTOMER EXPERIENCE MANAGEMENT
8.6.4 APPLICATION DEVELOPMENT & API INTEGRATION
8.6.5 CYBERSECURITY INTELLIGENCE
8.7 GENERATIVE DESIGN AI
8.7.1 ACCELERATING AND EXPANDING CREATIVE POSSIBILITIES WITH GENERATIVE DESIGN AI
8.7.2 DESIGN EXPLORATION & VARIATION
8.7.3 MODELING & PROTOTYPING
8.7.4 PRODUCT RENDERING & VISUAL COLLATERALS
8.8 OTHER APPLICATIONS
9 GENERATIVE AI MARKET, BY END USER
9.1 INTRODUCTION
9.1.1 END USER: GENERATIVE AI MARKET DRIVERS
9.2 CONSUMERS
9.3 ENTERPRISES
9.3.1 BFSI
9.3.1.1 Intelligent automation transforms BFSI workflows from KYC to regulatory compliance
9.3.1.2 Personalized finance advisors
9.3.1.3 Automated report & commentary generation
9.3.1.4 Intelligent underwriting & claims
9.3.1.5 Fraud detection & prevention
9.3.1.6 Regulatory reporting & compliance
9.3.1.7 Other BFSI use cases
9.3.2 RETAIL & E-COMMERCE
9.3.2.1 AI transforms e-commerce through virtual assistants, SEO content, and demand forecasting
9.3.2.2 Product description & SEO content generation
9.3.2.3 Virtual shopping assistants
9.3.2.4 Personalized product recommendations
9.3.2.5 Customer query resolution
9.3.2.6 Demand forecasting & inventory management
9.3.2.7 Other retail & e-commerce use cases
9.3.3 GOVERNMENT & DEFENSE
9.3.3.1 AI enhances defense readiness and service delivery through scenario simulations and legislative summaries
9.3.3.2 Policy drafting & legislative summarization
9.3.3.3 Citizen services chatbots
9.3.3.4 OSINT briefing & reporting
9.3.3.5 Document classification & knowledge retrieval
9.3.3.6 Threat scenario simulation
9.3.3.7 Other government & defense use cases
9.3.4 TELECOMMUNICATIONS
9.3.4.1 Enhancing telecom efficiency with AI-powered contact centers,
field services, and fraud detection
9.3.4.2 Network operations & fault diagnosis
9.3.4.3 Automated SLA reporting
9.3.4.4 Contact center intelligence
9.3.4.5 Marketing content & campaign personalization
9.3.4.6 Revenue assurance & fraud prevention
9.3.4.7 Other telecommunications use cases
9.3.5 MEDIA & ENTERTAINMENT
9.3.5.1 Generative AI redefines content creation across film, gaming,
and marketing
9.3.5.2 Scriptwriting & narrative generation
9.3.5.3 AI voiceover & dubbing
9.3.5.4 Visual assets generation & motion design
9.3.5.5 Multilingual content localization
9.3.5.6 Advertising & campaign copywriting
9.3.5.7 Synthetic influencers, hosts, & digital avatars
9.3.5.8 Digital rights & IP protection
9.3.5.9 Other media & entertainment use cases
9.3.6 TRANSPORTATION & LOGISTICS
9.3.6.1 Generative AI empowers logistics firms with predictive routing,
smart documentation, and efficient warehouse planning
9.3.6.2 Route optimization
9.3.6.3 Freight documentation
9.3.6.4 Fleet management
9.3.6.5 Warehouse management
9.3.6.6 Traffic scenario simulation
9.3.6.7 Other transportation & logistics use cases
9.3.7 MANUFACTURING
9.3.7.1 Generative AI transforms product lifecycle from planning and design to maintenance and technical content
9.3.7.2 Design generation
9.3.7.3 Predictive maintenance
9.3.7.4 Quality inspection & control
9.3.7.5 Procurement & supplier management
9.3.7.6 Product planning & simulation
9.3.7.7 Other manufacturing use cases
9.3.8 HEALTHCARE & LIFE SCIENCES
9.3.8.1 Improving patient outcomes and medical research with Gen AI tools and applications
9.3.8.2 Electronic health record (EHR) automation
9.3.8.3 Medical imaging
9.3.8.4 Virtual health assistants
9.3.8.5 Drug discovery & molecule design
9.3.8.6 Clinical trial protocol design
9.3.8.7 Personalized treatment plans
9.3.8.8 Other healthcare & life sciences use cases
9.3.9 SOFTWARE & TECHNOLOGY PROVIDERS
9.3.9.1 Automating knowledge discovery and workflows with Gen AI in software & technology firms
9.3.9.2 Code generation & debugging
9.3.9.3 Test case generation & QA automation
9.3.9.4 Gen AI-assisted ITSM
9.3.9.5 Customer support automation
9.3.9.6 Knowledge discovery
9.3.9.7 Business process automation
9.3.9.8 Other software & technology provider use cases
9.3.10 ENERGY & UTILITIES
9.3.10.1 Enhancing grid operations, asset maintenance, and forecasting using generative AI
9.3.10.2 Condition-based asset maintenance
9.3.10.3 Grid operations management
9.3.10.4 Renewable energy forecasting
9.3.10.5 Sustainability & emissions reporting
9.3.10.6 Digital twin simulations
9.3.10.7 Other energy & utilities use cases
9.3.11 OTHER ENTERPRISES
10 GENERATIVE AI MARKET, BY REGION
10.1 INTRODUCTION
10.2 NORTH AMERICA
