세계의 인공지능(AI) 시장 : 제공별, 기술별, 비즈니스 기능별, 기업 용도별, 최종사용자별, 지역별 - 예측(-2032년)

The AI market is projected to grow from USD 371.71 billion in 2025 to USD 2,407.02 billion in 2032, at a CAGR of 30.6% during 2025-2032. The AI market is driven by advancements in generative AI and large language models, fueling innovations in hyper-personalization for customer engagement and AI-assisted decision-making. These technologies enable businesses to enhance customer experiences and make data-driven decisions. However, the market faces significant restraints, including challenges related to data availability and quality, which impact model performance. Additionally, AI's high energy consumption and environmental impact raise concerns, especially with large-scale deployments, hindering widespread adoption and sustainability in industries looking to implement AI solutions efficiently.

"By infrastructure, the networking hardware segment is expected to register the highest growth rate during the forecast period."

Networking hardware is set to be the fastest-growing segment in the AI market due to the increasing demand for high-speed, low-latency communication between AI systems, data centers, and edge devices. AI workloads, such as training large models and real-time data processing, require a robust and efficient networking infrastructure to handle vast amounts of data with minimal delay. Use cases like autonomous vehicles, where real-time data from sensors needs to be processed and communicated quickly, and edge AI deployments in manufacturing, where quick data transmission between devices and centralized systems is crucial, highlight the need for advanced networking hardware. Additionally, the growth of cloud-based AI solutions and the demand for AI in IoT applications are further driving the need for scalable, high-performance networking hardware to support these evolving technologies.

"By business function, marketing and sales is expected to account for the largest market share during the forecast period."

Marketing and sales are expected to dominate the AI market share, driven by AI's transformative impact on customer engagement and sales efficiency. AI enables hyper-personalized marketing, predictive analytics, and automation, leading to improved customer experiences and increased revenue. For instance, companies like Delta Air Lines and Mars utilize AI to optimize advertising strategies, resulting in substantial sales growth. Additionally, AI-powered tools like chatbots and predictive lead scoring enhance sales processes, boosting conversion rates and productivity. The integration of AI in marketing and sales not only streamlines operations but also delivers measurable returns on investment, solidifying its position as a key driver in the AI market.

"By region, North America to have the largest market share in 2025, and Asia Pacific is slated to grow at the highest rate during the forecast period."

North America continues to dominate the AI market, driven by substantial investments from major tech companies and supportive government policies. Companies like Nvidia and AMD are at the forefront, developing advanced AI hardware and software solutions. AI adoption across sectors such as predictive analytics in healthcare, personalized customer service in retail, and intelligent automation in finance continues to drive momentum. North America's strong emphasis on public-private collaboration, digital transformation, and AI education also contributes to its dominant market position. In January 2025, President Trump signed 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 AI advancement.

Asia Pacific is experiencing the fastest growth in the AI market, driven by proactive government policies, increasing digital transformation, and heavy investments by regional tech leaders. In China, companies like Baidu, Alibaba, and Tencent are advancing AI across sectors, including autonomous driving, e-commerce, and healthcare. The Chinese government has introduced clear frameworks for generative AI services, providing regulatory clarity that supports innovation. Meanwhile, India has launched the IndiaAI initiative and recently established the IndiaAI Safety Institute to boost domestic R&D and ensure safe AI deployment. Countries across the region are leveraging AI for smart manufacturing, intelligent logistics, and advanced language processing. As digital economies mature and AI integration deepens, Asia Pacific is poised to be a global hotspot for AI innovation.

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 AI market.

• By Company: Tier I - 38%, Tier II - 27%, and Tier III - 35%
• By Designation: C-Level Executives - 33%, D-Level Executives - 40%, and others - 27%
• By Region: North America - 41%, Europe - 36%, Asia Pacific - 14%, Middle East & Africa - 5%, and Latin America - 4%

The report includes the study of key players offering AI solutions. It profiles major vendors in the AI market. The major players in the AI market include Microsoft (US), IBM (US), Google (US), Oracle (US), AWS (US), NVIDIA (US), Meta (US), Salesforce (US), OpenAI (US), Oracle (US), Intel (US), SAP (Germany), AMD (US), Qualcomm (US), Cisco (US), HPE (US), Siemens (Germany), Baidu (China), SAS Institute (US), Huawei (China), Alibaba Cloud (China), Centific (US), Fractal Analytics (US), Tiger Analytics (US), Quantiphi (US), databricks (US), iMerit (US), Telus International (US), Innodata (US), and Sama (US).

Research coverage

This research report categorizes the AI market by Offering (Infrastructure, Software, and Services), Technology (Machine Learning, Natural Language Processing, Computer Vision, Context-aware Artificial Intelligence (CAAI), and Generative AI), Business Function (Marketing and Sales, Human Resources, Finance and Accounting, Operations & Supply Chain, and Other Business Functions), Enterprise Application (BFSI, Transportation & Logistics, Government & Defense, Healthcare & Life Sciences, Telecommunication, Energy & Utilities, Manufacturing, Agriculture, Software & Technology Providers, Media & Entertainment, and Other Enterprise Applications), End User (Consumers and Enterprises [BFSI, Retail & E-commerce, Transportation & Logistics, Government & Defense, Healthcare & Life Sciences, Telecommunications, Energy & Utilities, Manufacturing, Education, 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 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, product & service launches, mergers and acquisitions, and recent developments associated with the AI market. This report covers a competitive analysis of upcoming startups in the 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 AI market and its subsegments. It would help stakeholders understand the competitive landscape and gain more insights better to 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 (Growth in adoption of autonomous artificial intelligence, Rise of deep learning and machine learning technologies, and advancements in computing power and availability of large databases), restraints (Increasing concerns over IP ownership and legal risks in generative AI-generated content, Cost and complexity of aligning models with enterprise-specific compliance and governance policies, and fragmentation in AI toolchains and lack of standardized evaluation frameworks for enterprise readiness), opportunities (Advancements in AI-native infrastructure enhancing scalability and performance, Expansion of edge AI capabilities for real-time data processing and decision-making, and advancements in generative AI to open new avenues for AI-powered content creation), and challenges (Lack of transparency and explainability in decision-making process of AI, Concerns related to bias and inaccurately generated output, and integration challenges and lack of understanding of state-of-the-art systems).
• Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and product & service launches in the AI market.
• Market Development: Comprehensive information about lucrative markets - the report analyzes the AI market across varied regions.
• Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI market.
• Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Microsoft (US), IBM (US), Google (US), Oracle (US), AWS (US), NVIDIA (US), Meta (US), Salesforce (US), OpenAI (US), Oracle (US), Intel (US), SAP (Germany), AMD (US), Qualcomm (US), Cisco (US), HPE (US), Siemens (Germany), Baidu (China), SAS Institute (US), Huawei (China), Alibaba Cloud (China), Centific (US), Fractal Analytics (US), Tiger Analytics (US), Quantiphi (US), databricks (US), iMerit (US), Telus International (US), Innodata (US), and Sama (US), among others in the AI market. The report also helps stakeholders understand the pulse of the 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 STUDY LIMITATIONS

