에이전틱 커머스 시장 규모, 점유율 및 업계 분석 보고서 : 인터랙션 모델별, 기술별, 용도별, 지역별 전망 및 예측(2026-2033년)

The Global Agentic Commerce Market is expected to reach USD 60.0 billion by 2033, growing at a CAGR of 33.9% during (2026 - 2033).

The agentic commerce market is driven by rising adoption of autonomous AI agents across digital payments, online shopping, procurement, customer service, customized commerce applications. Demand is also surging as businesses focus on faster transactions, automated decision-making, secure AI-enabled payments customized product recommendations, and improved customer engagement. The market evolved from the convergence of AI advancements and digital retail innovation. Natural language processing, machine learning, smart payment systems, and generative AI enabled AI agents to decide, understand, and act more independently.

Key Market Trends & Insights

• By interaction model, Consumer-to-Agent (C2A) dominated the market in 2025 with USD 3.1 billion and is expected to reach USD 30.6 billion by 2033, growing at a CAGR of 33.4%.
• Business-to-Agent (B2A) and Agent-to-Agent (A2A) are expected to grow faster by interaction model, each registering a CAGR of 34.4% during (2026 - 2033), supported by enterprise automation and autonomous agent collaboration.
• By technology, Generative AI & Large Language Models (LLMs) dominated the market in 2025 with USD 2.8 billion and is expected to reach USD 27.1 billion by 2033, growing at a CAGR of 33.2%.
• On-Device AI is expected to grow fastest by technology, registering a CAGR of 34.9% during (2026 - 2033), supported by privacy-focused processing, low-latency decisions, and edge-based commerce interactions.
• By application, Retail & E-commerce dominated the market in 2025 with USD 2.2 billion and is expected to reach USD 21.3 billion by 2033, growing at a CAGR of 33.0%.
• Customer Support & Engagement is expected to grow fastest by application, registering a CAGR of 35.4% during (2026 - 2033), supported by conversational AI, automated query resolution, and proactive customer interaction.
• Regionally, North America dominated the market in 2025 with USD 2.3 billion and is projected to reach USD 22.2 billion by 2033, growing at a CAGR of 33.3%.
• LAMEA is expected to grow fastest by region, registering a CAGR of 35.5% during (2026 - 2033), supported by improving digital infrastructure, fintech adoption, expanding online retail platforms, and rising AI-enabled commerce adoption.

Global market is rising as businesses witness transformation from passive recommendation engines toward proactive AI agents with capabilities of managing end-to-end commerce workflows. These systems enhance transaction efficiency, speed, personalization, and customer engagement across payments, retail, travel, customer support, and procurement. The adoption of interoperable platforms, secure AI agents, smart payment infrastructure, and real-time data analytics is supporting the market expansion.

Competitive environment is segmented and platform-driven, driven by consumer AI assistants, e-commerce marketplaces, cloud providers, specialized transaction infrastructure companies, and enterprise commerce platforms, and payment networks. Market participants compete through agent reliability, payment security, AI autonomy, merchant ecosystem access, compliance capabilities, checkout integration, user experience, and compliance capabilities. Moreover, the market competition is predicted to depend on complete agent-driven journeys from product discovery to post-purchase support.

Drivers

• Autonomous Operational Efficiency and Workflow Optimization
• Trust-Driven Adoption and Regulatory Enablement
• Data Maturity and Strategic Competitive Advantage
• Acceleration of Digital Transformation and Strategic Innovation

Restraints

• Regulatory Uncertainty and Legal Framework Challenges
• High Integration and Operational Costs
• Insufficient Standardization and Interoperability

Opportunities

• Autonomous Personalization Engines Driving Hyper-Targeted Commerce Experiences
• Integrated Autonomous Deal Facilitation Platforms Enhancing Transaction Efficiency
• Agentic AI-Enabled Supply Chain Orchestration for Responsive Commerce Networks

Challenges

• Data Privacy and Security Vulnerabilities in Agentic Commerce
• Interoperability and Integration Complexities
• Cost Barriers Related to Development and Maintenance