10.2.1 NORTH AMERICA: GENERATIVE AI MARKET DRIVERS
10.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
10.2.3 US
10.2.3.1 Advancements in foundational models and cloud infrastructure to drive market
10.2.4 CANADA
10.2.4.1 Focus on talent development, ethical AI policies, and ecosystem collaboration to drive market
10.3 EUROPE
10.3.1 EUROPE: GENERATIVE AI MARKET DRIVERS
10.3.2 EUROPE: MACROECONOMIC OUTLOOK
10.3.3 UK
10.3.3.1 AI Safety Summit to drive demand for responsible AI development
10.3.4 GERMANY
10.3.4.1 Strong public-private partnerships and collaborations between companies, startups, and universities to drive market
10.3.5 FRANCE
10.3.5.1 Promotion of flexible AI innovation through regulatory sandboxes and startup-friendly laws to drive market
10.3.6 ITALY
10.3.6.1 Advancements in generative AI research to drive market
10.3.7 SPAIN
10.3.7.1 Integration of generative AI with government-backed pilot programs to drive market
10.3.8 FINLAND
10.3.8.1 Support for homegrown businesses through Business Finland grants to drive market
10.3.9 REST OF EUROPE
10.4 ASIA PACIFIC
10.4.1 ASIA PACIFIC: GENERATIVE AI MARKET DRIVERS
10.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
10.4.3 CHINA
10.4.3.1 Structured frameworks for safe AI development and deployment to drive market
10.4.4 INDIA
10.4.4.1 Strong startup ecosystem to accelerate commercialization of AI research and innovation
10.4.5 JAPAN
10.4.5.1 Government initiatives like Moonshot R&D and Society 5.0 to drive market
10.4.6 SOUTH KOREA
10.4.6.1 Establishment of AI regulatory sandboxes and ethics guidelines for responsible experimentation to drive market
10.4.7 SINGAPORE
10.4.7.1 National AI Strategy 2.0 outlining AI integration across healthcare, finance, and urban planning to drive market
10.4.8 AUSTRALIA & NEW ZEALAND
10.4.8.1 Support for AI startup ecosystems through accelerators and R&D tax incentives to drive market
10.4.9 REST OF ASIA PACIFIC
10.5 MIDDLE EAST & AFRICA
10.5.1 MIDDLE EAST & AFRICA: GENERATIVE AI MARKET DRIVERS
10.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
10.5.3 SAUDI ARABIA
10.5.3.1 Startup support programs and partnerships with global AI firms to drive market
10.5.4 UAE
10.5.4.1 Funding and mentorship to AI startups to drive market
10.5.5 SOUTH AFRICA
10.5.5.1 Application of generative AI in platforms tailored to diverse linguistic and cultural needs to drive market
10.5.6 ISRAEL
10.5.6.1 Strong research institutions, mature tech ecosystem, and government support to drive market
10.5.7 REST OF MIDDLE EAST & AFRICA
10.6 LATIN AMERICA
10.6.1 LATIN AMERICA: GENERATIVE AI MARKET DRIVERS
10.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
10.6.3 BRAZIL
10.6.3.1 Support from Brazilian Development Bank (BNDES) for AI Startups through funding programs to drive market
10.6.4 MEXICO
10.6.4.1 Development of generative AI tools tailored to Spanish language and Mexican cultural context to drive market
10.6.5 ARGENTINA
10.6.5.1 Support for AI-driven startups through co-working spaces, grants, and mentorship to drive market
10.6.6 REST OF LATIN AMERICA
11 COMPETITIVE LANDSCAPE
11.1 OVERVIEW
11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2020–2024
11.3 REVENUE ANALYSIS, 2020–2024
11.4 MARKET SHARE ANALYSIS, 2024
11.4.1 MARKET RANKING ANALYSIS, 2024
11.5 PRODUCT COMPARISON
11.5.1 PRODUCT COMPARATIVE ANALYSIS, BY TEXT GENERATOR
11.5.1.1 OpenAI (GPT-4)
11.5.1.2 Google (Gemini)
11.5.1.3 Anthropic (Claude)
11.5.1.4 Perplexity (Perplexity AI)
11.5.1.5 DeepSeek (DeepSeek)
11.5.1.6 xAI (Grok)
11.5.2 PRODUCT COMPARATIVE ANALYSIS, BY IMAGE GENERATOR
11.5.2.1 OpenAI (DALL-E)
11.5.2.2 Midjourney (MidJourney V6)
11.5.2.3 Stability AI (Stable Diffusion)
11.5.2.4 Adobe (Adobe Firefly)
11.5.2.5 Runway (Runway Gen-2)
11.5.2.6 Google (Imagen)
11.5.3 PRODUCT COMPARATIVE ANALYSIS, BY VIDEO GENERATOR
11.5.3.1 OpenAI (Sora)
11.5.3.2 Runway (Runway Gen-2)
11.5.3.3 Synthesia (Synthesia Studio)
11.5.3.4 Lumen5 (Lumen5 Video Maker)
11.5.3.5 Colossyan (Colossyan Creator)
11.5.3.6 Pika Labs (Pika)
11.5.4 PRODUCT COMPARATIVE ANALYSIS, BY AUDIO & SPEECH GENERATOR
11.5.4.1 ElevenLabs (Eleven Multilingual Voice AI)
11.5.4.2 OpenAI (Voice Engine)
11.5.4.3 Play.ht (PlayAI Platform)
11.5.4.4 AWS (Amazon Polly)
11.5.4.5 Meta (Voicebox)
11.5.4.6 Soundful (AI Music Generator)
11.6 COMPANY VALUATION AND FINANCIAL METRICS
11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