3 EXECUTIVE SUMMARY

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES IN ARTIFICIAL INTELLIGENCE MARKET
• 4.2 ARTIFICIAL INTELLIGENCE MARKET: TOP THREE TECHNOLOGIES
• 4.3 NORTH AMERICA: ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING AND ENTERPRISE APPLICATION
• 4.4 ARTIFICIAL INTELLIGENCE MARKET, BY REGION

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Growth in adoption of autonomous artificial intelligence
    • 5.2.1.2 Rise of deep learning and machine learning technologies
    • 5.2.1.3 Advancements in computing power and availability of large databases
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Increasing concerns over IP ownership and legal risks in generative AI-generated content
    • 5.2.2.2 Cost and complexity of aligning models with enterprise-specific compliance and governance policies
    • 5.2.2.3 Fragmentation in AI toolchains and lack of standardized evaluation frameworks for enterprise readiness
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 Advancements in AI-native infrastructure enhancing scalability and performance
    • 5.2.3.2 Expansion of edge AI capabilities for real-time data processing and decision-making
    • 5.2.3.3 Advancements in generative AI to open new avenues for AI-powered content creation
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Lack of transparency and explainability in decision-making process of AI
    • 5.2.4.2 Concerns related to bias and inaccurately generated output
    • 5.2.4.3 Integration challenges and lack of understanding of state-of-the-art systems
• 5.3 ARTIFICIAL INTELLIGENCE MARKET: EVOLUTION
• 5.4 SUPPLY CHAIN ANALYSIS
• 5.5 ECOSYSTEM ANALYSIS
  • 5.5.1 ARTIFICIAL INTELLIGENCE HARDWARE PROVIDERS
  • 5.5.2 ARTIFICIAL INTELLIGENCE SOFTWARE PROVIDERS
  • 5.5.3 ARTIFICIAL INTELLIGENCE SERVICE PROVIDERS
• 5.6 IMPACT OF 2025 US TARIFF - ARTIFICIAL INTELLIGENCE (AI) MARKET
  • 5.6.1 INTRODUCTION
  • 5.6.2 KEY TARIFF RATES
  • 5.6.3 PRICE IMPACT ANALYSIS
    • 5.6.3.1 Strategic Shifts and Emerging Trends
  • 5.6.4 IMPACT ON COUNTRY/REGION
    • 5.6.4.1 US
      • 5.6.4.1.1 Strategic Shifts and Key Observations
    • 5.6.4.2 China
      • 5.6.4.2.1 Strategic Shifts and Key Observations
    • 5.6.4.3 Europe
      • 5.6.4.3.1 Strategic Shifts and Key Observations
    • 5.6.4.4 Asia Pacific (excluding China)
      • 5.6.4.4.1 Strategic Shifts and Key Observations
  • 5.6.5 IMPACT ON END-USE INDUSTRIES
    • 5.6.5.1 BFSI
    • 5.6.5.2 Healthcare & Life Sciences
    • 5.6.5.3 Manufacturing
    • 5.6.5.4 Retail & E-commerce
    • 5.6.5.5 Telecommunications
    • 5.6.5.6 Transportation & Logistics
    • 5.6.5.7 Software & Technology Providers
    • 5.6.5.8 Energy & Utilities
• 5.7 INVESTMENT LANDSCAPE AND FUNDING SCENARIO
• 5.8 CASE STUDY ANALYSIS
  • 5.8.1 IBM AND VODAFONE: TRANSFORMING CUSTOMER ENGAGEMENT WITH AI-POWERED VIRTUAL ASSISTANT TOBI
  • 5.8.2 MICROSOFT AND MARS: ADVANCING SUPPLY CHAIN OPTIMIZATION WITH AZURE MACHINE LEARNING
  • 5.8.3 NVIDIA AND PERPLEXITY AI: BOOSTING MODEL PERFORMANCE AND COST EFFICIENCY WITH NEMO FRAMEWORK
  • 5.8.4 OPENAI AND NOTION: POWERING INTELLIGENT PRODUCTIVITY WITH EMBEDDED AI ASSISTANTS
  • 5.8.5 GOOGLE CLOUD AND GE APPLIANCES: DELIVERING PERSONALIZED COOKING EXPERIENCES WITH GENERATIVE AI
• 5.9 TECHNOLOGY ANALYSIS
  • 5.9.1 KEY TECHNOLOGIES
    • 5.9.1.1 Generative AI
    • 5.9.1.2 Autonomous AI & Autonomous Agents
    • 5.9.1.3 AutoML
    • 5.9.1.4 Causal AI
    • 5.9.1.5 MLOps
  • 5.9.2 COMPLEMENTARY TECHNOLOGIES
    • 5.9.2.1 Blockchain
    • 5.9.2.2 Edge Computing
    • 5.9.2.3 Sensors and Robotics
    • 5.9.2.4 Cybersecurity
  • 5.9.3 ADJACENT TECHNOLOGIES
    • 5.9.3.1 Predictive Analytics
    • 5.9.3.2 IoT
    • 5.9.3.3 Big Data
    • 5.9.3.4 Augmented Reality/Virtual Reality
• 5.10 TARIFF AND REGULATORY LANDSCAPE
  • 5.10.1 TARIFF RELATED TO PROCESSORS AND CONTROLLERS (HSN: 854231)
  • 5.10.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.10.3 REGULATIONS: ARTIFICIAL INTELLIGENCE
    • 5.10.3.1 North America
      • 5.10.3.1.1 SCR 17: Artificial Intelligence Bill (California)
      • 5.10.3.1.2 S1103: Artificial Intelligence Automated Decision Bill (Connecticut)
      • 5.10.3.1.3 National Artificial Intelligence Initiative Act (NAIIA)
      • 5.10.3.1.4 The Artificial Intelligence and Data Act (AIDA) - Canada
    • 5.10.3.2 Europe
      • 5.10.3.2.1 The European Union (EU) - Artificial Intelligence Act (AIA)
      • 5.10.3.2.2 General Data Protection Regulation (Europe)
    • 5.10.3.3 Asia Pacific
      • 5.10.3.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services (China)
      • 5.10.3.3.2 The National AI Strategy (Singapore)
      • 5.10.3.3.3 The Hiroshima AI Process Comprehensive Policy Framework (Japan)
    • 5.10.3.4 Middle East & Africa
      • 5.10.3.4.1 The National Strategy for Artificial Intelligence (UAE)
      • 5.10.3.4.2 The National Artificial Intelligence Strategy (Qatar)
      • 5.10.3.4.3 The AI Ethics Principles and Guidelines (Dubai)
    • 5.10.3.5 Latin America
      • 5.10.3.5.1 The Santiago Declaration (Chile)
      • 5.10.3.5.2 The Brazilian Artificial Intelligence Strategy (EBIA)
• 5.11 PATENT ANALYSIS
  • 5.11.1 METHODOLOGY
  • 5.11.2 PATENTS FILED, BY DOCUMENT TYPE
  • 5.11.3 INNOVATION AND PATENT APPLICATIONS
• 5.12 PRICING ANALYSIS
  • 5.12.1 AVERAGE SELLING PRICE OF OFFERING, BY KEY PLAYER, 2025
  • 5.12.2 AVERAGE SELLING PRICE, BY APPLICATION, 2025
• 5.13 TRADE ANALYSIS
  • 5.13.1 EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
  • 5.13.2 IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
• 5.14 KEY CONFERENCES AND EVENTS (2025-2026)
• 5.15 PORTER'S FIVE FORCES ANALYSIS
  • 5.15.1 THREAT OF NEW ENTRANTS
  • 5.15.2 THREAT OF SUBSTITUTES
  • 5.15.3 BARGAINING POWER OF SUPPLIERS
  • 5.15.4 BARGAINING POWER OF BUYERS
  • 5.15.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.16 KEY STAKEHOLDERS & BUYING CRITERIA
  • 5.16.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.16.2 BUYING CRITERIA
• 5.17 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS' BUSINESSES
  • 5.17.1 TRENDS/DISRUPTIONS IMPACTING CUSTOMERS' BUSINESSES