Market Share Analysis

Agentic commerce market represents a moderately consolidated, rapidly evolving, and platform-driven competitive landscape led by AI assistant providers, e-commerce marketplaces, payment infrastructure companies, cloud platforms, and enterprise commerce vendors. Microsoft, OpenAI, Amazon, and Alphabet form the leading competitive market through product discovery interfaces, consumer-facing AI assistants, and agentic transaction capabilities. Salesforce, Stripe, Shopify, Mastercard, Visa, and commerce tools further support market competition through checkout infrastructure, merchant enablement, commerce orchestration, tokenization, payment authentication and enterprise-grade agent connectivity.

Interaction Model Outlook

Based on Interaction Model, the market is segmented into Consumer-to-Agent (C2A), Business-to-Agent (B2A), and Agent-to-Agent (A2A). The Consumer-to-Agent (C2A) market dominated the Global Agentic Commerce Market by Interaction Model in 2025, and would continue to be a dominant market till 2033; thereby, achieving a market value of USD 30.6 billion by 2033, growing at a CAGR of 33.4 % during the forecast period. The Business-to-Agent (B2A) market is expected to witness a CAGR of 34.4% during (2026 - 2033). The Agent-to-Agent (A2A) market is expected to witness a CAGR of 34.4% during (2026 - 2033).

Business-to-Agent is gaining adoption as enterprises deploy agentic AI for procurement automation, customer engagement, supplier management, workflow optimization, and operational decision support. Agent-to-Agent remains an emerging model where autonomous agents communicate, negotiate, validate information, and execute transactions across commerce ecosystems. Together, these interaction models show how agentic commerce is moving from consumer assistance toward broader autonomous commercial coordination.

Technology Outlook

Based on Technology, the market is segmented into Generative AI & Large Language Models (LLMs), Multi-Agent Systems, On-Device AI, and Blockchain & Smart Contracts. The Generative AI & Large Language Models (LLMs) market dominated the Global Agentic Commerce Market by Technology in 2025, and would continue to be a dominant market till 2033; thereby, achieving a market value of USD 27.1 billion by 2033, growing at a CAGR of 33.2 % during the forecast period. The Multi-Agent Systems market is expected to witness a CAGR of 34.2% during (2026 - 2033). Additionally, The On-Device AI market is expected to witness highest CAGR of 34.9% during (2026 - 2033).

Multi-Agent Systems support coordinated decision-making where multiple autonomous agents work together across procurement, supply chain, pricing, and transaction workflows. On-Device AI supports low-latency processing, privacy-focused decision-making, and edge-based personalization. Blockchain & Smart Contracts provide secure, transparent, and automated transaction execution, especially where trust, auditability, identity validation, and decentralized commerce workflows are important.

Application Outlook

Based on Application, the market is segmented into Retail & E-commerce, Financial Services & Payments, Travel & Hospitality, Enterprise Procurement (B2B), and Customer Support & Engagement. The Retail & E-commerce market dominated the Global Agentic Commerce Market by Application in 2025, and would continue to be a dominant market till 2033; thereby, achieving a market value of USD 21.3 billion by 2033, growing at a CAGR of 33 % during the forecast period. The Financial Services & Payments market is expected to witness a CAGR of 33.6% during (2026 - 2033). Additionally, The Travel & Hospitality market is expected to witness highest CAGR of 34.5% during (2026 - 2033).

Financial Services & Payments are gaining traction as agentic systems support secure transaction execution, payment automation, fraud detection, and real-time risk assessment. Travel & Hospitality uses AI agents for itinerary planning, booking assistance, dynamic pricing, and customer service. Enterprise Procurement benefits from autonomous sourcing, supplier interaction, contract management, and purchasing optimization. Customer Support & Engagement continues growing through conversational AI, virtual assistants, automated query resolution, and proactive customer interaction.

