세계의 에이전트 AI 시장 예측(-2032년) : 소프트웨어별, 에이전트의 역할별, 용도별

The agentic AI market is projected to grow from USD 7.06 billion in 2025 to USD 93.20 billion in 2032, with a CAGR of 44.6% during 2025-2032.

The agentic AI market is growing fast, driven by increasing support from agentic AI platforms for fine-tuning agents on domain-specific reinforcement learning from human feedback (RLHF), chain of thought reasoning (CoT), and behavior datasets, code-interpreter agents write, test, debug, and execute code to complete complex tasks, allowing agents to iteratively refine their methods, and sandboxes help fine-tune agent behavior under edge cases, especially for mission-critical applications which helps grow confidence in the agentic AI solutions. However, there are also some restraints. Most agentic AI platforms rely on commercial LLMs (e.g., GPT-4, Claude) as core reasoners. This creates vendor lock-in, cost scalability issues, and operational risks if APIs fail or change, and without unified memory standards, agents cannot collaborate effectively or retain institutional knowledge reliably.

"By use case, vertical use cases expected to register the fastest growth during the forecast period."

Vertical use cases are set to record the highest CAGR in the agentic AI market as organizations increasingly shift from generic automation to highly contextual, industry-specific agentic applications that solve unique sector challenges. Sectors like BFSI, healthcare, manufacturing, logistics, and automotive are actively embedding autonomous AI agents into core operations to automate tasks that require domain-specific reasoning and real-time decision-making. For instance, banks are using agentic AI for fraud detection, real-time compliance monitoring, and autonomous risk assessment, while manufacturers deploy agentic systems for smart factory operations, predictive maintenance, and supply chain optimization. This vertical focus not only drives faster ROI but also supports critical outcomes like safety, efficiency, and regulatory adherence. Governments and defense bodies are rapidly piloting agentic surveillance and disaster response planning, while energy players tap autonomous agents for grid optimization and leak detection. With more industry players favoring pre-built, domain-adapted agentic modules over broad platforms, the appetite for vertical use cases is expanding. Vendors are responding with tailored offerings, plug-and-play integrations, and managed services, making adoption easier for regulated and complex sectors. These factors together position vertical use cases as the strongest growth lever, aligning Agentic AI's promise directly with tangible industry KPIs and deep transformation roadmaps.

"By end user, professional service providers expected to account for the largest market share during the forecast period."

Professional service providers are poised to capture the largest market share in the agentic AI market as enterprises increasingly rely on their specialized expertise to navigate the complexity of deploying autonomous AI agents at scale. Major consulting and IT service firms such as Accenture, Deloitte, TCS, Wipro, and Capgemini are expanding their agentic AI portfolios by combining advisory, design, integration, and managed services under one roof. This end-to-end model allows clients in sectors like BFSI, manufacturing, telecom, and government to implement advanced agentic solutions without needing in-house AI engineering teams or deep AI governance capabilities. Professional services firms also play a critical role in customizing agentic AI to align with industry-specific regulations, security standards, and legacy infrastructure. Additionally, many providers now build and maintain partnerships with technology vendors to deliver tailored, plug-and-play agentic AI frameworks, accelerating time-to-value for clients. Their strong global delivery networks, industry-certified talent pools, and proven track records in driving enterprise digital transformation further strengthen their position. As enterprises look for trusted partners to manage risk, handle large-scale deployments, and deliver measurable ROI from agentic AI, professional service providers are naturally emerging as the largest revenue contributors in this evolving market.

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

North America is expected to hold the largest market share in the agentic AI market during the forecast period, driven by early adoption, strong cloud infrastructure, and the presence of key innovators such as OpenAI, Google, Microsoft, and AWS. The region benefits from a mature AI ecosystem, government-backed R&D (e.g., DARPA and NSF initiatives), and enterprise readiness to implement autonomous, agent-driven workflows across sectors like defense, finance, and software. In contrast, the Asia Pacific region is projected to grow at the highest CAGR, fueled by aggressive digital transformation efforts, rising investments in AI research from countries like China, Japan, South Korea, and Singapore, and a rapidly expanding base of AI startups. Governments in the region are also rolling out strategic frameworks and sandboxes to accelerate agent-based automation in manufacturing, public services, and telecom sectors. This dual dynamic reflects North America's current technological leadership and Asia Pacific's growing momentum in scalable agentic AI deployment.

Breakdown of primaries

In-depth interviews were conducted with innovation and technology directors, system integrators, and executives from various key organizations operating in the agentic AI market.

• By Company: Tier I - 29%, Tier II - 42%, and Tier III - 29%
• By Designation: Directors - 27%, Managers - 39%, and others - 34%
• By Region: North America - 41%, Europe - 27%, Asia Pacific - 24%, Middle East & Africa - 3%, and Latin America - 5%

The report includes the study of key players offering agentic AI solutions. It profiles major vendors in the agentic AI market. The major players in the agentic AI market include Aisera (US), Avanade (US), PwC (UK), Wipro (India), HCL Tech (India), Cognizant (US), Cisco (US), Ericsson (Sweden), NTT Data (Japan), SAS (US), Capgemini (France), Appian (US), IBM (US), ServiceNow (US), Accenture (Ireland), EY (UK), Salesforce (US), Pega (US), SAP (Germany), Snowflake (US), Altair (US), CyberArk (Israel), Zycus (US), Oracle (US), OpenAI (US), UiPath (US), Deloitte (UK), AWS (US), Microsoft (US), NVIDIA (US), Google (US), Newgen (India), Hexaware (India), AMD (US), Amdocs (US), ValueLabs (India), TCS (India), Datamatics (US), Rewind AI (US), Ema (US), Exa (US), Orby AI (US), Artisan AI (US), Dexa AI (US), Simular (US), relevance AI (US), and Adept AI (US).