6 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING

• 6.1 INTRODUCTION
  • 6.1.1 OFFERING: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
• 6.2 INFRASTRUCTURE, BY TYPE
  • 6.2.1 AI MARKET GROWTH DRIVEN BY ROBUST INFRASTRUCTURE
  • 6.2.2 COMPUTE
    • 6.2.2.1 Graphics Processing Unit (GPU)
    • 6.2.2.2 Central Processing Unit (CPU)
    • 6.2.2.3 Field-programmable Gate Array (FPGA)
  • 6.2.3 MEMORY
    • 6.2.3.1 Double Data Rate (DDR)
    • 6.2.3.2 High Bandwidth Memory (HBM)
  • 6.2.4 NETWORKING HARDWARE
    • 6.2.4.1 NIC/Network Adapters
      • 6.2.4.1.1 Ethernet
      • 6.2.4.1.2 InfiniBand
    • 6.2.4.2 Interconnects
  • 6.2.5 STORAGE
• 6.3 INFRASTRUCTURE, BY FUNCTION
  • 6.3.1 INFERENCE INFRASTRUCTURE IN HIGH DEMAND AS ORGANIZATIONS MOVE TOWARD REAL-WORLD IMPLEMENTATION
  • 6.3.2 TRAINING
  • 6.3.3 INFERENCE
• 6.4 SOFTWARE
  • 6.4.1 EMPOWERING SCALABLE INTELLIGENCE WITH PURPOSE-BUILT TOOLS
  • 6.4.2 DIGITAL ASSISTANT & BOTS
  • 6.4.3 MACHINE LEARNING FRAMEWORKS
  • 6.4.4 NO-CODE/LOW-CODE ML TOOLS
  • 6.4.5 COMPUTER VISION PLATFORMS
  • 6.4.6 DATA PRE-PROCESSING TOOLS
  • 6.4.7 BUSINESS INTELLIGENCE & ANALYTICS PLATFORMS
  • 6.4.8 DEVELOPER PLATFORMS
  • 6.4.9 OTHER AI SOFTWARE
• 6.5 SERVICES
  • 6.5.1 POWERING AI SYSTEMS THROUGH STRUCTURED AND GOVERNED DATA
  • 6.5.2 CORE DATA SERVICES
    • 6.5.2.1 Data Collection & Ingestion
    • 6.5.2.2 Data Processing & Transformation
    • 6.5.2.3 Data Storage & Management
    • 6.5.2.4 Data Security & Privacy
    • 6.5.2.5 Data Governance & Quality Management
    • 6.5.2.6 Data Integration & Interoperability
    • 6.5.2.7 Data Annotation & Training Data Services
      • 6.5.2.7.1 Human-in-the-loop Annotation
      • 6.5.2.7.2 Automated Labeling & Augmentation
  • 6.5.3 INTEGRATED SERVICES
    • 6.5.3.1 AI Model Development & Deployment
    • 6.5.3.2 AI Model Optimization & Fine-tuning
    • 6.5.3.3 AI Security & Compliance Services
    • 6.5.3.4 AI Software Development Services
    • 6.5.3.5 Support & Maintenance Services

7 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY

• 7.1 INTRODUCTION
  • 7.1.1 TECHNOLOGY: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
• 7.2 MACHINE LEARNING
  • 7.2.1 STRATEGIC ROLE OF MACHINE LEARNING IN ENTERPRISE AI
  • 7.2.2 SUPERVISED LEARNING
  • 7.2.3 UNSUPERVISED LEARNING
  • 7.2.4 REINFORCEMENT LEARNING
• 7.3 NATURAL LANGUAGE PROCESSING
  • 7.3.1 UNLOCKING BUSINESS VALUE FROM UNSTRUCTURED AND MULTILINGUAL DATA
  • 7.3.2 NATURAL LANGUAGE UNDERSTANDING
  • 7.3.3 NATURAL LANGUAGE GENERATION
• 7.4 COMPUTER VISION AI
  • 7.4.1 COMPUTER VISION AI TRANSLATES VISUAL DATA INTO REAL-TIME, ACTIONABLE INSIGHTS
  • 7.4.2 OBJECT DETECTION
  • 7.4.3 IMAGE CLASSIFICATION
  • 7.4.4 SEMANTIC SEGMENTATION
  • 7.4.5 FACIAL RECOGNITION
  • 7.4.6 OTHER COMPUTER VISION AI
• 7.5 CONTEXT-AWARE ARTIFICIAL INTELLIGENCE
  • 7.5.1 VIRTUAL ASSISTANTS MAINTAIN CONTINUITY AND INTENT ACROSS INTERACTIONS AND PLATFORMS
  • 7.5.2 CONTEXT-AWARE RECOMMENDATION SYSTEMS
  • 7.5.3 MULTI-MODAL AI
  • 7.5.4 CONTEXT-AWARE VIRTUAL ASSISTANTS
• 7.6 GENERATIVE AI
  • 7.6.1 DEEP LEARNING MODELS ENABLE MACHINES TO PRODUCE CONTEXTUALLY RELEVANT AND REALISTIC OUTPUTS

