Artificial Intelligence (AI) Market by Offering (Infrastructure, Software, Services), Technology (ML, NLP, Generative AI), Business Function (Operations & Supply Chain, Finance & Accounting), Enterprise Application, and End User - Global Forecast to 2032
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.
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:
“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%
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.
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
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