11.7.1 STARS
11.7.2 EMERGING LEADERS
11.7.3 PERVASIVE PLAYERS
11.7.4 PARTICIPANTS
11.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
11.7.5.1 Company footprint
11.7.5.2 Region footprint
11.7.5.3 Offering footprint
11.7.5.4 Data modality footprint
11.7.5.5 End user footprint
11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
11.8.1 PROGRESSIVE COMPANIES
11.8.2 RESPONSIVE COMPANIES
11.8.3 DYNAMIC COMPANIES
11.8.4 STARTING BLOCKS
11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
11.8.5.1 Detailed list of key startups/SMEs
11.8.5.2 Competitive benchmarking of key startups/SMEs
11.9 COMPETITIVE SCENARIO
11.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS
11.9.2 DEALS
12 COMPANY PROFILES
12.1 INTRODUCTION
12.2 KEY PLAYERS
12.2.1 MICROSOFT
12.2.1.1 Business overview
12.2.1.2 Products offered
12.2.1.3 Recent developments
12.2.1.3.1 Product launches and enhancements
12.2.1.3.2 Deals
12.2.1.4 MnM view
12.2.1.4.1 Key strengths
12.2.1.4.2 Strategic choices
12.2.1.4.3 Weaknesses and competitive threats
12.2.2 AWS
12.2.2.1 Business overview
12.2.2.2 Products offered
12.2.2.3 Recent developments
12.2.2.3.1 Product launches and enhancements
12.2.2.3.2 Deals
12.2.2.4 MnM view
12.2.2.4.1 Key strengths
12.2.2.4.2 Strategic choices
12.2.2.4.3 Weaknesses and competitive threats
12.2.3 GOOGLE
12.2.3.1 Business overview
12.2.3.2 Products offered
12.2.3.3 Recent developments
12.2.3.3.1 Product launches and enhancements
12.2.3.3.2 Deals
12.2.3.4 MnM view
12.2.3.4.1 Key strengths
12.2.3.4.2 Strategic choices
12.2.3.4.3 Weaknesses and competitive threats
12.2.4 ADOBE
12.2.4.1 Business overview
12.2.4.2 Products offered
12.2.4.3 Recent developments
12.2.4.3.1 Product launches and enhancements
12.2.4.3.2 Deals
12.2.4.4 MnM view
12.2.4.4.1 Key strengths
12.2.4.4.2 Strategic choices
12.2.4.4.3 Weaknesses and competitive threats
12.2.5 OPENAI
12.2.5.1 Business overview
12.2.5.2 Products offered
12.2.5.3 Recent developments
12.2.5.3.1 Product launches and enhancements
12.2.5.3.2 Deals
12.2.5.4 MnM view
12.2.5.4.1 Key strengths
12.2.5.4.2 Strategic choices made
12.2.5.4.3 Weaknesses and competitive threats
12.2.6 IBM
12.2.6.1 Business overview
12.2.6.2 Products offered
12.2.6.3 Recent developments
12.2.6.3.1 Product launches and enhancements
12.2.6.3.2 Deals
12.2.7 META
12.2.7.1 Business overview
12.2.7.2 Products offered
12.2.7.3 Recent developments
12.2.7.3.1 Product launches and enhancements
12.2.7.3.2 Deals
12.2.8 ANTHROPIC
12.2.8.1 Business overview
12.2.8.2 Products offered
12.2.8.3 Recent developments
12.2.8.3.1 Product launches and enhancements
12.2.8.3.2 Deals
12.2.9 NVIDIA
12.2.9.1 Business overview
12.2.9.2 Products offered
12.2.9.3 Recent developments
12.2.9.3.1 Product launches and enhancements
12.2.9.3.2 Deals
12.2.10 ACCENTURE
12.2.10.1 Business overview
12.2.10.2 Products offered
12.2.10.3 Recent developments
12.2.10.3.1 Deals
12.2.11 CAPGEMINI
12.2.11.1 Business overview
12.2.11.2 Products offered
12.2.11.3 Recent developments
12.2.11.3.1 Product launches and enhancements
12.2.11.3.2 Deals
12.2.12 HPE
12.2.12.1 Business overview
12.2.12.2 Products offered
12.2.12.3 Recent developments
12.2.12.3.1 Product launches and enhancements
12.2.12.3.2 Deals
12.2.13 AMD
12.2.13.1 Business overview
12.2.13.2 Products offered
12.2.13.3 Recent developments
12.2.13.3.1 Product launches and enhancements
12.2.13.3.2 Deals
12.2.14 ORACLE
12.2.14.1 Business overview
12.2.14.2 Products offered
12.2.14.3 Recent developments
12.2.14.3.1 Product launches and enhancements
12.2.14.3.2 Deals
12.2.15 SALESFORCE
12.2.15.1 Business overview
12.2.15.2 Products offered
12.2.15.3 Recent developments
12.2.15.3.1 Product launches and enhancements
12.2.15.3.2 Deals
12.2.16 TELUS INTERNATIONAL
12.2.16.1 Business overview
12.2.16.2 Products offered
12.2.17 INNODATA
12.2.17.1 Business overview
12.2.17.2 Products offered
12.2.17.3 Recent developments
12.2.17.3.1 Product launches and enhancements
12.2.18 IMERIT
12.2.19 DIALPAD
12.2.20 CENTIFIC
12.2.20.1 Business overview
12.2.20.2 Products offered
12.2.20.3 Recent developments
12.2.20.3.1 Deals
12.2.21 FRACTAL ANALYTICS
12.2.22 TIGER ANALYTICS
12.2.23 QUANTIPHI
12.2.24 APPEN
12.2.25 DATABRICKS
12.3 STARTUPS/SMES
12.3.1 CURSOR
12.3.2 DEEPSEEK
12.3.3 XAI
12.3.4 ABRIDGE
12.3.5 PERPLEXITY AI
12.3.6 SAMBANOVA
12.3.7 INSILICO MEDICINE
12.3.8 SIMPLIFIED
12.3.9 AI21 LABS
12.3.10 HUGGING FACE