8 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION

• 8.1 INTRODUCTION
  • 8.1.1 BUSINESS FUNCTION: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
• 8.2 MARKETING & SALES
  • 8.2.1 PERSONALIZING MARKETING EFFORTS THROUGH CONTENT AND AUDIENCE SEGMENTATION
  • 8.2.2 SENTIMENT ANALYSIS
  • 8.2.3 PREDICTIVE FORECASTING
  • 8.2.4 CONTENT GENERATION & MARKETING
  • 8.2.5 AUDIENCE SEGMENTATION & PERSONALIZATION
  • 8.2.6 CUSTOMER EXPERIENCE MANAGEMENT
  • 8.2.7 OTHER MARKETING & SALES FUNCTIONS
• 8.3 HUMAN RESOURCES
  • 8.3.1 ALIGNING EMPLOYEE PERFORMANCE WITH ORGANIZATIONAL GOALS USING AI
  • 8.3.2 ONBOARDING AUTOMATION
  • 8.3.3 CANDIDATE SCREENING & RECRUITMENT
  • 8.3.4 PERFORMANCE MANAGEMENT
  • 8.3.5 WORKFORCE MANAGEMENT
  • 8.3.6 EMPLOYEE FEEDBACK ANALYSIS
  • 8.3.7 OTHER HUMAN RESOURCES FUNCTIONS
• 8.4 FINANCE & ACCOUNTING
  • 8.4.1 ENHANCING FORECASTING AND FINANCIAL PLANNING WITH AI
  • 8.4.2 FINANCIAL PLANNING & FORECASTING
  • 8.4.3 AUTOMATED BOOKKEEPING & RECONCILIATION
  • 8.4.4 PROCUREMENT & SUPPLY CHAIN FINANCE
  • 8.4.5 REVENUE CYCLE MANAGEMENT
  • 8.4.6 FINANCIAL COMPLIANCE & REGULATORY REPORTING
  • 8.4.7 OTHER FINANCE & ACCOUNTING FUNCTIONS
• 8.5 OPERATIONS & SUPPLY CHAIN
  • 8.5.1 ACCURATE DEMAND FORECASTING WITH AI FOR SMARTER PLANNING
  • 8.5.2 AIOPS
  • 8.5.3 IT SERVICE MANAGEMENT
  • 8.5.4 DEMAND PLANNING & FORECASTING
  • 8.5.5 PROCUREMENT & SOURCING
  • 8.5.6 WAREHOUSE & INVENTORY MANAGEMENT
  • 8.5.7 PRODUCTION PLANNING & SCHEDULING
  • 8.5.8 OTHER OPERATIONS & SUPPLY CHAIN FUNCTIONS
• 8.6 OTHER BUSINESS FUNCTIONS

9 ARTIFICIAL INTELLIGENCE MARKET, BY ENTERPRISE APPLICATION

• 9.1 INTRODUCTION
  • 9.1.1 ENTERPRISE APPLICATION: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
• 9.2 BFSI
  • 9.2.1 ADOPTION OF AI IN BFSI DRIVEN BY RISING DATA VOLUMES, REGULATORY COMPLEXITY, AND EVOLVING CUSTOMER EXPECTATIONS
  • 9.2.2 FRAUD DETECTION AND PREVENTION
  • 9.2.3 RISK ASSESSMENT AND MANAGEMENT
  • 9.2.4 ALGORITHMIC TRADING
  • 9.2.5 CREDIT SCORING AND UNDERWRITING
  • 9.2.6 CUSTOMER SERVICE AUTOMATION
  • 9.2.7 PERSONALIZED FINANCIAL RECOMMENDATIONS
  • 9.2.8 INVESTMENT PORTFOLIO MANAGEMENT
  • 9.2.9 REGULATORY COMPLIANCE MONITORING
  • 9.2.10 OTHER BFSI APPLICATIONS
• 9.3 RETAIL & E-COMMERCE
  • 9.3.1 PRICE OPTIMIZATION AND SUPPLY CHAIN MANAGEMENT-LIKE FUNCTIONS BEING REVOLUTIONIZED THROUGH PREDICTIVE ALGORITHMS AND REAL-TIME ANALYTICS
  • 9.3.2 PERSONALIZED PRODUCT RECOMMENDATION
  • 9.3.3 CUSTOMER RELATIONSHIP MANAGEMENT
  • 9.3.4 VISUAL SEARCH
  • 9.3.5 VIRTUAL CUSTOMER ASSISTANT
  • 9.3.6 PRICE OPTIMIZATION
  • 9.3.7 SUPPLY CHAIN MANAGEMENT & DEMAND PLANNING
  • 9.3.8 VIRTUAL STORES
  • 9.3.9 OTHER RETAIL & E-COMMERCE APPLICATIONS
• 9.4 TRANSPORTATION & LOGISTICS
  • 9.4.1 SUPPLY CHAIN VISIBILITY AND TRACKING ENHANCED THROUGH AI-DRIVEN REAL-TIME MONITORING AND PREDICTIVE ANALYTICS
  • 9.4.2 ROUTE OPTIMIZATION
  • 9.4.3 DRIVER ASSISTANCE SYSTEM
  • 9.4.4 SEMI-AUTONOMOUS & AUTONOMOUS VEHICLES
  • 9.4.5 INTELLIGENT TRAFFIC MANAGEMENT
  • 9.4.6 SMART LOGISTICS AND WAREHOUSING
  • 9.4.7 SUPPLY CHAIN VISIBILITY AND TRACKING
  • 9.4.8 FLEET MANAGEMENT
  • 9.4.9 OTHER TRANSPORTATION AND LOGISTICS APPLICATIONS
• 9.5 GOVERNMENT & DEFENSE
  • 9.5.1 AI STRENGTHENS COMMAND AND CONTROL SYSTEMS BY INTEGRATING DATA FOR UNIFIED OPERATIONAL VIEWS AND STRATEGIC DECISIONS
  • 9.5.2 SURVEILLANCE AND SITUATIONAL AWARENESS
  • 9.5.3 LAW ENFORCEMENT
  • 9.5.4 INTELLIGENCE ANALYSIS AND DATA PROCESSING
  • 9.5.5 SIMULATION AND TRAINING
  • 9.5.6 COMMAND AND CONTROL
  • 9.5.7 DISASTER RESPONSE AND RECOVERY ASSISTANCE
  • 9.5.8 E-GOVERNANCE AND DIGITAL CITY SERVICES
  • 9.5.9 OTHER GOVERNMENT & DEFENSE APPLICATIONS
• 9.6 HEALTHCARE & LIFE SCIENCES
  • 9.6.1 AI EXTENDS ITS IMPACT INTO DRUG DISCOVERY, VIRTUAL CARE, AND MEDICAL RESEARCH
  • 9.6.2 PATIENT DATA AND RISK ANALYSIS
  • 9.6.3 LIFESTYLE MANAGEMENT AND MONITORING
  • 9.6.4 PRECISION MEDICINE
  • 9.6.5 INPATIENT CARE AND HOSPITAL MANAGEMENT
  • 9.6.6 MEDICAL IMAGING AND DIAGNOSTICS
  • 9.6.7 DRUG DISCOVERY
  • 9.6.8 AI-ASSISTED MEDICAL SERVICES
  • 9.6.9 MEDICAL RESEARCH
  • 9.6.10 OTHER HEALTHCARE & LIFE SCIENCES APPLICATIONS
• 9.7 TELECOMMUNICATIONS
  • 9.7.1 TELECOM OPERATORS TURNING TO AI TO ENHANCE AGILITY, REDUCE OPERATIONAL COSTS, AND DELIVER SUPERIOR USER EXPERIENCES
  • 9.7.2 NETWORK OPTIMIZATION
  • 9.7.3 NETWORK SECURITY
  • 9.7.4 CUSTOMER SERVICE AND SUPPORT
  • 9.7.5 NETWORK ANALYTICS
  • 9.7.6 INTELLIGENT CALL ROUTING
  • 9.7.7 NETWORK FAULT PREDICTION
  • 9.7.8 VIRTUAL NETWORK ASSISTANTS
  • 9.7.9 VOICE AND SPEECH RECOGNITION
  • 9.7.10 OTHER TELECOMMUNICATIONS APPLICATIONS
• 9.8 ENERGY & UTILITIES
  • 9.8.1 ADVANCED MACHINE LEARNING ALGORITHMS AND EDGE AI PLATFORMS ENABLING REAL-TIME OPTIMIZATION AND PREDICTIVE MAINTENANCE
  • 9.8.2 ENERGY DEMAND FORECASTING
  • 9.8.3 GRID OPTIMIZATION AND MANAGEMENT
  • 9.8.4 ENERGY CONSUMPTION ANALYTICS
  • 9.8.5 SMART METERING AND ENERGY DATA MANAGEMENT
  • 9.8.6 ENERGY STORAGE OPTIMIZATION
  • 9.8.7 REAL-TIME ENERGY MONITORING AND CONTROL
  • 9.8.8 POWER QUALITY MONITORING AND MANAGEMENT
  • 9.8.9 ENERGY TRADING AND MARKET FORECASTING
  • 9.8.10 INTELLIGENT ENERGY MANAGEMENT SYSTEMS
  • 9.8.11 OTHER ENERGY & UTILITIES APPLICATIONS
• 9.9 MANUFACTURING
  • 9.9.1 AI SUPPORTS SUSTAINABLE MANUFACTURING THROUGH RECYCLABLE MATERIAL RECLAMATION
  • 9.9.2 MATERIAL MOVEMENT MANAGEMENT
  • 9.9.3 PREDICTIVE MAINTENANCE AND MACHINERY INSPECTION
  • 9.9.4 PRODUCTION PLANNING
  • 9.9.5 RECYCLABLE MATERIAL RECLAMATION
  • 9.9.6 PRODUCTION LINE OPTIMIZATION
  • 9.9.7 QUALITY CONTROL
  • 9.9.8 INTELLIGENT INVENTORY MANAGEMENT
  • 9.9.9 OTHER MANUFACTURING APPLICATIONS
• 9.10 AGRICULTURE
  • 9.10.1 AI'S GROWING INFLUENCE IN AGRICULTURE NECESSARY STEP TOWARD FUTURE-READY FARMING SYSTEMS
  • 9.10.2 CROP MONITORING AND YIELD PREDICTION
  • 9.10.3 PRECISION FARMING
  • 9.10.4 SOIL ANALYSIS AND NUTRIENT MANAGEMENT
  • 9.10.5 PEST AND DISEASE DETECTION
  • 9.10.6 IRRIGATION OPTIMIZATION AND WATER MANAGEMENT
  • 9.10.7 AUTOMATED HARVESTING AND SORTING
  • 9.10.8 WEED DETECTION AND MANAGEMENT
  • 9.10.9 WEATHER AND CLIMATE MONITORING
  • 9.10.10 LIVESTOCK MONITORING AND HEALTH MANAGEMENT
  • 9.10.11 OTHER AGRICULTURE APPLICATIONS
• 9.11 SOFTWARE & TECHNOLOGY PROVIDERS
  • 9.11.1 FROM INTELLIGENT AUTOMATION TO ROBUST SECURITY, AI IS REDEFINING SOFTWARE CAPABILITIES
  • 9.11.2 CODE GENERATION & AUTO-COMPLETION
  • 9.11.3 BUG DETECTION & FIXING
  • 9.11.4 AUTOMATED SOFTWARE TESTING & QA
  • 9.11.5 AI-POWERED CYBERSECURITY & THREAT DETECTION
  • 9.11.6 AUTOMATED DEVOPS & CI/CD OPTIMIZATION
  • 9.11.7 OTHER SOFTWARE & TECHNOLOGY PROVIDERS APPLICATIONS
• 9.12 MEDIA AND ENTERTAINMENT
  • 9.12.1 FROM PERSONALIZED CONTENT TO COPYRIGHT PROTECTION, AI TO RESHAPE DIGITAL MEDIA STRATEGIES
  • 9.12.2 CONTENT RECOMMENDATION SYSTEMS
  • 9.12.3 CONTENT CREATION AND GENERATION
  • 9.12.4 CONTENT COPYRIGHT PROTECTION
  • 9.12.5 AUDIENCE ANALYTICS AND SEGMENTATION
  • 9.12.6 PERSONALIZED ADVERTISING
  • 9.12.7 OTHER MEDIA AND ENTERTAINMENT APPLICATIONS
• 9.13 OTHER ENTERPRISE APPLICATIONS