Research coverage

This research report categorizes the agentic AI market by Offering (Agentic AI Infrastructure, Agentic AI Platforms, Agentic AI SaaS, and Agentic AI Services), Use Case (Vertical Use Case, and Horizontal Use Case [Finance & Accounting, Workplace Experience, Sales, Data Analytics & BI, Marketing, Security Ops, Customer Experience, Data Retrieval, Coding & Testing, and Regulatory Compliance]), End User (Individual Users, and Enterprise), 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 agentic 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 agentic AI market. Competitive analysis of upcoming startups in the agentic AI market ecosystem is covered in this report.

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 agentic 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 (Increasing enterprise need for hyper-automation to streamline workflows end-to-end, Breakthroughs in LLMs, memory, and orchestration frameworks enable autonomous multi-step task execution, Widespread access to high-performance computing and scalable AI deployment environments, and Growing maturity of digital twins with agentic orchestration for real-world simulation), restraints (Inconsistent standards for safe agent coordination across geographies, and Unclear ROI for some sectors where simpler automation suffices), opportunities (New orchestration engines for multiple autonomous agents working collaboratively, Scaling autonomous agents across BFSI, telecom, and manufacturing for digital transformation, and Emerging AI regulations are unlocking new markets for complaint autonomy), and challenges (Fragmented autonomy stacks and missing interoperability standards restrict system integration, and Legal and ethical gaps around autonomous actions are delaying adoption in regulated sectors).

Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and product & service launches in the agentic AI market.

Market Development: Comprehensive information about lucrative markets - the report analyzes the agentic AI market across varied regions.

Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the agentic AI market.

Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players like Aisera (US), Avanade (US), PwC (UK), Wipro (India), HCL Tech (India), Cognizant (US), Cisco (US), Ericsson (Sweden), NTT Data (Japan), SAS (US), Capgemini (France), Appian (US), IBM (US), ServiceNow (US), Accenture (Ireland), EY (UK), Salesforce (US), Pega (US), SAP (Germany), Snowflake (US), Altair (US), CyberArk (Israel), Zycus (US), Oracle (US), OpenAI (US), UiPath (US), Deloitte (UK), AWS (US), Microsoft (US), NVIDIA (US), Google (US), Newgen (India), Hexaware (India), AMD (US), Amdocs (US), ValueLabs (India), TCS (India), Datamatics (US), Rewind AI (US), EMA (US), Exa (US), Orby AI (US), Artisan AI (US), Dexa AI (US), Simular (US), relevance AI (US), and Adept AI (US), among others in the agentic AI market. The report also helps stakeholders understand the pulse of the agentic 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

• 3.1 THE DAWN OF AGENTIC AI
• 3.2 UNDERSTANDING AGENTIC AI: DEFINING THE NEXT WAVE OF AUTONOMY
  • 3.2.1 AGENTIC AI VS. AI AGENTS: A CRITICAL DISTINCTION
  • 3.2.2 THE CORE DIFFERENTIATOR: AUTONOMY AND GOAL-ORIENTATION
• 3.3 CORE CHARACTERISTICS OF HIGH-AUTONOMY AGENTIC SYSTEMS
  • 3.3.1 DEFINING FEATURES
  • 3.3.2 OPERATIONAL LOOP AND PROACTIVE BEHAVIOR
  • 3.3.3 PROBABILISTIC AND ADAPTABLE DECISION-MAKING
  • 3.3.4 ADVANCED INTEGRATION AND TOOL USE
  • 3.3.5 LEVELS OF AI AUTONOMY: FRAMEWORK FOR STRATEGIC DESIGN
• 3.4 REDEFINING WORK AND ORGANIZATIONAL STRUCTURES
  • 3.4.1 SHIFTING HUMAN ROLES AND SKILL REQUIREMENTS
  • 3.4.2 ENHANCING PRODUCTIVITY AND INNOVATION CYCLES
  • 3.4.3 HUMAN-AI PARTNERSHIP PARADIGM
• 3.5 STRATEGIC IMPERATIVES FOR DECISION-MAKERS
• 3.6 VENDOR LANDSCAPE AND MARKET TRENDS

4 PREMIUM INSIGHTS

• 4.1 ATTRACTIVE OPPORTUNITIES IN AGENTIC AI MARKET
• 4.2 AGENTIC AI MARKET: TOP THREE HORIZONTAL USE CASES
• 4.3 NORTH AMERICA: AGENTIC AI MARKET, BY OFFERING AND HORIZONTAL USE CASE
• 4.4 AGENTIC AI MARKET, BY REGION