12.3.11 PERSADO
12.3.12 SCALE AI
12.3.13 SNORKEL
12.3.14 LABELBOX
12.3.15 HQE SYSTEMS
12.3.15.1 Business overview
12.3.15.2 Products offered
12.3.16 LIGHTRICKS
12.3.17 SPEECHIFY
12.3.18 MIDJOURNEY
12.3.19 FIREFLIES
12.3.20 SYNTHESIA
12.3.21 MOSTLY AI
12.3.22 CHARACTER.AI
12.3.23 HYPOTENUSE AI
12.3.24 WRITESONIC
12.3.25 COPY.AI
12.3.26 SYNTHESIS AI
12.3.27 COLOSSYAN
12.3.28 INFLECTION AI
12.3.29 JASPER
12.3.30 RUNWAY
12.3.31 INWORLD AI
12.3.32 TYPEFACE
12.3.33 INSTADEEP
12.3.34 FORETHOUGHT
12.3.35 TOGETHER AI
12.3.36 UPSTAGE
12.3.37 MISTRAL AI
12.3.38 ADEPT
12.3.39 STABILITY AI
12.3.40 COHERE
12.4 OPEN-SOURCE COMPANIES
12.4.1 APPLE
12.4.2 LG
12.4.3 NOUS RESEARCH
12.4.4 FONTJOY
12.4.5 ELEUTHERAI
12.4.6 TECHNOLOGY INNOVATION INSTITUTE
12.4.7 STARRYAI
12.4.8 MAGIC STUDIO
12.4.9 ABACUS.AI
12.4.10 OPENLM
13 ADJACENT AND RELATED MARKETS
13.1 INTRODUCTION
13.2 LARGE LANGUAGE MODEL MARKET – GLOBAL FORECAST TO 2030
13.2.1 MARKET DEFINITION
13.2.2 MARKET OVERVIEW
13.2.2.1 Large language model market, by offering
13.2.2.2 Large language model market, by architecture
13.2.2.3 Large language model market, by modality
13.2.2.4 Large language model market, by model size
13.2.2.5 Large language model market, by application
13.2.2.6 Large language model market, by end user
13.2.2.7 Large language model market, by region
13.3 ARTIFICIAL INTELLIGENCE MARKET – GLOBAL FORECAST TO 2032
13.3.1 MARKET DEFINITION
13.3.2 MARKET OVERVIEW
13.3.2.1 Artificial intelligence (AI) market, by offering
13.3.2.2 Artificial intelligence (AI) market, by technology
13.3.2.3 Artificial intelligence (AI) market, by business function
13.3.2.4 Artificial intelligence (AI) market, by enterprise application
13.3.2.5 Artificial intelligence (AI) market, by end user
13.3.2.6 Artificial intelligence (AI) market, by region
14 APPENDIX
14.1 DISCUSSION GUIDE
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
14.3 CUSTOMIZATION OPTIONS
14.4 RELATED REPORTS
14.5 AUTHOR DETAILS
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)
5.11.3.5 Latin America
5.11.3.5.1 Santiago Declaration (Chile)
5.11.3.5.2 Brazilian Artificial Intelligence Strategy (EBIA)
5.12 TRADE ANALYSIS
5.12.1 EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
5.12.2 IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
5.13 PATENT ANALYSIS
5.13.1 METHODOLOGY
5.13.2 PATENTS FILED, BY DOCUMENT TYPE
5.13.3 INNOVATION AND PATENT APPLICATIONS
5.14 PRICING ANALYSIS
5.14.1 AVERAGE SELLING PRICE OF OFFERING, BY KEY PLAYER, 2025
5.14.2 AVERAGE SELLING PRICE, BY APPLICATION, 2025
5.15 KEY CONFERENCES AND EVENTS
5.16 PORTER’S FIVE FORCES ANALYSIS
5.16.1 THREAT OF NEW ENTRANTS
5.16.2 THREAT OF SUBSTITUTES
5.16.3 BARGAINING POWER OF SUPPLIERS
5.16.4 BARGAINING POWER OF BUYERS
5.16.5 INTENSITY OF COMPETITION RIVALRY
5.17 KEY STAKEHOLDERS AND BUYING CRITERIA
5.17.1 KEY STAKEHOLDERS IN BUYING PROCESS
5.17.2 BUYING CRITERIA
5.18 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
6 GENERATIVE AI MARKET, BY OFFERING
6.1 INTRODUCTION
6.1.1 OFFERING: GENERATIVE AI MARKET DRIVERS
6.2 INFRASTRUCTURE
6.2.1 COMPUTE
6.2.1.1 Compute power drives model training and inference
6.2.1.2 Graphics processing units (GPUs)
6.2.1.3 Central processing units (CPUs)
6.2.1.4 Field-programmable gate arrays (FPGAs)
6.2.2 MEMORY
6.2.2.1 High-performance memory to sustain AI workload demands
6.2.2.2 Double data rate (DDR)
6.2.2.3 High bandwidth memory (HBM)
6.2.3 NETWORKING HARDWARE
6.2.3.1 Fast, scalable connectivity to support distributed AI systems
6.2.3.2 NIC/Network adapters
6.2.3.2.1 Ethernet
6.2.3.2.2 InfiniBand
6.2.3.3 Interconnects
6.2.4 STORAGE
6.2.4.1 Storage systems built for speed, scale, and AI readiness
6.3 SOFTWARE
6.3.1 FOUNDATION MODELS
6.3.1.1 Foundation models power diverse, scalable generative AI applications
6.3.2 MODEL ENABLEMENT & ORCHESTRATION TOOLS
6.3.2.1 Tooling ecosystem critical to operationalizing generative AI at scale
6.3.2.2 Model hosting & access platforms
6.3.2.3 LLMOps & prompt engineering tools
6.3.2.4 Model fine-tuning tools
6.3.2.5 Model monitoring & evaluation tools
6.3.2.6 Governance & risk platforms
6.3.3 GEN AI SAAS
6.3.3.1 Packaged generative AI SaaS unlocks business value across functions
6.3.3.2 Code generators
6.3.3.3 Generative design & prototyping tools
6.3.3.4 Synthetic data generators
6.3.3.5 Generative AI agents
6.3.3.6 Domain-specific Gen AI tools
6.4 SERVICES