10 ARTIFICIAL INTELLIGENCE MARKET, BY END USER

• 10.1 INTRODUCTION
  • 10.1.1 END USER: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
• 10.2 CONSUMERS
  • 10.2.1 AI INTEGRATION INTO SMART ASSISTANTS, AND CREATIVE CONTENT GENERATION TOOLS DRIVING RAPID CONSUMER ADOPTION
• 10.3 ENTERPRISES
  • 10.3.1 BFSI
    • 10.3.1.1 Increased use of AI for fraud detection, personalized financial services, and real-time risk management in BFSI
    • 10.3.1.2 Banking
    • 10.3.1.3 Financial Services
    • 10.3.1.4 Insurance
  • 10.3.2 RETAIL & E-COMMERCE
    • 10.3.2.1 AI-powered recommendation engines, personalized marketing, and dynamic pricing are transforming consumer experiences
    • 10.3.2.2 Consumer Goods Retail
    • 10.3.2.3 Industrial Goods Retail
  • 10.3.3 TRANSPORTATION & LOGISTICS
    • 10.3.3.1 AI is optimizing route planning and supply chain visibility, enabling cost-effective and responsive transportation systems
    • 10.3.3.2 Rail
    • 10.3.3.3 Road
    • 10.3.3.4 Marine
    • 10.3.3.5 Air
  • 10.3.4 GOVERNMENT & DEFENSE
    • 10.3.4.1 AI is enabling smarter public services, enhanced security, and improved decision-making in government operations
    • 10.3.4.2 Federal Government
    • 10.3.4.3 State & Local Governments
    • 10.3.4.4 Military & Defense
    • 10.3.4.5 Public Service Agencies
  • 10.3.5 HEALTHCARE & LIFE SCIENCES
    • 10.3.5.1 AI transforming clinical and operational aspects of healthcare through rapid drug discovery and improving diagnostic accuracy
    • 10.3.5.2 Healthcare Providers
    • 10.3.5.3 Pharmaceuticals & Biotech Sector
    • 10.3.5.4 MedTech
  • 10.3.6 TELECOMMUNICATIONS
    • 10.3.6.1 Telecom providers are leveraging AI to optimize their infrastructure and services via autonomous network management
    • 10.3.6.2 Network Operators
    • 10.3.6.3 Telecom Equipment Providers
    • 10.3.6.4 Communication Service Providers (CSPs)
    • 10.3.6.5 Data & Cloud Connectivity Providers
  • 10.3.7 ENERGY & UTILITIES
    • 10.3.7.1 AI-driven energy optimization, predictive maintenance, and grid management are supporting the transition to renewable energy
    • 10.3.7.2 Oil & Gas
    • 10.3.7.3 Power Generation
    • 10.3.7.4 Utilities
  • 10.3.8 MANUFACTURING
    • 10.3.8.1 Predictive maintenance, smart factories, and automation of production lines through AI are enhancing productivity and reducing downtime
    • 10.3.8.2 Discrete Manufacturing
    • 10.3.8.3 Process Manufacturing
  • 10.3.9 SOFTWARE & TECHNOLOGY PROVIDERS
    • 10.3.9.1 AI-driven infrastructure and generative AI tools are empowering software & tech players to integrate AI into products and services
    • 10.3.9.2 Cloud Hyperscalers
    • 10.3.9.3 Foundation Model/LLM Providers
    • 10.3.9.4 AI Technology Providers
    • 10.3.9.5 IT & IT-enabled Service Providers (ITeS)
  • 10.3.10 MEDIA AND ENTERTAINMENT
    • 10.3.10.1 Generative AI tools for content creation and real-time personalization are accelerating innovation and cost reduction in media industries
    • 10.3.10.2 Publishing & Journalism
    • 10.3.10.3 Television, Film & OTT
    • 10.3.10.4 Music & Audio
    • 10.3.10.5 Gaming & Interactive Media
    • 10.3.10.6 Advertising & Marketing Agencies
    • 10.3.10.7 Other Media & Entertainment Enterprises
  • 10.3.11 OTHER ENTERPRISES
    • 10.3.11.1 AI applications like personalized learning, audience engagement, and operational optimization are driving efficiencies