Regional Outlook

Region-wise, the Agentic Commerce Market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The agentic commerce market held the largest share in North America region in 2025, and is predicted to remain dominant during the forecast period with a market value of USD 22.2 billion by 2033, rising at a CAGR of 33.3%. Further, Europe market is projected to grow at a CAGR of 33.7%. Also, Asia Pacific is expected to witness a CAGR of 34.6%.

Europe region is driven by responsible AI frameworks, digital transformation, secure payment infrastructure, online retail growth, and enterprise automation. Asia Pacific region is gaining traction through fintech adoption, e-commerce expansion, smart automation, mobile commerce, and increasing investment in AI-powered consumer applications. LAMEA is developing largely through rising fintech ecosystems, enhancing digital infrastructure, increasing awareness of AI-enabled commerce solutions, and expanding online retail platforms.

Recent Strategies Deployed in the Market

• 2026-May: SAP announced its intent to acquire Dremio in Germany and the United States to strengthen SAP Business Data Cloud and enhance enterprise agentic AI capabilities for governed, real-time business data access.
• 2025-March: Salesforce launched AgentExchange Marketplace in the United States to enable partners, developers, and enterprises to build, distribute, and deploy reusable AI agents and agentic components.
• 2025-January: Google Cloud launched new retail solutions for the agentic AI era in the United States, including AI-powered retail agents, conversational commerce, commerce search, and catalog enrichment capabilities.
• 2025-April: Microsoft expanded Microsoft 365 Copilot with enterprise AI agent capabilities in the United States, supporting automated business processes, organizational data reasoning, and natural-language task execution.
• 2025-May: Shopify expanded its AI commerce platform in Canada with Sidekick, AI Store Builder, Horizon customization, and Shopify Catalog to support AI-powered merchant operations and product discovery.
• 2025-February: OpenAI introduced Cristal intelligence in Japan with SoftBank Group to deliver enterprise AI agents capable of automating knowledge work, customer engagement, and operational workflows.
• 2025-May: SAP expanded Joule Agents and its Business AI platform in the United States to support autonomous workflows across procurement, finance, supply chain, customer experience, and enterprise operations.
• 2025-April: Visa launched Visa Intelligent Commerce in the United States to enable AI agents to securely discover, select, and purchase products using tokenization, authentication, and trusted payment APIs.
• 2025-May: Shopify expanded its AI shopping agent ecosystem through Perplexity integration in Canada and the United States, enabling AI-powered product discovery using Shopify Catalog.
• 2025-January: Google Cloud expanded its partnership with Wayfair in the United States to improve AI-powered shopping experiences, product catalog management, customer support, and personalized product discovery.

List of Key Companies Profiled

• Amazon.com, Inc.
• Microsoft Corporation
• Google LLC
• OpenAI, L.L.C.
• Shopify Inc.
• Salesforce, Inc.
• Visa Inc.
• SAP SE
• Stripe, Inc.
• Adobe Inc.

Global Agentic Commerce Market Report Segmentation

By Interaction Model

• Consumer-to-Agent (C2A)
• Business-to-Agent (B2A)
• Agent-to-Agent (A2A)

By Technology

• Generative AI & Large Language Models (LLMs)
• Multi-Agent Systems
• On-Device AI
• Blockchain & Smart Contracts

By Application

• Retail & E-commerce
• Financial Services & Payments
• Travel & Hospitality
• Enterprise Procurement (B2B)
• Customer Support & Engagement

By Geography

• North America
  • US
  • Canada
  • Mexico
  • Rest of North America
• Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
• LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Table of Contents

Chapter 1. Research Scope & Methodology

• 1.1 Market Definition
• 1.2 Analysis Period & Currency
• 1.3 Segmentation
• 1.4 Agentic Commerce Market, by Geography
• 1.5 Research Methodology

Chapter 2. Market Overview

• 2.1 COVID-19 Impact
• 2.2 Market Composition and Scenario

Chapter 3. Key Factors Impacting Market

• 3.1 Market Drivers
• 3.2 Market Restraints
• 3.3 Market Opportunities
• 3.4 Market Challenges
• 3.5 Market Trends
• 3.6 State of Competition
• 3.7 Market Consolidation
• 3.8 Key Customer Criteria