6.4.1 GEN AI TRAINING & CONSULTING SERVICES
6.4.1.1 Empowering enterprises with strategic generative AI advisory and training programs
6.4.2 MODEL DEVELOPMENT & FINE-TUNING SERVICES
6.4.2.1 Delivering customized generative AI models through development and fine-tuning expertise
6.4.3 PROMPT ENGINEERING SERVICES
6.4.3.1 Optimizing generative AI outcomes with advanced prompt engineering techniques
6.4.4 INTEGRATION & DEPLOYMENT SERVICES
6.4.4.1 Accelerating enterprise transformation through seamless generative AI integration and deployment
6.4.5 SUPPORT & MAINTENANCE SERVICES
6.4.5.1 Ensuring reliability and compliance with ongoing generative AI support and maintenance
6.4.6 GEN AI TRAINING DATA SERVICES
6.4.6.1 Enabling high-performance generative AI with curated and domain-specific training data services
6.4.7 MANAGED GEN AI SERVICES
6.4.7.1 Simplifying AI operations with comprehensive managed generative AI solutions
7 GENERATIVE AI MARKET, BY DATA MODALITY
7.1 INTRODUCTION
7.1.1 DATA MODALITY: GENERATIVE AI MARKET DRIVERS
7.2 TEXT
7.2.1 TEXT-BASED AI POWERS HUMAN-LIKE CONTENT CREATION
7.3 IMAGE
7.3.1 TRANSFORMING DESIGN AND MARKETING WITH GENERATIVE IMAGES
7.4 VIDEO
7.4.1 COMPLEX VIDEO GENERATION THROUGH AI
7.5 AUDIO & SPEECH
7.5.1 ENHANCING HUMAN-MACHINE DIALOGUE THROUGH SPEECH AI
7.6 CODE
7.6.1 ACCELERATING SOFTWARE DEVELOPMENT THROUGH EXECUTABLE OUTPUT GENERATION
7.7 MULTIMODAL
7.7.1 MERGING TEXT, IMAGE, AND AUDIO FOR RICHER AI EXPERIENCES
8 GENERATIVE AI MARKET, BY APPLICATION
8.1 INTRODUCTION
8.1.1 APPLICATION: GENERATIVE AI MARKET DRIVERS
8.2 BUSINESS INTELLIGENCE & VISUALIZATION
8.2.1 ENABLING SMARTER INSIGHTS ACROSS BUSINESS FUNCTIONS
8.2.2 SALES INTELLIGENCE
8.2.3 MARKETING INTELLIGENCE
8.2.4 HUMAN RESOURCE INTELLIGENCE
8.2.5 FINANCE INTELLIGENCE
8.2.6 OPERATIONS & SUPPLY CHAIN INTELLIGENCE
8.3 CONTENT MANAGEMENT
8.3.1 ACCELERATING DIGITAL CONTENT WORKFLOWS THROUGH AI
8.3.2 CONTENT GENERATION
8.3.3 CONTENT CURATION, TAGGING, & CATEGORIZATION
8.3.4 DIGITAL MARKETING
8.3.5 MEDIA EDITING
8.4 SYNTHETIC DATA MANAGEMENT
8.4.1 AI-GENERATED DATA FOR FASTER, FAIRER MODEL TRAINING
8.4.2 SYNTHETIC DATA AUGMENTATION
8.4.3 SYNTHETIC DATA TRAINING
8.5 SEARCH & DISCOVERY
8.5.1 INTELLIGENT INFORMATION ACCESS THROUGH GENERATIVE MODELS
8.5.2 GENERAL SEARCH
8.5.3 INSIGHT GENERATION
8.6 AUTOMATION & INTEGRATION
8.6.1 CONNECTING SYSTEMS AND AUTOMATING WORKFLOWS USING
GENERATIVE AI
8.6.2 PERSONALIZATION & RECOMMENDATION SYSTEMS
8.6.3 CUSTOMER EXPERIENCE MANAGEMENT
8.6.4 APPLICATION DEVELOPMENT & API INTEGRATION
8.6.5 CYBERSECURITY INTELLIGENCE
8.7 GENERATIVE DESIGN AI
8.7.1 ACCELERATING AND EXPANDING CREATIVE POSSIBILITIES WITH GENERATIVE DESIGN AI
8.7.2 DESIGN EXPLORATION & VARIATION
8.7.3 MODELING & PROTOTYPING
8.7.4 PRODUCT RENDERING & VISUAL COLLATERALS
8.8 OTHER APPLICATIONS
9 GENERATIVE AI MARKET, BY END USER
9.1 INTRODUCTION
9.1.1 END USER: GENERATIVE AI MARKET DRIVERS
9.2 CONSUMERS
9.3 ENTERPRISES
9.3.1 BFSI
9.3.1.1 Intelligent automation transforms BFSI workflows from KYC to regulatory compliance
9.3.1.2 Personalized finance advisors
9.3.1.3 Automated report & commentary generation
9.3.1.4 Intelligent underwriting & claims
9.3.1.5 Fraud detection & prevention
9.3.1.6 Regulatory reporting & compliance
9.3.1.7 Other BFSI use cases
9.3.2 RETAIL & E-COMMERCE
9.3.2.1 AI transforms e-commerce through virtual assistants, SEO content, and demand forecasting
9.3.2.2 Product description & SEO content generation
9.3.2.3 Virtual shopping assistants
9.3.2.4 Personalized product recommendations
9.3.2.5 Customer query resolution
9.3.2.6 Demand forecasting & inventory management
9.3.2.7 Other retail & e-commerce use cases
9.3.3 GOVERNMENT & DEFENSE
9.3.3.1 AI enhances defense readiness and service delivery through scenario simulations and legislative summaries
9.3.3.2 Policy drafting & legislative summarization
9.3.3.3 Citizen services chatbots
9.3.3.4 OSINT briefing & reporting
9.3.3.5 Document classification & knowledge retrieval
9.3.3.6 Threat scenario simulation
9.3.3.7 Other government & defense use cases
9.3.4 TELECOMMUNICATIONS
9.3.4.1 Enhancing telecom efficiency with AI-powered contact centers,
field services, and fraud detection
9.3.4.2 Network operations & fault diagnosis
9.3.4.3 Automated SLA reporting
9.3.4.4 Contact center intelligence
9.3.4.5 Marketing content & campaign personalization
9.3.4.6 Revenue assurance & fraud prevention