5 MARKET OVERVIEW AND INDUSTRY TRENDS

• 5.1 INTRODUCTION
• 5.2 MARKET DYNAMICS
  • 5.2.1 DRIVERS
    • 5.2.1.1 Increasing enterprise need for hyper-automation to streamline workflows end-to-end
    • 5.2.1.2 Breakthroughs in LLMs, memory, and orchestration frameworks enabling autonomous multi-step task execution
    • 5.2.1.3 Widespread access to high-performance computing and scalable AI deployment environments
    • 5.2.1.4 Growing integration of digital twins with agentic orchestration for real-world simulation
  • 5.2.2 RESTRAINTS
    • 5.2.2.1 Inconsistent standards for safe agent coordination across geographies
    • 5.2.2.2 Unclear ROI for some sectors where simpler automation suffices
  • 5.2.3 OPPORTUNITIES
    • 5.2.3.1 New orchestration engines for multiple autonomous agents working collaboratively
    • 5.2.3.2 Scaling autonomous agents across BFSI, telecom, and manufacturing for digital transformation
    • 5.2.3.3 Emerging AI regulations unlocking new markets for compliant autonomy
  • 5.2.4 CHALLENGES
    • 5.2.4.1 Fragmented autonomy stacks and missing interoperability standards restricting system integration
    • 5.2.4.2 Legal and ethical gaps around autonomous actions delaying adoption in regulated sectors
• 5.3 EVOLUTION OF AGENTIC AI
• 5.4 SUPPLY CHAIN ANALYSIS
• 5.5 ECOSYSTEM ANALYSIS
  • 5.5.1 AGENTIC AI FRAMEWORK PROVIDERS
  • 5.5.2 AGENTIC AI PLATFORM PROVIDERS
  • 5.5.3 AGENTIC AI SAAS PROVIDERS
  • 5.5.4 AGENTIC AI SERVICE PROVIDERS
• 5.6 STRATEGIC ROADMAP FOR ENTERPRISES
  • 5.6.1 ORGANIZATIONAL READINESS ASSESSMENT
  • 5.6.2 INTEGRATION STRATEGIES
  • 5.6.3 CHANGE MANAGEMENT AND TALENT STRATEGY
  • 5.6.4 GOVERNANCE AND CONTROL
  • 5.6.5 VENDOR AND PARTNER EVALUATION FRAMEWORK
  • 5.6.6 GO-TO-MARKET IMPLICATIONS
  • 5.6.7 SUCCESS METRICS AND ROI MEASUREMENT
• 5.7 FUTURE OUTLOOK
  • 5.7.1 EVOLUTION TOWARD SUPER-AGENTIC SYSTEMS
  • 5.7.2 LONG-TERM SOCIETAL AND WORKFORCE IMPACT
  • 5.7.3 POTENTIAL RISKS AND EXISTENTIAL CONCERNS
  • 5.7.4 SCENARIO PLANNING
  • 5.7.5 INVESTMENT AND INNOVATION OPPORTUNITIES
  • 5.7.6 NEXT FRONTIER RESEARCH AREAS
• 5.8 IMPACT OF 2025 US TARIFF - AGENTIC AI MARKET
  • 5.8.1 INTRODUCTION
  • 5.8.2 KEY TARIFF RATES
  • 5.8.3 PRICE IMPACT ANALYSIS
    • 5.8.3.1 Strategic shifts and emerging trends
  • 5.8.4 IMPACT ON COUNTRY/REGION
    • 5.8.4.1 US
    • 5.8.4.2 China
    • 5.8.4.3 Europe
    • 5.8.4.4 Asia Pacific (excluding China)
  • 5.8.5 IMPACT ON END-USE INDUSTRIES
    • 5.8.5.1 BFSI
    • 5.8.5.2 Telecommunications
    • 5.8.5.3 Government & public sector
    • 5.8.5.4 Healthcare & life sciences
    • 5.8.5.5 Manufacturing
    • 5.8.5.6 Media & entertainment
    • 5.8.5.7 Retail & e-commerce
    • 5.8.5.8 Software & technology providers
• 5.9 INVESTMENT AND FUNDING SCENARIO
• 5.10 CASE STUDY ANALYSIS
  • 5.10.1 CENCORA REALIZED 4X FASTER TURNAROUND THROUGH INFINITUS' VOISE AI AGENTS
  • 5.10.2 TEVA PHARMACEUTICALS DEPLOYS CONVERSATIONAL AI AGENT "MEDI" TO ENHANCE MEDICATION INFORMATION ACCESS AND SAFETY
  • 5.10.3 AISERA AND CITY AND COUNTY OF DENVER - AUTOMATING CITIZEN SERVICES WITH AGENTIC AI
  • 5.10.4 EZCATER ELEVATES COMPLEX CUSTOMER SERVICE OPERATIONS WITH LEVEL AI'S AUTONOMOUS AGENT SOLUTIONS
• 5.11 TECHNOLOGY ANALYSIS
  • 5.11.1 KEY TECHNOLOGIES
    • 5.11.1.1 Reinforcement learning (RL)
    • 5.11.1.2 Multi-agent systems (MAS)
    • 5.11.1.3 Continual learning
    • 5.11.1.4 Symbolic planning & decision-making
    • 5.11.1.5 Contextual memory & retrieval mechanisms
  • 5.11.2 COMPLEMENTARY TECHNOLOGIES
    • 5.11.2.1 Large language models (LLMs)
    • 5.11.2.2 Natural language understanding (NLU)
    • 5.11.2.3 Generative AI
    • 5.11.2.4 Computer vision
    • 5.11.2.5 Vector embedding & similarity search
  • 5.11.3 ADJACENT TECHNOLOGIES
    • 5.11.3.1 AIOps
    • 5.11.3.2 Computer Vision
    • 5.11.3.3 Explainable AI (XAI)
    • 5.11.3.4 Blockchain
    • 5.11.3.5 Natural Language Understanding (NLU)
• 5.12 REGULATORY LANDSCAPE
  • 5.12.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
  • 5.12.2 REGULATIONS
    • 5.12.2.1 North America
      • 5.12.2.1.1 SCR 17: Artificial Intelligence Bill (California)
      • 5.12.2.1.2 S1103: Artificial Intelligence Automated Decision Bill (Connecticut)
      • 5.12.2.1.3 National Artificial Intelligence Initiative Act (NAIIA) (US)
      • 5.12.2.1.4 Artificial Intelligence and Data Act (AIDA) (Canada)
    • 5.12.2.2 Europe
      • 5.12.2.2.1 European Union (EU) - Artificial Intelligence Act (AIA)
      • 5.12.2.2.2 General Data Protection Regulation (Europe)
    • 5.12.2.3 Asia Pacific
      • 5.12.2.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services (China)
      • 5.12.2.3.2 National AI Strategy (Singapore)
      • 5.12.2.3.3 Hiroshima AI Process Comprehensive Policy Framework (Japan)
    • 5.12.2.4 Middle East & Africa
      • 5.12.2.4.1 National Strategy for Artificial Intelligence (UAE)
      • 5.12.2.4.2 National Artificial Intelligence Strategy (Qatar)
      • 5.12.2.4.3 AI Ethics Principles and Guidelines (Dubai)
    • 5.12.2.5 Latin America
      • 5.12.2.5.1 Santiago Declaration (Chile)
      • 5.12.2.5.2 Brazilian Artificial Intelligence Strategy (EBIA)
• 5.13 PATENT ANALYSIS
  • 5.13.1 METHODOLOGY
  • 5.13.2 PATENTS FILED, BY DOCUMENT TYPE
  • 5.13.3 INNOVATION AND PATENT APPLICATIONS
• 5.14 PRICING ANALYSIS
  • 5.14.1 AVERAGE SELLING PRICE OF OFFERINGS, BY KEY PLAYER, 2025
  • 5.14.2 AVERAGE SELLING PRICE OF HORIZONTAL USE CASES, 2025
• 5.15 KEY CONFERENCES AND EVENTS, 2025-2026
• 5.16 PORTER'S FIVE FORCES ANALYSIS
  • 5.16.1 THREAT OF NEW ENTRANTS
  • 5.16.2 THREAT OF SUBSTITUTES
  • 5.16.3 BARGAINING POWER OF SUPPLIERS
  • 5.16.4 BARGAINING POWER OF BUYERS
  • 5.16.5 INTENSITY OF COMPETITIVE RIVALRY
• 5.17 KEY STAKEHOLDERS AND BUYING CRITERIA
  • 5.17.1 KEY STAKEHOLDERS IN BUYING PROCESS
  • 5.17.2 BUYING CRITERIA
• 5.18 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS

6 AGENTIC AI MARKET, BY OFFERING

• 6.1 INTRODUCTION
  • 6.1.1 DRIVERS: AGENTIC AI MARKET, BY OFFERING
• 6.2 AGENTIC AI INFRASTRUCTURE
  • 6.2.1 INNOVATIONS IN MEMORY-AUGMENTED AGENTS AND TASK-CHAINING ENABLE COMPLEX PERFORMANCE AND AUTONOMOUS FUNCTIONS
• 6.3 AGENTIC AI PLATFORMS
  • 6.3.1 TASK-CHAINING AND CONTEXTUAL MEMORY DRIVE NEW FRONTIERS FOR ENTERPRISE-GRADE AUTONOMY
• 6.4 AGENTIC AI SAAS
  • 6.4.1 AUTONOMOUS BEHAVIOR EMBEDDED IN SAAS UNLOCKS REAL-WORLD PROCESS OPTIMIZATION
• 6.5 AGENTIC AI SERVICES
  • 6.5.1 END-TO-END AGENTIC AI SERVICES ANCHOR ADOPTION AND TRUST IN AGENTIC DEPLOYMENTS

7 AGENTIC AI MARKET, BY HORIZONTAL USE CASE

• 7.1 INTRODUCTION
  • 7.1.1 DRIVERS: AGENTIC AI MARKET, BY HORIZONTAL USE CASE
• 7.2 FINANCE & ACCOUNTING
  • 7.2.1 AUTONOMOUS AGENTS RESHAPE COMPLEX FINANCE & ACCOUNTING WORKFLOWS
• 7.3 WORKPLACE EXPERIENCE
  • 7.3.1 ELEVATING EMPLOYEE EXPERIENCE THROUGH CONTEXT-AWARE AUTONOMOUS AGENTS
• 7.4 SALES
  • 7.4.1 AUTONOMOUS AGENTS UNLOCK ALWAYS-ON SALES INTELLIGENCE AND DEAL ACCELERATION
• 7.5 DATA ANALYTICS & BI
  • 7.5.1 AUTONOMOUS ORCHESTRATION AMPLIFIES DATA ANALYTICS AND BUSINESS INSIGHTS
• 7.6 MARKETING
  • 7.6.1 AGENTIC AI DRIVES PRECISION, PERSONALIZATION, AND CAMPAIGN AUTONOMY IN MARKETING
• 7.7 SECURITY OPS
  • 7.7.1 AUTONOMOUS AGENTS REINVENT THREAT DETECTION AND RESPONSE CYCLES IN SECURITY OPS
• 7.8 CUSTOMER EXPERIENCE
  • 7.8.1 ORCHESTRATED AGENTS ELEVATE CUSTOMER SERVICE WITH ADAPTIVE, PROACTIVE SUPPORT
• 7.9 DATA RETRIEVAL
  • 7.9.1 AGENTIC ORCHESTRATION TRANSFORMS ENTERPRISE DATA RETRIEVAL INTO CONTEXTUAL INTELLIGENCE
• 7.10 CODING & TESTING
  • 7.10.1 AUTONOMOUS AGENTS BOOST DEVELOPER VELOCITY AND SOFTWARE RELIABILITY
• 7.11 REGULATORY COMPLIANCE
  • 7.11.1 AGENTIC AI ELEVATES COMPLIANCE MONITORING AND CONTINUOUS RISK MITIGATION