Chapter 4. Product Life Cycle

Chapter 5. Value Chain Analysis of Agentic Commerce Market

Chapter 6. Competition Analysis - Global

• 6.1 Market Share Analysis
• 6.2 Recent Developments
  • 6.2.1 Mergers & Acquisitions
  • 6.2.2 Product Launch & Product Expansion
  • 6.2.3 Partnership, Collaboration & Agreements
  • 6.2.4 Geographical Expansion

Chapter 7. Segmentation By Interaction Model

• 7.1 Consumer-to-Agent (C2A)
• 7.2 Business-to-Agent (B2A)
• 7.3 Agent-to-Agent (A2A)

Chapter 8. Segmentation By Technology

• 8.1 Generative AI & Large Language Models (LLMs)
• 8.2 Multi-Agent Systems
• 8.3 On-Device AI
• 8.4 Blockchain & Smart Contracts

Chapter 9. Segmentation By Application

• 9.1 Retail & E-commerce
• 9.2 Financial Services & Payments
• 9.3 Travel & Hospitality
• 9.4 Enterprise Procurement (B2B)
• 9.5 Customer Support & Engagement

Chapter 10. North America Market

• 10.1 Market Overview
• 10.2 Key Factors Impacting Market
  • 10.2.1 Market Drivers
  • 10.2.2 Market Restraints
  • 10.2.3 Market Opportunities
  • 10.2.4 Market Challenges
  • 10.2.5 Market Trends
  • 10.2.6 State of Competition
  • 10.2.7 Market Consolidation
  • 10.2.8 Key Customer Criteria
• 10.3 Product Life Cycle
• 10.4 Segmentation By Interaction Model
  • 10.4.1 Consumer-to-Agent (C2A)
  • 10.4.2 Business-to-Agent (B2A)
  • 10.4.3 Agent-to-Agent (A2A)
• 10.5 Segmentation By Technology
  • 10.5.1 Generative AI & Large Language Models (LLMs)
  • 10.5.2 Multi-Agent Systems
  • 10.5.3 On-Device AI
  • 10.5.4 Blockchain & Smart Contracts
• 10.6 Segmentation By Application
  • 10.6.1 Retail & E-commerce
  • 10.6.2 Financial Services & Payments
  • 10.6.3 Travel & Hospitality
  • 10.6.4 Enterprise Procurement (B2B)
  • 10.6.5 Customer Support & Engagement
• 10.7 Segmentation By Country
  • 10.7.1 US
    • 10.7.1.1 Segmentation By Interaction Model
      • 10.7.1.1.1 Consumer-to-Agent (C2A)
      • 10.7.1.1.2 Business-to-Agent (B2A)
      • 10.7.1.1.3 Agent-to-Agent (A2A)
    • 10.7.1.2 Segmentation By Technology
      • 10.7.1.2.1 Generative AI & Large Language Models (LLMs)
      • 10.7.1.2.2 Multi-Agent Systems
      • 10.7.1.2.3 On-Device AI
      • 10.7.1.2.4 Blockchain & Smart Contracts
    • 10.7.1.3 Segmentation By Application
      • 10.7.1.3.1 Retail & E-commerce