11 ARTIFICIAL INTELLIGENCE MARKET, BY REGION

• 11.1 INTRODUCTION
• 11.2 NORTH AMERICA
  • 11.2.1 NORTH AMERICA: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
  • 11.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 11.2.3 US
    • 11.2.3.1 Growth initiatives by US government and businesses to drive market growth
  • 11.2.4 CANADA
    • 11.2.4.1 Rise in funding for building transformational public computing infrastructure
• 11.3 EUROPE
  • 11.3.1 EUROPE: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
  • 11.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 11.3.3 UK
    • 11.3.3.1 Continuous investments and initiatives by UK government to bolster growth of AI market
  • 11.3.4 GERMANY
    • 11.3.4.1 Germany recognizing AI as most important future technology
  • 11.3.5 FRANCE
    • 11.3.5.1 Active promotions of AI initiatives and investments in research and development to push French market forward
  • 11.3.6 ITALY
    • 11.3.6.1 Adoption of sophisticated technologies with thriving startup ecosystem in Italy to drive market growth
  • 11.3.7 SPAIN
    • 11.3.7.1 Initiatives by Spanish government to promote widespread adoption of artificial intelligence
  • 11.3.8 NORDICS
  • 11.3.9 BENELUX
  • 11.3.10 RUSSIA
  • 11.3.11 REST OF EUROPE
• 11.4 ASIA PACIFIC
  • 11.4.1 ASIA PACIFIC: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
  • 11.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 11.4.3 CHINA
    • 11.4.3.1 Government initiatives and regulations in favor of AI development in China to drive market growth
  • 11.4.4 INDIA
    • 11.4.4.1 Exploring generative AI for innovation and industry transformation in India to drive market growth
  • 11.4.5 JAPAN
    • 11.4.5.1 Japan's diverse ecosystem of startups and established tech giants to drive innovation
  • 11.4.6 SOUTH KOREA
    • 11.4.6.1 Government investments in artificial intelligence infrastructure to enhance citizen services in South Korea
  • 11.4.7 AUSTRALIA & NEW ZEALAND
    • 11.4.7.1 Business experiments with gen AI applications to analyze vast amounts of data and extract insights
  • 11.4.8 ASEAN
  • 11.4.9 REST OF ASIA PACIFIC
• 11.5 MIDDLE EAST & AFRICA
  • 11.5.1 MIDDLE EAST & AFRICA: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
  • 11.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 11.5.3 SAUDI ARABIA
    • 11.5.3.1 Greater emphasis on artificial intelligence development across key industry verticals in Saudi Arabia to drive market growth
  • 11.5.4 UAE
    • 11.5.4.1 Implementing proactive strategies and establishing regulatory frameworks for AI adoption to drive market growth
  • 11.5.5 SOUTH AFRICA
    • 11.5.5.1 Collaborations and investments to boost startup ecosystem growth
  • 11.5.6 TURKEY
    • 11.5.6.1 Turkish government fostering innovation and international collaborations to drive economic growth
  • 11.5.7 QATAR
    • 11.5.7.1 Robust and resilient physical and digital infrastructure to be key enabler for Qatar's economic development
  • 11.5.8 EGYPT
    • 11.5.8.1 Government's strategic focus on digital transformation and innovation to drive market in Egypt
  • 11.5.9 KUWAIT
    • 11.5.9.1 Rising number of investments in AI technologies and government initiatives to push market in Kuwait
  • 11.5.10 REST OF MIDDLE EAST & AFRICA
• 11.6 LATIN AMERICA
  • 11.6.1 LATIN AMERICA: ARTIFICIAL INTELLIGENCE MARKET DRIVERS
  • 11.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 11.6.3 BRAZIL
    • 11.6.3.1 Strong governmental support and growing interest from private enterprises to boost AI market in Brazil
  • 11.6.4 MEXICO
    • 11.6.4.1 Mexico to become digitally advanced country due to adoption of AI
  • 11.6.5 ARGENTINA
    • 11.6.5.1 Adoption of artificial intelligence to enhance processes and improve decision-making of businesses in Argentina
  • 11.6.6 CHILE
    • 11.6.6.1 Rise in adoption of artificial intelligence to promote research and innovation centered around human well-being to drive market growth
  • 11.6.7 REST OF LATIN AMERICA