8 AGENTIC AI MARKET, BY VERTICAL USE CASE

• 8.1 INTRODUCTION
  • 8.1.1 DRIVERS: AGENTIC AI MARKET, BY VERTICAL USE CASE
• 8.2 BFSI
  • 8.2.1 AGENTIC AI REVOLUTIONIZES CORE BANKING WORKFLOWS WITH ADAPTIVE RISK CONTROLS AND INTELLIGENT PROCESS AUTOMATION
  • 8.2.2 FRAUD DETECTION
  • 8.2.3 AUTOMATED CREDIT UNDERWRITING
  • 8.2.4 AUTONOMOUS CLAIMS PROCESSING
  • 8.2.5 PORTFOLIO RISK SIMULATION
  • 8.2.6 COMPLIANCE MONITORING
  • 8.2.7 OTHER BFSI VERTICAL USE CASES
• 8.3 RETAIL & E-COMMERCE
  • 8.3.1 AGENTIC AI POWERS INTELLIGENT MERCHANDISING, PRICING PRECISION, AND SEAMLESS OMNICHANNEL RETAIL OPERATIONS
  • 8.3.2 DYNAMIC PRICING OPTIMIZATION
  • 8.3.3 INTELLIGENT INVENTORY MANAGEMENT
  • 8.3.4 CHECKOUT FRAUD PREVENTION
  • 8.3.5 LAST-MILE ROUTE OPTIMIZATION
  • 8.3.6 PERSONALIZED MERCHANDISING LAYOUTS
  • 8.3.7 OTHER RETAIL & E-COMMERCE VERTICAL USE CASES
• 8.4 PROFESSIONAL SERVICES
  • 8.4.1 AGENTIC AI UNLOCKS SCALABLE EXPERTISE AND ENGAGEMENT INTELLIGENCE ACROSS HIGH-TOUCH PROFESSIONAL SERVICES
  • 8.4.2 CONTRACT REVIEW & LEGAL DRAFTING
  • 8.4.3 AUDIT WORKFLOW MANAGEMENT
  • 8.4.4 PROPOSAL & RFP GENERATION
  • 8.4.5 GENERATIVE DESIGN
  • 8.4.6 CAMPAIGN VARIANT GENERATION
  • 8.4.7 OTHER PROFESSIONAL SERVICE VERTICAL USE CASES
• 8.5 HEALTHCARE & LIFE SCIENCES
  • 8.5.1 AGENTIC AI ELEVATES PATIENT CARE AND CLINICAL EFFICIENCY THROUGH SELF-LEARNING DIAGNOSTIC AND WORKFLOW AGENTS
  • 8.5.2 CLINICAL TRIAL WORKFLOW OPTIMIZATION
  • 8.5.3 AI-POWERED DIAGNOSTIC IMAGING
  • 8.5.4 PERSONALIZED TREATMENT PLANNING
  • 8.5.5 HOSPITAL RESOURCE ORCHESTRATION
  • 8.5.6 AUTONOMOUS CLAIMS REVIEW
  • 8.5.7 OTHER HEALTHCARE & LIFE SCIENCES VERTICAL USE CASES
• 8.6 TELECOMMUNICATIONS
  • 8.6.1 AGENTIC AI ORCHESTRATES REAL-TIME TELECOM OPERATIONS, BILLING, FRAUD DETECTION, AND CUSTOMER EXPERIENCE AUTOMATION
  • 8.6.2 RAN CONFIGURATION OPTIMIZATION
  • 8.6.3 TELECOM FRAUD DETECTION
  • 8.6.4 PREDICTIVE NETWORK FAULT RESOLUTION
  • 8.6.5 DYNAMIC BANDWIDTH ALLOCATION
  • 8.6.6 AUTONOMOUS BILLING DISPUTE HANDLING
  • 8.6.7 OTHER TELECOMMUNICATIONS VERTICAL USE CASES
• 8.7 SOFTWARE & TECHNOLOGY PROVIDERS
  • 8.7.1 SOFTWARE & TECHNOLOGY PROVIDERS EMBED AGENTIC AI TO AUTOMATE PIPELINES, TEST APIS, AND OPTIMIZE CLOUD SPEND
  • 8.7.2 DEVOPS PIPELINE AUTOMATION
  • 8.7.3 INTELLIGENT FEATURE FLAG MANAGEMENT
  • 8.7.4 CONTINUOUS VULNERABILITY REMEDIATION
  • 8.7.5 AUTONOMOUS API BEHAVIOR TESTING
  • 8.7.6 CLOUD RESOURCE OPTIMIZATION
  • 8.7.7 OTHER SOFTWARE & TECHNOLOGY PROVIDERS VERTICAL USE CASES
• 8.8 MEDIA & ENTERTAINMENT
  • 8.8.1 MEDIA & ENTERTAINMENT FIRMS LEVERAGE AGENTIC AI FOR CONTENT GENERATION, CURATION, AND AUDIENCE ENGAGEMENT AT SCALE
  • 8.8.2 AUTOMATED CONTENT GENERATION
  • 8.8.3 INTELLIGENT CONTENT MODERATION
  • 8.8.4 CROSS-PLATFORM AUDIENCE PERSONALIZATION
  • 8.8.5 AI-ASSISTED PRODUCTION PLANNING
  • 8.8.6 LIVE EVENT ORCHESTRATION
  • 8.8.7 OTHER MEDIA & ENTERTAINMENT VERTICAL USE CASES
• 8.9 LOGISTICS & TRANSPORTATION
  • 8.9.1 AGENTIC AI REDEFINES LOGISTICS WITH AUTONOMOUS ORCHESTRATION AND REAL-TIME OPERATIONAL PRECISION
  • 8.9.2 REAL-TIME ROUTE OPTIMIZATION
  • 8.9.3 AUTONOMOUS WAREHOUSE COORDINATION
  • 8.9.4 DRONE FLEET MANAGEMENT
  • 8.9.5 INTELLIGENT LOGISTICS AUDITING
  • 8.9.6 MULTI-MODAL DELIVERY ORCHESTRATION
  • 8.9.7 OTHER LOGISTICS & TRANSPORTATION VERTICAL USE CASES
• 8.10 GOVERNMENT & DEFENSE
  • 8.10.1 GOVERNMENT & DEFENSE ELEVATING NATIONAL RESILIENCE THROUGH AGENTIC AI ORCHESTRATION
  • 8.10.2 PUBLIC SAFETY SURVEILLANCE
  • 8.10.3 AUTONOMOUS BORDER MONITORING
  • 8.10.4 DISASTER RESPONSE PLANNING
  • 8.10.5 URBAN MOBILITY COORDINATION
  • 8.10.6 PUBLIC INFRASTRUCTURE INCIDENT DETECTION
  • 8.10.7 OTHER GOVERNMENT & DEFENSE VERTICAL USE CASES
• 8.11 AUTOMOTIVE
  • 8.11.1 TRANSFORMING VEHICLE AUTONOMY AND IN-CABIN EXPERIENCES WITH INTELLIGENT AGENTIC ORCHESTRATION
  • 8.11.2 AUTONOMOUS VEHICLE NAVIGATION
  • 8.11.3 IN-VEHICLE DECISION SUPPORT
  • 8.11.4 DRIVER BEHAVIOR ADAPTATION
  • 8.11.5 PREDICTIVE IN-CABIN PERSONALIZATION
  • 8.11.6 SAFETY SYSTEM COORDINATION
  • 8.11.7 OTHER AUTOMOTIVE VERTICAL USE CASES
• 8.12 ENERGY & UTILITIES
  • 8.12.1 ORCHESTRATING INTELLIGENT GRIDS AND ENERGY ASSETS THROUGH AGENTIC AI COORDINATION
  • 8.12.2 DECENTRALIZED GRID OPTIMIZATION
  • 8.12.3 SMART GRID MANAGEMENT
  • 8.12.4 DEMAND RESPONSE MANAGEMENT
  • 8.12.5 PIPELINE LEAK DETECTION
  • 8.12.6 AUTONOMOUS ENERGY ASSET COORDINATION
  • 8.12.7 OTHER ENERGY & UTILITIES VERTICAL USE CASES
• 8.13 MANUFACTURING
  • 8.13.1 AGENTIC AI REWIRES MODERN MANUFACTURING FOR AUTONOMOUS RESILIENCE AND ADAPTIVE PRODUCTIVITY
  • 8.13.2 SMART FACTORY OPERATIONS
  • 8.13.3 PREDICTIVE MAINTENANCE SCHEDULING
  • 8.13.4 SUPPLY CHAIN OPTIMIZATION
  • 8.13.5 AUTOMATED QUALITY INSPECTION
  • 8.13.6 WORKPLACE SAFETY MONITORING
  • 8.13.7 OTHER MANUFACTURING VERTICAL USE CASES