9.3.4.7 Other telecommunications use cases
9.3.5 MEDIA & ENTERTAINMENT
9.3.5.1 Generative AI redefines content creation across film, gaming,
and marketing
9.3.5.2 Scriptwriting & narrative generation
9.3.5.3 AI voiceover & dubbing
9.3.5.4 Visual assets generation & motion design
9.3.5.5 Multilingual content localization
9.3.5.6 Advertising & campaign copywriting
9.3.5.7 Synthetic influencers, hosts, & digital avatars
9.3.5.8 Digital rights & IP protection
9.3.5.9 Other media & entertainment use cases
9.3.6 TRANSPORTATION & LOGISTICS
9.3.6.1 Generative AI empowers logistics firms with predictive routing,
smart documentation, and efficient warehouse planning
9.3.6.2 Route optimization
9.3.6.3 Freight documentation
9.3.6.4 Fleet management
9.3.6.5 Warehouse management
9.3.6.6 Traffic scenario simulation
9.3.6.7 Other transportation & logistics use cases
9.3.7 MANUFACTURING
9.3.7.1 Generative AI transforms product lifecycle from planning and design to maintenance and technical content
9.3.7.2 Design generation
9.3.7.3 Predictive maintenance
9.3.7.4 Quality inspection & control
9.3.7.5 Procurement & supplier management
9.3.7.6 Product planning & simulation
9.3.7.7 Other manufacturing use cases
9.3.8 HEALTHCARE & LIFE SCIENCES
9.3.8.1 Improving patient outcomes and medical research with Gen AI tools and applications
9.3.8.2 Electronic health record (EHR) automation
9.3.8.3 Medical imaging
9.3.8.4 Virtual health assistants
9.3.8.5 Drug discovery & molecule design
9.3.8.6 Clinical trial protocol design
9.3.8.7 Personalized treatment plans
9.3.8.8 Other healthcare & life sciences use cases
9.3.9 SOFTWARE & TECHNOLOGY PROVIDERS
9.3.9.1 Automating knowledge discovery and workflows with Gen AI in software & technology firms
9.3.9.2 Code generation & debugging
9.3.9.3 Test case generation & QA automation
9.3.9.4 Gen AI-assisted ITSM
9.3.9.5 Customer support automation
9.3.9.6 Knowledge discovery
9.3.9.7 Business process automation
9.3.9.8 Other software & technology provider use cases
9.3.10 ENERGY & UTILITIES
9.3.10.1 Enhancing grid operations, asset maintenance, and forecasting using generative AI
9.3.10.2 Condition-based asset maintenance
9.3.10.3 Grid operations management
9.3.10.4 Renewable energy forecasting
9.3.10.5 Sustainability & emissions reporting
9.3.10.6 Digital twin simulations
9.3.10.7 Other energy & utilities use cases
9.3.11 OTHER ENTERPRISES
10 GENERATIVE AI MARKET, BY REGION
10.1 INTRODUCTION
10.2 NORTH AMERICA
10.2.1 NORTH AMERICA: GENERATIVE AI MARKET DRIVERS
10.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
10.2.3 US
10.2.3.1 Advancements in foundational models and cloud infrastructure to drive market
10.2.4 CANADA
10.2.4.1 Focus on talent development, ethical AI policies, and ecosystem collaboration to drive market
10.3 EUROPE
10.3.1 EUROPE: GENERATIVE AI MARKET DRIVERS
10.3.2 EUROPE: MACROECONOMIC OUTLOOK
10.3.3 UK
10.3.3.1 AI Safety Summit to drive demand for responsible AI development
10.3.4 GERMANY
10.3.4.1 Strong public-private partnerships and collaborations between companies, startups, and universities to drive market
10.3.5 FRANCE
10.3.5.1 Promotion of flexible AI innovation through regulatory sandboxes and startup-friendly laws to drive market
10.3.6 ITALY
10.3.6.1 Advancements in generative AI research to drive market
10.3.7 SPAIN
10.3.7.1 Integration of generative AI with government-backed pilot programs to drive market
10.3.8 FINLAND
10.3.8.1 Support for homegrown businesses through Business Finland grants to drive market
10.3.9 REST OF EUROPE
10.4 ASIA PACIFIC
10.4.1 ASIA PACIFIC: GENERATIVE AI MARKET DRIVERS
10.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
10.4.3 CHINA
10.4.3.1 Structured frameworks for safe AI development and deployment to drive market
10.4.4 INDIA
10.4.4.1 Strong startup ecosystem to accelerate commercialization of AI research and innovation
10.4.5 JAPAN
10.4.5.1 Government initiatives like Moonshot R&D and Society 5.0 to drive market
10.4.6 SOUTH KOREA
10.4.6.1 Establishment of AI regulatory sandboxes and ethics guidelines for responsible experimentation to drive market
10.4.7 SINGAPORE
10.4.7.1 National AI Strategy 2.0 outlining AI integration across healthcare, finance, and urban planning to drive market
10.4.8 AUSTRALIA & NEW ZEALAND
10.4.8.1 Support for AI startup ecosystems through accelerators and R&D tax incentives to drive market
10.4.9 REST OF ASIA PACIFIC