      • 10.7.1.3.2 Financial Services & Payments
      • 10.7.1.3.3 Travel & Hospitality
      • 10.7.1.3.4 Enterprise Procurement (B2B)
      • 10.7.1.3.5 Customer Support & Engagement
  • 10.7.2 Canada
    • 10.7.2.1 Segmentation By Interaction Model
      • 10.7.2.1.1 Consumer-to-Agent (C2A)
      • 10.7.2.1.2 Business-to-Agent (B2A)
      • 10.7.2.1.3 Agent-to-Agent (A2A)
    • 10.7.2.2 Segmentation By Technology
      • 10.7.2.2.1 Generative AI & Large Language Models (LLMs)
      • 10.7.2.2.2 Multi-Agent Systems
      • 10.7.2.2.3 On-Device AI
      • 10.7.2.2.4 Blockchain & Smart Contracts
    • 10.7.2.3 Segmentation By Application
      • 10.7.2.3.1 Retail & E-commerce
      • 10.7.2.3.2 Financial Services & Payments
      • 10.7.2.3.3 Travel & Hospitality
      • 10.7.2.3.4 Enterprise Procurement (B2B)
      • 10.7.2.3.5 Customer Support & Engagement
  • 10.7.3 Mexico
    • 10.7.3.1 Segmentation By Interaction Model
      • 10.7.3.1.1 Consumer-to-Agent (C2A)
      • 10.7.3.1.2 Business-to-Agent (B2A)
      • 10.7.3.1.3 Agent-to-Agent (A2A)
    • 10.7.3.2 Segmentation By Technology
      • 10.7.3.2.1 Generative AI & Large Language Models (LLMs)
      • 10.7.3.2.2 Multi-Agent Systems
      • 10.7.3.2.3 On-Device AI
      • 10.7.3.2.4 Blockchain & Smart Contracts
    • 10.7.3.3 Segmentation By Application
      • 10.7.3.3.1 Retail & E-commerce
      • 10.7.3.3.2 Financial Services & Payments
      • 10.7.3.3.3 Travel & Hospitality
      • 10.7.3.3.4 Enterprise Procurement (B2B)
      • 10.7.3.3.5 Customer Support & Engagement
  • 10.7.4 Rest of North America
    • 10.7.4.1 Segmentation By Interaction Model
      • 10.7.4.1.1 Consumer-to-Agent (C2A)
      • 10.7.4.1.2 Business-to-Agent (B2A)
      • 10.7.4.1.3 Agent-to-Agent (A2A)
    • 10.7.4.2 Segmentation By Technology
      • 10.7.4.2.1 Generative AI & Large Language Models (LLMs)
      • 10.7.4.2.2 Multi-Agent Systems
      • 10.7.4.2.3 On-Device AI
      • 10.7.4.2.4 Blockchain & Smart Contracts
    • 10.7.4.3 Segmentation By Application
      • 10.7.4.3.1 Retail & E-commerce
      • 10.7.4.3.2 Financial Services & Payments
      • 10.7.4.3.3 Travel & Hospitality
      • 10.7.4.3.4 Enterprise Procurement (B2B)
      • 10.7.4.3.5 Customer Support & Engagement