9 AGENTIC AI MARKET, BY END USER

• 9.1 INTRODUCTION
  • 9.1.1 DRIVERS: AGENTIC AI MARKET, BY END USER
• 9.2 INDIVIDUAL USERS
• 9.3 ENTERPRISES
  • 9.3.1 BFSI
    • 9.3.1.1 Autonomous agents increasingly being embedded in personalized financial recommendations and automate claims processing
  • 9.3.2 RETAIL & E-COMMERCE
    • 9.3.2.1 Agentic AI drives always-on personalization, dynamic inventory, and adaptive customer engagement at scale
  • 9.3.3 PROFESSIONAL SERVICE PROVIDERS
    • 9.3.3.1 Rising demand for faster, cost-efficient expert services pushing agentic AI adoption across professional service firms
  • 9.3.4 HEALTHCARE & LIFE SCIENCES
    • 9.3.4.1 Agentic AI enables real-time clinical decision support and autonomous patient journey management end-to-end
  • 9.3.5 TELECOMMUNICATIONS
    • 9.3.5.1 Agentic AI streamlines network operations and personalizes user services for hyperconnected digital environments
  • 9.3.6 TECHNOLOGY & SOFTWARE PROVIDERS
    • 9.3.6.1 Agentic AI fuels next-gen software development, automated testing, and continuous product innovation cycles
  • 9.3.7 MEDIA & ENTERTAINMENT
    • 9.3.7.1 Agentic AI powers hyper-personalized content creation and real-time audience engagement experiences
  • 9.3.8 TRANSPORTATION & LOGISTICS
    • 9.3.8.1 Agentic AI orchestrates supply chain flows and autonomous fleet operations in real-time
  • 9.3.9 GOVERNMENT & DEFENSE
    • 9.3.9.1 Agentic AI enhances autonomous decision-making for critical defense, public safety, and citizen services
  • 9.3.10 AUTOMOTIVE
    • 9.3.10.1 Agentic AI integrates autonomous driving, predictive maintenance, and driver experience in next-gen vehicles
  • 9.3.11 ENERGY & UTILITIES
    • 9.3.11.1 Agentic AI optimizes distributed energy grids and autonomous demand response at scale
  • 9.3.12 MANUFACTURING
    • 9.3.12.1 Agentic AI automates factory floor coordination, predictive quality control, and adaptive production planning
  • 9.3.13 OTHER ENTERPRISES

10 AGENTIC AI MARKET, BY REGION

• 10.1 INTRODUCTION
• 10.2 NORTH AMERICA
  • 10.2.1 NORTH AMERICA: AGENTIC AI MARKET DRIVERS
  • 10.2.2 NORTH AMERICA: MACROECONOMIC OUTLOOK
  • 10.2.3 US
  • 10.2.4 CANADA
• 10.3 EUROPE
  • 10.3.1 EUROPE: AGENTIC AI MARKET DRIVERS
  • 10.3.2 EUROPE: MACROECONOMIC OUTLOOK
  • 10.3.3 UK
  • 10.3.4 GERMANY
  • 10.3.5 FRANCE
  • 10.3.6 ITALY
  • 10.3.7 SPAIN
  • 10.3.8 NETHERLANDS
  • 10.3.9 REST OF EUROPE
• 10.4 ASIA PACIFIC
  • 10.4.1 ASIA PACIFIC: AGENTIC AI MARKET DRIVERS
  • 10.4.2 ASIA PACIFIC: MACROECONOMIC OUTLOOK
  • 10.4.3 CHINA
  • 10.4.4 INDIA
  • 10.4.5 JAPAN
  • 10.4.6 SOUTH KOREA
  • 10.4.7 SINGAPORE
  • 10.4.8 AUSTRALIA & NEW ZEALAND
  • 10.4.9 REST OF ASIA PACIFIC
• 10.5 MIDDLE EAST & AFRICA
  • 10.5.1 MIDDLE EAST & AFRICA: AGENTIC AI MARKET DRIVERS
  • 10.5.2 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
  • 10.5.3 SAUDI ARABIA
  • 10.5.4 UAE
  • 10.5.5 QATAR
  • 10.5.6 TURKEY
  • 10.5.7 REST OF MIDDLE EAST
  • 10.5.8 SOUTH AFRICA
• 10.6 LATIN AMERICA
  • 10.6.1 LATIN AMERICA: AGENTIC AI MARKET DRIVERS
  • 10.6.2 LATIN AMERICA: MACROECONOMIC OUTLOOK
  • 10.6.3 BRAZIL
  • 10.6.4 MEXICO
  • 10.6.5 ARGENTINA
  • 10.6.6 REST OF LATIN AMERICA