10.5 MIDDLE EAST & AFRICA
10.5.1 MIDDLE EAST & AFRICA: GENERATIVE AI MARKET DRIVERS
10.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
10.5.3 SAUDI ARABIA
10.5.3.1 Startup support programs and partnerships with global AI firms to drive market
10.5.4 UAE
10.5.4.1 Funding and mentorship to AI startups to drive market
10.5.5 SOUTH AFRICA
10.5.5.1 Application of generative AI in platforms tailored to diverse linguistic and cultural needs to drive market
10.5.6 ISRAEL
10.5.6.1 Strong research institutions, mature tech ecosystem, and government support to drive market
10.5.7 REST OF MIDDLE EAST & AFRICA
10.6 LATIN AMERICA
10.6.1 LATIN AMERICA: GENERATIVE AI MARKET DRIVERS
10.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
10.6.3 BRAZIL
10.6.3.1 Support from Brazilian Development Bank (BNDES) for AI Startups through funding programs to drive market
10.6.4 MEXICO
10.6.4.1 Development of generative AI tools tailored to Spanish language and Mexican cultural context to drive market
10.6.5 ARGENTINA
10.6.5.1 Support for AI-driven startups through co-working spaces, grants, and mentorship to drive market
10.6.6 REST OF LATIN AMERICA
11 COMPETITIVE LANDSCAPE
11.1 OVERVIEW
11.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2020–2024
11.3 REVENUE ANALYSIS, 2020–2024
11.4 MARKET SHARE ANALYSIS, 2024
11.4.1 MARKET RANKING ANALYSIS, 2024
11.5 PRODUCT COMPARISON
11.5.1 PRODUCT COMPARATIVE ANALYSIS, BY TEXT GENERATOR
11.5.1.1 OpenAI (GPT-4)
11.5.1.2 Google (Gemini)
11.5.1.3 Anthropic (Claude)
11.5.1.4 Perplexity (Perplexity AI)
11.5.1.5 DeepSeek (DeepSeek)
11.5.1.6 xAI (Grok)
11.5.2 PRODUCT COMPARATIVE ANALYSIS, BY IMAGE GENERATOR
11.5.2.1 OpenAI (DALL-E)
11.5.2.2 Midjourney (MidJourney V6)
11.5.2.3 Stability AI (Stable Diffusion)
11.5.2.4 Adobe (Adobe Firefly)
11.5.2.5 Runway (Runway Gen-2)
11.5.2.6 Google (Imagen)
11.5.3 PRODUCT COMPARATIVE ANALYSIS, BY VIDEO GENERATOR
11.5.3.1 OpenAI (Sora)
11.5.3.2 Runway (Runway Gen-2)
11.5.3.3 Synthesia (Synthesia Studio)
11.5.3.4 Lumen5 (Lumen5 Video Maker)
11.5.3.5 Colossyan (Colossyan Creator)
11.5.3.6 Pika Labs (Pika)
11.5.4 PRODUCT COMPARATIVE ANALYSIS, BY AUDIO & SPEECH GENERATOR
11.5.4.1 ElevenLabs (Eleven Multilingual Voice AI)
11.5.4.2 OpenAI (Voice Engine)
11.5.4.3 Play.ht (PlayAI Platform)
11.5.4.4 AWS (Amazon Polly)
11.5.4.5 Meta (Voicebox)
11.5.4.6 Soundful (AI Music Generator)
11.6 COMPANY VALUATION AND FINANCIAL METRICS
11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
11.7.1 STARS
11.7.2 EMERGING LEADERS
11.7.3 PERVASIVE PLAYERS
11.7.4 PARTICIPANTS
11.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
11.7.5.1 Company footprint
11.7.5.2 Region footprint
11.7.5.3 Offering footprint
11.7.5.4 Data modality footprint
11.7.5.5 End user footprint
11.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
11.8.1 PROGRESSIVE COMPANIES
11.8.2 RESPONSIVE COMPANIES
11.8.3 DYNAMIC COMPANIES
11.8.4 STARTING BLOCKS
11.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
11.8.5.1 Detailed list of key startups/SMEs
11.8.5.2 Competitive benchmarking of key startups/SMEs
11.9 COMPETITIVE SCENARIO
11.9.1 PRODUCT LAUNCHES AND ENHANCEMENTS
11.9.2 DEALS
12 COMPANY PROFILES
12.1 INTRODUCTION
12.2 KEY PLAYERS
12.2.1 MICROSOFT
12.2.1.1 Business overview
12.2.1.2 Products offered
12.2.1.3 Recent developments
12.2.1.3.1 Product launches and enhancements
12.2.1.3.2 Deals
12.2.1.4 MnM view
12.2.1.4.1 Key strengths
12.2.1.4.2 Strategic choices
12.2.1.4.3 Weaknesses and competitive threats
12.2.2 AWS
12.2.2.1 Business overview
12.2.2.2 Products offered
12.2.2.3 Recent developments
12.2.2.3.1 Product launches and enhancements
12.2.2.3.2 Deals
12.2.2.4 MnM view
12.2.2.4.1 Key strengths
12.2.2.4.2 Strategic choices
12.2.2.4.3 Weaknesses and competitive threats
12.2.3 GOOGLE
12.2.3.1 Business overview
12.2.3.2 Products offered
12.2.3.3 Recent developments
12.2.3.3.1 Product launches and enhancements
12.2.3.3.2 Deals
12.2.3.4 MnM view
12.2.3.4.1 Key strengths
12.2.3.4.2 Strategic choices
12.2.3.4.3 Weaknesses and competitive threats
12.2.4 ADOBE
12.2.4.1 Business overview
12.2.4.2 Products offered
12.2.4.3 Recent developments
12.2.4.3.1 Product launches and enhancements
12.2.4.3.2 Deals
12.2.4.4 MnM view
12.2.4.4.1 Key strengths
12.2.4.4.2 Strategic choices
12.2.4.4.3 Weaknesses and competitive threats
12.2.5 OPENAI
12.2.5.1 Business overview
12.2.5.2 Products offered
12.2.5.3 Recent developments