12 COMPETITIVE LANDSCAPE

• 12.1 OVERVIEW
• 12.2 KEY PLAYER STRATEGIES, 2020-2024
• 12.3 REVENUE ANALYSIS, 2020-2024
• 12.4 MARKET SHARE ANALYSIS, 2024
  • 12.4.1 MARKET RANKING ANALYSIS, 2024
• 12.5 PRODUCT COMPARATIVE ANALYSIS
  • 12.5.1 PRODUCT COMPARATIVE ANALYSIS, BY MACHINE LEARNING
    • 12.5.1.1 Vertex AI
    • 12.5.1.2 Amazon Forecast
    • 12.5.1.3 NVIDIA Jarvis
    • 12.5.1.4 SAS Viya
    • 12.5.1.5 Microsoft Azure AI Personalizer
  • 12.5.2 PRODUCT COMPARATIVE ANALYSIS, BY NATURAL LANGUAGE PROCESSING
    • 12.5.2.1 Gensim
    • 12.5.2.2 MindMeld
    • 12.5.2.3 Google Cloud Natural Language
    • 12.5.2.4 MonkeyLearn
    • 12.5.2.5 Amazon Comprehend
  • 12.5.3 PRODUCT COMPARATIVE ANALYSIS, BY COMPUTER VISION
    • 12.5.3.1 OpenCV
    • 12.5.3.2 Viso Suite
    • 12.5.3.3 TensorFlow
    • 12.5.3.4 MATLAB
    • 12.5.3.5 Keras
• 12.6 COMPANY VALUATION AND FINANCIAL METRICS
• 12.7 COMPANY EVALUATION MATRIX: KEY PLAYERS (AI INFRASTRUCTURE), 2024
  • 12.7.1 STARS
  • 12.7.2 EMERGING LEADERS
  • 12.7.3 PERVASIVE PLAYERS
  • 12.7.4 PARTICIPANTS
  • 12.7.5 COMPANY FOOTPRINT: KEY PLAYERS (AI INFRASTRUCTURE), 2024
    • 12.7.5.1 Company Footprint
    • 12.7.5.2 Offering Footprint
    • 12.7.5.3 Technology Footprint
    • 12.7.5.4 Enterprise Application Footprint
    • 12.7.5.5 Region Footprint
• 12.8 COMPANY EVALUATION MATRIX: KEY PLAYERS (AI SOFTWARE), 2024
  • 12.8.1 STARS
  • 12.8.2 EMERGING LEADERS
  • 12.8.3 PERVASIVE PLAYERS
  • 12.8.4 PARTICIPANTS
  • 12.8.5 COMPANY FOOTPRINT: KEY PLAYERS (AI SOFTWARE), 2024
    • 12.8.5.1 Company Footprint
    • 12.8.5.2 Offering Footprint
    • 12.8.5.3 Technology Footprint
    • 12.8.5.4 Enterprise Application Footprint
    • 12.8.5.5 Region Footprint
• 12.9 COMPANY EVALUATION MATRIX: KEY PLAYERS (AI SERVICES), 2024
  • 12.9.1 STARS
  • 12.9.2 EMERGING LEADERS
  • 12.9.3 PERVASIVE PLAYERS
  • 12.9.4 PARTICIPANTS
  • 12.9.5 COMPANY FOOTPRINT: KEY PLAYERS (AI SERVICES), 2024
    • 12.9.5.1 Company Footprint
    • 12.9.5.2 Offering Footprint
    • 12.9.5.3 Technology Footprint
    • 12.9.5.4 Enterprise Application Footprint
    • 12.9.5.5 Region Footprint
• 12.10 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
  • 12.10.1 STARTUPS/SMES - AI SOFTWARE PLAYERS
    • 12.10.1.1 Progressive Companies
    • 12.10.1.2 Responsive Companies
    • 12.10.1.3 Dynamic Companies
    • 12.10.1.4 Starting Blocks
  • 12.10.2 STARTUPS/SMES - AI SERVICES PROVIDERS
    • 12.10.2.1 Progressive Companies
    • 12.10.2.2 Responsive Companies
    • 12.10.2.3 Dynamic Companies
    • 12.10.2.4 Starting Blocks
  • 12.10.3 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
    • 12.10.3.1 Detailed List of Key Startups/SMEs
    • 12.10.3.2 Competitive Benchmarking of Key Startups/SMEs
• 12.11 COMPETITIVE SCENARIO AND TRENDS
  • 12.11.1 PRODUCT LAUNCHES AND ENHANCEMENTS
  • 12.11.2 DEALS