11 COMPETITIVE LANDSCAPE

• 11.1 OVERVIEW
• 11.2 KEY PLAYERS' STRATEGIES, 2022 - 2025
• 11.3 REVENUE ANALYSIS, 2022 - 2024
• 11.4 MARKET SHARE ANALYSIS, 2024
  • 11.4.1 MARKET RANKING ANALYSIS, 2024
• 11.5 PRODUCT COMPARATIVE ANALYSIS
  • 11.5.1 PRODUCT COMPARATIVE ANALYSIS: AGENTIC AI INFRASTRUCTURE PROVIDERS
  • 11.5.2 PRODUCT COMPARATIVE ANALYSIS: AGENTIC AI PLATFORM PROVIDERS
  • 11.5.3 PRODUCT COMPARATIVE ANALYSIS: AGENTIC AI SAAS PROVIDERS
• 11.6 COMPANY VALUATION AND FINANCIAL METRICS OF KEY VENDORS
• 11.7 COMPANY EVALUATION MATRIX: KEY PLAYERS (AGENTIC AI INFRASTRUCTURE VENDORS)
  • 11.7.1 STARS
  • 11.7.2 EMERGING LEADERS
  • 11.7.3 PERVASIVE PLAYERS
  • 11.7.4 PARTICIPANTS
  • 11.7.5 COMPANY FOOTPRINT: KEY PLAYERS (AGENTIC AI INFRASTRUCTURE)
    • 11.7.5.1 Overall Company Footprint
    • 11.7.5.2 Offering Footprint
    • 11.7.5.3 Region Footprint
    • 11.7.5.4 Horizontal Use Case Footprint
    • 11.7.5.5 End User Footprint
• 11.8 COMPANY EVALUATION MATRIX: KEY PLAYERS (AGENTIC AI PLATFORM VENDORS)
  • 11.8.1 STARS
  • 11.8.2 EMERGING LEADERS
  • 11.8.3 PERVASIVE PLAYERS
  • 11.8.4 PARTICIPANTS
  • 11.8.5 COMPANY FOOTPRINT: KEY PLAYERS (AGENTIC AI PLATFORMS)
    • 11.8.5.1 Overall Company Footprint
    • 11.8.5.2 Offering Footprint
    • 11.8.5.3 Region Footprint
    • 11.8.5.4 Horizontal Use Case Footprint
    • 11.8.5.5 End User Footprint
• 11.9 COMPANY EVALUATION MATRIX: KEY PLAYERS (AGENTIC AI SAAS VENDORS)
  • 11.9.1 STARS
  • 11.9.2 EMERGING LEADERS
  • 11.9.3 PERVASIVE PLAYERS
  • 11.9.4 PARTICIPANTS
  • 11.9.5 COMPANY FOOTPRINT: KEY PLAYERS (AGENTIC AI SAAS)
    • 11.9.5.1 Overall Company Footprint
    • 11.9.5.2 Offering Footprint
    • 11.9.5.3 Region Footprint
    • 11.9.5.4 Horizontal Use Case Footprint
    • 11.9.5.5 End User Footprint
• 11.10 COMPANY EVALUATION MATRIX: KEY PLAYERS (AGENTIC AI SERVICE PROVIDERS)
  • 11.10.1 STARS
  • 11.10.2 EMERGING LEADERS
  • 11.10.3 PERVASIVE PLAYERS
  • 11.10.4 PARTICIPANTS
  • 11.10.5 COMPANY FOOTPRINT: KEY PLAYERS (AGENTIC AI SERVICES)
    • 11.10.5.1 Overall Company Footprint
    • 11.10.5.2 Offering Footprint
    • 11.10.5.3 Region Footprint
    • 11.10.5.4 Horizontal Use Case Footprint
    • 11.10.5.5 End User Footprint
• 11.11 COMPETITIVE SCENARIO
  • 11.11.1 PRODUCT LAUNCHES & ENHANCEMENTS
  • 11.11.2 DEALS