12.2.5.3.1 Product launches and enhancements
12.2.5.3.2 Deals
12.2.5.4 MnM view
12.2.5.4.1 Key strengths
12.2.5.4.2 Strategic choices made
12.2.5.4.3 Weaknesses and competitive threats
12.2.6 IBM
12.2.6.1 Business overview
12.2.6.2 Products offered
12.2.6.3 Recent developments
12.2.6.3.1 Product launches and enhancements
12.2.6.3.2 Deals
12.2.7 META
12.2.7.1 Business overview
12.2.7.2 Products offered
12.2.7.3 Recent developments
12.2.7.3.1 Product launches and enhancements
12.2.7.3.2 Deals
12.2.8 ANTHROPIC
12.2.8.1 Business overview
12.2.8.2 Products offered
12.2.8.3 Recent developments
12.2.8.3.1 Product launches and enhancements
12.2.8.3.2 Deals
12.2.9 NVIDIA
12.2.9.1 Business overview
12.2.9.2 Products offered
12.2.9.3 Recent developments
12.2.9.3.1 Product launches and enhancements
12.2.9.3.2 Deals
12.2.10 ACCENTURE
12.2.10.1 Business overview
12.2.10.2 Products offered
12.2.10.3 Recent developments
12.2.10.3.1 Deals
12.2.11 CAPGEMINI
12.2.11.1 Business overview
12.2.11.2 Products offered
12.2.11.3 Recent developments
12.2.11.3.1 Product launches and enhancements
12.2.11.3.2 Deals
12.2.12 HPE
12.2.12.1 Business overview
12.2.12.2 Products offered
12.2.12.3 Recent developments
12.2.12.3.1 Product launches and enhancements
12.2.12.3.2 Deals
12.2.13 AMD
12.2.13.1 Business overview
12.2.13.2 Products offered
12.2.13.3 Recent developments
12.2.13.3.1 Product launches and enhancements
12.2.13.3.2 Deals
12.2.14 ORACLE
12.2.14.1 Business overview
12.2.14.2 Products offered
12.2.14.3 Recent developments
12.2.14.3.1 Product launches and enhancements
12.2.14.3.2 Deals
12.2.15 SALESFORCE
12.2.15.1 Business overview
12.2.15.2 Products offered
12.2.15.3 Recent developments
12.2.15.3.1 Product launches and enhancements
12.2.15.3.2 Deals
12.2.16 TELUS INTERNATIONAL
12.2.16.1 Business overview
12.2.16.2 Products offered
12.2.17 INNODATA
12.2.17.1 Business overview
12.2.17.2 Products offered
12.2.17.3 Recent developments
12.2.17.3.1 Product launches and enhancements
12.2.18 IMERIT
12.2.19 DIALPAD
12.2.20 CENTIFIC
12.2.20.1 Business overview
12.2.20.2 Products offered
12.2.20.3 Recent developments
12.2.20.3.1 Deals
12.2.21 FRACTAL ANALYTICS
12.2.22 TIGER ANALYTICS
12.2.23 QUANTIPHI
12.2.24 APPEN
12.2.25 DATABRICKS
12.3 STARTUPS/SMES
12.3.1 CURSOR
12.3.2 DEEPSEEK
12.3.3 XAI
12.3.4 ABRIDGE
12.3.5 PERPLEXITY AI
12.3.6 SAMBANOVA
12.3.7 INSILICO MEDICINE
12.3.8 SIMPLIFIED
12.3.9 AI21 LABS
12.3.10 HUGGING FACE
12.3.11 PERSADO
12.3.12 SCALE AI
12.3.13 SNORKEL
12.3.14 LABELBOX
12.3.15 HQE SYSTEMS
12.3.15.1 Business overview
12.3.15.2 Products offered
12.3.16 LIGHTRICKS
12.3.17 SPEECHIFY
12.3.18 MIDJOURNEY
12.3.19 FIREFLIES
12.3.20 SYNTHESIA
12.3.21 MOSTLY AI
12.3.22 CHARACTER.AI
12.3.23 HYPOTENUSE AI
12.3.24 WRITESONIC
12.3.25 COPY.AI
12.3.26 SYNTHESIS AI
12.3.27 COLOSSYAN
12.3.28 INFLECTION AI
12.3.29 JASPER
12.3.30 RUNWAY
12.3.31 INWORLD AI
12.3.32 TYPEFACE
12.3.33 INSTADEEP
12.3.34 FORETHOUGHT
12.3.35 TOGETHER AI
12.3.36 UPSTAGE
12.3.37 MISTRAL AI
12.3.38 ADEPT
12.3.39 STABILITY AI
12.3.40 COHERE
12.4 OPEN-SOURCE COMPANIES
12.4.1 APPLE
12.4.2 LG
12.4.3 NOUS RESEARCH
12.4.4 FONTJOY
12.4.5 ELEUTHERAI
12.4.6 TECHNOLOGY INNOVATION INSTITUTE
12.4.7 STARRYAI
12.4.8 MAGIC STUDIO
12.4.9 ABACUS.AI
12.4.10 OPENLM
13 ADJACENT AND RELATED MARKETS
13.1 INTRODUCTION
13.2 LARGE LANGUAGE MODEL MARKET – GLOBAL FORECAST TO 2030
13.2.1 MARKET DEFINITION
13.2.2 MARKET OVERVIEW
13.2.2.1 Large language model market, by offering
13.2.2.2 Large language model market, by architecture
13.2.2.3 Large language model market, by modality
13.2.2.4 Large language model market, by model size
13.2.2.5 Large language model market, by application
13.2.2.6 Large language model market, by end user
13.2.2.7 Large language model market, by region
13.3 ARTIFICIAL INTELLIGENCE MARKET – GLOBAL FORECAST TO 2032
13.3.1 MARKET DEFINITION
13.3.2 MARKET OVERVIEW
13.3.2.1 Artificial intelligence (AI) market, by offering
13.3.2.2 Artificial intelligence (AI) market, by technology
13.3.2.3 Artificial intelligence (AI) market, by business function
13.3.2.4 Artificial intelligence (AI) market, by enterprise application
13.3.2.5 Artificial intelligence (AI) market, by end user
13.3.2.6 Artificial intelligence (AI) market, by region
14 APPENDIX
14.1 DISCUSSION GUIDE
14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
14.3 CUSTOMIZATION OPTIONS
14.4 RELATED REPORTS
14.5 AUTHOR DETAILS