13 COMPANY PROFILES

• 13.1 INTRODUCTION
• 13.2 MAJOR PLAYERS
  • 13.2.1 NVIDIA
    • 13.2.1.1 Business overview
    • 13.2.1.2 Products offered
    • 13.2.1.3 Recent developments
      • 13.2.1.3.1 Product launches and enhancements
      • 13.2.1.3.2 Deals
    • 13.2.1.4 MnM view
      • 13.2.1.4.1 Key strengths/Right to win
      • 13.2.1.4.2 Strategic choices
      • 13.2.1.4.3 Weaknesses and competitive threats
  • 13.2.2 MICROSOFT
    • 13.2.2.1 Business overview
    • 13.2.2.2 Products offered
    • 13.2.2.3 Recent developments
      • 13.2.2.3.1 Product launches and enhancements
      • 13.2.2.3.2 Deals
    • 13.2.2.4 MnM view
      • 13.2.2.4.1 Key strengths/Right to win
      • 13.2.2.4.2 Strategic choices
      • 13.2.2.4.3 Weaknesses and competitive threats
  • 13.2.3 AWS
    • 13.2.3.1 Business overview
    • 13.2.3.2 Products offered
    • 13.2.3.3 Recent developments
      • 13.2.3.3.1 Product launches and enhancements
      • 13.2.3.3.2 Deals
      • 13.2.3.3.3 Others
    • 13.2.3.4 MnM view
      • 13.2.3.4.1 Key strengths/Right to win
      • 13.2.3.4.2 Strategic choices
      • 13.2.3.4.3 Weaknesses and competitive threats
  • 13.2.4 GOOGLE
    • 13.2.4.1 Business overview
    • 13.2.4.2 Products offered
    • 13.2.4.3 Recent developments
      • 13.2.4.3.1 Product launches and enhancements
      • 13.2.4.3.2 Deals
      • 13.2.4.3.3 Expansions
    • 13.2.4.4 MnM view
      • 13.2.4.4.1 Key strengths/Right to win
      • 13.2.4.4.2 Strategic choices
      • 13.2.4.4.3 Weaknesses and competitive threats
  • 13.2.5 IBM
    • 13.2.5.1 Business overview
    • 13.2.5.2 Products offered
    • 13.2.5.3 Recent developments
      • 13.2.5.3.1 Product launches and enhancements
      • 13.2.5.3.2 Deals
    • 13.2.5.4 MnM view
      • 13.2.5.4.1 Key strengths/Right to win
      • 13.2.5.4.2 Strategic choices
      • 13.2.5.4.3 Weaknesses and competitive threats
  • 13.2.6 AMD
    • 13.2.6.1 Business overview
    • 13.2.6.2 Products offered
    • 13.2.6.3 Recent developments
      • 13.2.6.3.1 Product launches and enhancements
      • 13.2.6.3.2 Deals
  • 13.2.7 ORACLE
    • 13.2.7.1 Business overview
    • 13.2.7.2 Products offered
    • 13.2.7.3 Recent developments
      • 13.2.7.3.1 Product launches and enhancements
      • 13.2.7.3.2 Deals
  • 13.2.8 INTEL
    • 13.2.8.1 Business overview
    • 13.2.8.2 Products offered
    • 13.2.8.3 Recent developments
      • 13.2.8.3.1 Product launches and enhancements
      • 13.2.8.3.2 Deals
  • 13.2.9 OPENAI
    • 13.2.9.1 Business overview
    • 13.2.9.2 Solutions offered
    • 13.2.9.3 Recent developments
      • 13.2.9.3.1 Product launches and enhancements
      • 13.2.9.3.2 Deals
  • 13.2.10 BAIDU
    • 13.2.10.1 Business overview
    • 13.2.10.2 Products offered
    • 13.2.10.3 Recent developments
      • 13.2.10.3.1 Product launches and enhancements
      • 13.2.10.3.2 Deals
  • 13.2.11 QUALCOMM
    • 13.2.11.1 Business overview
    • 13.2.11.2 Products offered
    • 13.2.11.3 Recent developments
      • 13.2.11.3.1 Product launches and enhancements
      • 13.2.11.3.2 Deals
  • 13.2.12 HPE
    • 13.2.12.1 Business overview
    • 13.2.12.2 Products offered
    • 13.2.12.3 Recent developments
      • 13.2.12.3.1 Product launches and enhancements
      • 13.2.12.3.2 Deals
  • 13.2.13 ALIBABA CLOUD
    • 13.2.13.1 Business overview
    • 13.2.13.2 Products offered
    • 13.2.13.3 Recent developments
      • 13.2.13.3.1 Product launches and enhancements
      • 13.2.13.3.2 Deals
  • 13.2.14 HUAWEI
    • 13.2.14.1 Business overview
    • 13.2.14.2 Products offered
    • 13.2.14.3 Recent developments
      • 13.2.14.3.1 Product launches and enhancements
      • 13.2.14.3.2 Deals
  • 13.2.15 SALESFORCE
    • 13.2.15.1 Business overview
    • 13.2.15.2 Products offered
    • 13.2.15.3 Recent developments
      • 13.2.15.3.1 Product launches and enhancements
      • 13.2.15.3.2 Deals
  • 13.2.16 META
    • 13.2.16.1 Business overview
    • 13.2.16.2 Products offered
    • 13.2.16.3 Recent developments
      • 13.2.16.3.1 Product launches and enhancements
      • 13.2.16.3.2 Deals
  • 13.2.17 SAP
    • 13.2.17.1 Business overview
    • 13.2.17.2 Products offered
    • 13.2.17.3 Recent developments
      • 13.2.17.3.1 Product launches and enhancements
      • 13.2.17.3.2 Deals
  • 13.2.18 CISCO
    • 13.2.18.1 Business overview
    • 13.2.18.2 Products offered
    • 13.2.18.3 Recent developments
      • 13.2.18.3.1 Product launches and enhancements
      • 13.2.18.3.2 Deals
  • 13.2.19 SAS INSTITUTE
    • 13.2.19.1 Business overview
    • 13.2.19.2 Products offered
    • 13.2.19.3 Recent developments
      • 13.2.19.3.1 Product launches and enhancements
      • 13.2.19.3.2 Deals
  • 13.2.20 SIEMENS
    • 13.2.20.1 Business overview
    • 13.2.20.2 Products offered
    • 13.2.20.3 Recent developments
      • 13.2.20.3.1 Product launches and enhancements
      • 13.2.20.3.2 Deals
  • 13.2.21 DATABRICKS
  • 13.2.22 IMERIT
  • 13.2.23 CENTIFIC
    • 13.2.23.1 Business overview
    • 13.2.23.2 Solutions offered
    • 13.2.23.3 Recent developments
      • 13.2.23.3.1 Product launches and enhancements
      • 13.2.23.3.2 Deals
  • 13.2.24 QUANTIPHI
  • 13.2.25 TIGER ANALYTICS
  • 13.2.26 TELUS INTERNATIONAL
    • 13.2.26.1 Business overview
    • 13.2.26.2 Products offered
  • 13.2.27 INNODATA
    • 13.2.27.1 Business overview
    • 13.2.27.2 Products offered
    • 13.2.27.3 Recent developments
      • 13.2.27.3.1 Product launches & enhancements
  • 13.2.28 FRACTAL ANALYTICS
  • 13.2.29 SAMA
    • 13.2.29.1 Business overview
    • 13.2.29.2 Products/Solutions/Services offered
    • 13.2.29.3 Recent developments
      • 13.2.29.3.1 Product launches & enhancements
• 13.3 STARTUP/SME PROFILES
  • 13.3.1 ANTHROPIC
  • 13.3.2 SCALE AI
  • 13.3.3 C3 AI
    • 13.3.3.1 Business overview
    • 13.3.3.2 Products/Solutions/Services offered
    • 13.3.3.3 Recent developments
      • 13.3.3.3.1 Product launches and enhancements
      • 13.3.3.3.2 Deals
  • 13.3.4 DIALPAD
  • 13.3.5 CEREBRAS
  • 13.3.6 SHIELD AI
  • 13.3.7 APPIER
    • 13.3.7.1 Business overview
    • 13.3.7.2 Products offered
    • 13.3.7.3 Recent developments
      • 13.3.7.3.1 Product launches and enhancements
      • 13.3.7.3.2 Deals
  • 13.3.8 ADA
  • 13.3.9 DEEPL
  • 13.3.10 JASPER
  • 13.3.11 METROPOLIS TECHNOLOGIES
  • 13.3.12 ADEPT
  • 13.3.13 H2O.AI
  • 13.3.14 AI21 LABS
  • 13.3.15 SYNTHESIA
  • 13.3.16 COHERE
  • 13.3.17 PERSADO
  • 13.3.18 ANYSCALE
  • 13.3.19 APPEN
  • 13.3.20 SNORKEL
  • 13.3.21 COGITO TECH
    • 13.3.21.1 Business overview
    • 13.3.21.2 Products offered
  • 13.3.22 INBENTA
  • 13.3.23 OBSERVE AI
  • 13.3.24 CHARACTER.AI
  • 13.3.25 SPOT AI
  • 13.3.26 ARTHUR AI
  • 13.3.27 WRITESONIC
  • 13.3.28 INFLECTION AI
  • 13.3.29 MOSTLY AI
  • 13.3.30 LABELBOX
  • 13.3.31 GAMAYA
  • 13.3.32 GRAPHCORE
  • 13.3.33 HQE SYSTEMS, INC.
    • 13.3.33.1 Business overview
    • 13.3.33.2 Products offered
  • 13.3.34 ONE AI
  • 13.3.35 SOUNDFUL
  • 13.3.36 ARROW AI

14 ADJACENT AND RELATED MARKETS

• 14.1 INTRODUCTION
• 14.2 CONVERSATIONAL AI MARKET - GLOBAL FORECAST TO 2030
  • 14.2.1 MARKET DEFINITION
  • 14.2.2 MARKET OVERVIEW
    • 14.2.2.1 Conversational AI market, by offering
    • 14.2.2.2 Conversational AI market, by service
    • 14.2.2.3 Conversational AI market, by business function
    • 14.2.2.4 Conversational AI market, by conversational agent type
    • 14.2.2.5 Conversational AI market, by integration mode
    • 14.2.2.6 Conversational AI market, by vertical
    • 14.2.2.7 Conversational AI market, by region
• 14.3 GENERATIVE AI MARKET - GLOBAL FORECAST TO 2030
  • 14.3.1 MARKET DEFINITION
  • 14.3.2 MARKET OVERVIEW
    • 14.3.2.1 Generative AI market, by offering
    • 14.3.2.2 Generative AI market, by data modality
    • 14.3.2.3 Generative AI market, by application
    • 14.3.2.4 Generative AI market, by end user
    • 14.3.2.5 Generative AI market, by region

15 APPENDIX

• 15.1 DISCUSSION GUIDE
• 15.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 15.3 CUSTOMIZATION OPTIONS
• 15.4 RELATED REPORTS
• 15.5 AUTHOR DETAILS