12 COMPANY PROFILES

• 12.1 INTRODUCTION
• 12.2 AI INFRASTRUCTURE/FRAMEWORK PROVIDERS
  • 12.2.1 MICROSOFT
    • 12.2.1.1 Business overview
    • 12.2.1.2 Products/Solutions/Services offered
    • 12.2.1.3 Recent developments
      • 12.2.1.3.1 Product launches and enhancements
      • 12.2.1.3.2 Deals
    • 12.2.1.4 MnM view
      • 12.2.1.4.1 Key strengths
      • 12.2.1.4.2 Strategic choices
      • 12.2.1.4.3 Weaknesses and competitive threats
  • 12.2.2 NVIDIA
    • 12.2.2.1 Business overview
    • 12.2.2.2 Products/Solutions/Services offered
    • 12.2.2.3 Recent developments
      • 12.2.2.3.1 Product launches and enhancements
      • 12.2.2.3.2 Deals
  • 12.2.3 GOOGLE
    • 12.2.3.1 Business overview
    • 12.2.3.2 Products/Solutions/Services offered
    • 12.2.3.3 Recent developments
      • 12.2.3.3.1 Product launches and enhancements
      • 12.2.3.3.2 Deals
    • 12.2.3.4 MnM view
      • 12.2.3.4.1 Key strengths
      • 12.2.3.4.2 Strategic choices
      • 12.2.3.4.3 Weaknesses and competitive threats
  • 12.2.4 AWS
  • 12.2.5 AMD
• 12.3 AGENTIC AI PLATFORM PROVIDERS
  • 12.3.1 OPENAI
    • 12.3.1.1 Business overview
    • 12.3.1.2 Products/Solutions/Services offered
    • 12.3.1.3 Recent developments
      • 12.3.1.3.1 Product launches and enhancements
      • 12.3.1.3.2 Deals
  • 12.3.2 UIPATH
  • 12.3.3 SNOWFLAKE
  • 12.3.4 AISERA
  • 12.3.5 APPIAN
  • 12.3.6 NEWGEN
  • 12.3.7 AMDOCS
  • 12.3.8 HEXAWARE
  • 12.3.9 ADEPT AI
  • 12.3.10 RELEVANCE AI
• 12.4 AGENTIC AI SERVICE PROVIDERS
  • 12.4.1 ACCENTURE
    • 12.4.1.1 Business overview
    • 12.4.1.2 Products/Solutions/Services offered
    • 12.4.1.3 Recent developments
      • 12.4.1.3.1 Product launches and enhancements
      • 12.4.1.3.2 Deals
    • 12.4.1.4 MnM view
      • 12.4.1.4.1 Key strengths
      • 12.4.1.4.2 Strategic choices
      • 12.4.1.4.3 Weaknesses and competitive threats
  • 12.4.2 COGNIZANT
    • 12.4.2.1 Business overview
    • 12.4.2.2 Products/Solutions/Services offered
    • 12.4.2.3 Recent developments
      • 12.4.2.3.1 Product launches and enhancements
      • 12.4.2.3.2 Deals
  • 12.4.3 NTT DATA
  • 12.4.4 DELOITTE
  • 12.4.5 EY
  • 12.4.6 WIPRO
  • 12.4.7 CAPGEMINI
    • 12.4.7.1 Business overview
    • 12.4.7.2 Products/Solutions/Services offered
    • 12.4.7.3 Recent developments
      • 12.4.7.3.1 Deals
  • 12.4.8 HCL TECH
  • 12.4.9 TCS
  • 12.4.10 PWC
  • 12.4.11 DATAMATICS
• 12.5 AGENTIC AI SAAS PROVIDERS
  • 12.5.1 SAP
    • 12.5.1.1 Business overview
    • 12.5.1.2 Products/Solutions/Services offered
    • 12.5.1.3 Recent developments
      • 12.5.1.3.1 Product launches and enhancements
      • 12.5.1.3.2 Deals
    • 12.5.1.4 MnM view
      • 12.5.1.4.1 Key strengths
      • 12.5.1.4.2 Strategic choices
      • 12.5.1.4.3 Weaknesses and competitive threats
  • 12.5.2 IBM
    • 12.5.2.1 Business overview
    • 12.5.2.2 Products/Solutions/Services offered
    • 12.5.2.3 Recent developments
      • 12.5.2.3.1 Product launches and enhancements
      • 12.5.2.3.2 Deals
    • 12.5.2.4 MnM view
      • 12.5.2.4.1 Key strengths
      • 12.5.2.4.2 Strategic choices
      • 12.5.2.4.3 Weaknesses and competitive threats
  • 12.5.3 SALESFORCE
    • 12.5.3.1 Business overview
    • 12.5.3.2 Products/Solutions/Services offered
    • 12.5.3.3 Recent developments
      • 12.5.3.3.1 Product launches and enhancements
  • 12.5.4 SERVICENOW
  • 12.5.5 CISCO
  • 12.5.6 ALTAIR
  • 12.5.7 PEGA
  • 12.5.8 CYBERARK
  • 12.5.9 ZYCUS
  • 12.5.10 ORACLE
  • 12.5.11 SAS INSTITUTE
  • 12.5.12 AVANADE
  • 12.5.13 ERICSSON
  • 12.5.14 VALUELABS
  • 12.5.15 REWIND AI
  • 12.5.16 EMA
  • 12.5.17 ORBY AI
  • 12.5.18 EXA
  • 12.5.19 ARTISAN AI
  • 12.5.20 DEXA AI
  • 12.5.21 SIMULAR

13 ADJACENT AND RELATED MARKETS

• 13.1 INTRODUCTION
• 13.2 AI AGENTS MARKET - GLOBAL FORECAST TO 2030
  • 13.2.1 MARKET DEFINITION
  • 13.2.2 MARKET OVERVIEW
    • 13.2.2.1 AI agents market, by offering
    • 13.2.2.2 AI agents market, by agent system
    • 13.2.2.3 AI agents market, by product type
    • 13.2.2.4 AI agents market, by agent role
    • 13.2.2.5 AI agents market, by end user
    • 13.2.2.6 AI agents market, by region
• 13.3 ARTIFICIAL INTELLIGENCE MARKET - GLOBAL FORECAST TO 2032
  • 13.3.1 MARKET DEFINITION
  • 13.3.2 MARKET OVERVIEW
    • 13.3.2.1 Artificial intelligence (AI) market, by offering
    • 13.3.2.2 Artificial intelligence (AI) market, by technology
    • 13.3.2.3 Artificial intelligence (AI) market, by business function
    • 13.3.2.4 Artificial intelligence (AI) market, by enterprise application
    • 13.3.2.5 Artificial intelligence (AI) market, by end user
    • 13.3.2.6 Artificial intelligence (AI) market, by region

14 APPENDIX

• 14.1 DISCUSSION GUIDE
• 14.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
• 14.3 CUSTOMIZATION OPTIONS
• 14.4 RELATED REPORTS
• 14.5 AUTHOR DETAILS