Chapter 11. Europe Market

• 11.1 Market Overview
• 11.2 Key Factors Impacting Market
  • 11.2.1 Market Drivers
  • 11.2.2 Market Restraints
  • 11.2.3 Market Opportunities
  • 11.2.4 Market Challenges
  • 11.2.5 Market Trends
  • 11.2.6 State of Competition
  • 11.2.7 Market Consolidation
  • 11.2.8 Key Customer Criteria
• 11.3 Product Life Cycle
• 11.4 Segmentation By Interaction Model
  • 11.4.1 Consumer-to-Agent (C2A)
  • 11.4.2 Business-to-Agent (B2A)
  • 11.4.3 Agent-to-Agent (A2A)
• 11.5 Segmentation By Technology
  • 11.5.1 Generative AI & Large Language Models (LLMs)
  • 11.5.2 Multi-Agent Systems
  • 11.5.3 On-Device AI
  • 11.5.4 Blockchain & Smart Contracts
• 11.6 Segmentation By Application
  • 11.6.1 Retail & E-commerce
  • 11.6.2 Financial Services & Payments
  • 11.6.3 Travel & Hospitality
  • 11.6.4 Enterprise Procurement (B2B)
  • 11.6.5 Customer Support & Engagement
• 11.7 Segmentation By Country
  • 11.7.1 Germany
    • 11.7.1.1 Segmentation By Interaction Model
      • 11.7.1.1.1 Consumer-to-Agent (C2A)
      • 11.7.1.1.2 Business-to-Agent (B2A)
      • 11.7.1.1.3 Agent-to-Agent (A2A)
    • 11.7.1.2 Segmentation By Technology
      • 11.7.1.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.1.2.2 Multi-Agent Systems
      • 11.7.1.2.3 On-Device AI
      • 11.7.1.2.4 Blockchain & Smart Contracts
    • 11.7.1.3 Segmentation By Application
      • 11.7.1.3.1 Retail & E-commerce
      • 11.7.1.3.2 Financial Services & Payments
      • 11.7.1.3.3 Travel & Hospitality
      • 11.7.1.3.4 Enterprise Procurement (B2B)
      • 11.7.1.3.5 Customer Support & Engagement
  • 11.7.2 UK
    • 11.7.2.1 Segmentation By Interaction Model
      • 11.7.2.1.1 Consumer-to-Agent (C2A)
      • 11.7.2.1.2 Business-to-Agent (B2A)
      • 11.7.2.1.3 Agent-to-Agent (A2A)
    • 11.7.2.2 Segmentation By Technology
      • 11.7.2.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.2.2.2 Multi-Agent Systems
      • 11.7.2.2.3 On-Device AI
      • 11.7.2.2.4 Blockchain & Smart Contracts
    • 11.7.2.3 Segmentation By Application
      • 11.7.2.3.1 Retail & E-commerce
      • 11.7.2.3.2 Financial Services & Payments
      • 11.7.2.3.3 Travel & Hospitality
      • 11.7.2.3.4 Enterprise Procurement (B2B)
      • 11.7.2.3.5 Customer Support & Engagement
  • 11.7.3 France
    • 11.7.3.1 Segmentation By Interaction Model
      • 11.7.3.1.1 Consumer-to-Agent (C2A)
      • 11.7.3.1.2 Business-to-Agent (B2A)
      • 11.7.3.1.3 Agent-to-Agent (A2A)
    • 11.7.3.2 Segmentation By Technology
      • 11.7.3.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.3.2.2 Multi-Agent Systems
      • 11.7.3.2.3 On-Device AI
      • 11.7.3.2.4 Blockchain & Smart Contracts
    • 11.7.3.3 Segmentation By Application
      • 11.7.3.3.1 Retail & E-commerce
      • 11.7.3.3.2 Financial Services & Payments
      • 11.7.3.3.3 Travel & Hospitality
      • 11.7.3.3.4 Enterprise Procurement (B2B)
      • 11.7.3.3.5 Customer Support & Engagement
  • 11.7.4 Russia
    • 11.7.4.1 Segmentation By Interaction Model
      • 11.7.4.1.1 Consumer-to-Agent (C2A)
      • 11.7.4.1.2 Business-to-Agent (B2A)
      • 11.7.4.1.3 Agent-to-Agent (A2A)
    • 11.7.4.2 Segmentation By Technology
      • 11.7.4.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.4.2.2 Multi-Agent Systems
      • 11.7.4.2.3 On-Device AI
      • 11.7.4.2.4 Blockchain & Smart Contracts
    • 11.7.4.3 Segmentation By Application
      • 11.7.4.3.1 Retail & E-commerce
      • 11.7.4.3.2 Financial Services & Payments
      • 11.7.4.3.3 Travel & Hospitality
      • 11.7.4.3.4 Enterprise Procurement (B2B)
      • 11.7.4.3.5 Customer Support & Engagement
  • 11.7.5 Spain
    • 11.7.5.1 Segmentation By Interaction Model
      • 11.7.5.1.1 Consumer-to-Agent (C2A)
      • 11.7.5.1.2 Business-to-Agent (B2A)
      • 11.7.5.1.3 Agent-to-Agent (A2A)
    • 11.7.5.2 Segmentation By Technology
      • 11.7.5.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.5.2.2 Multi-Agent Systems
      • 11.7.5.2.3 On-Device AI
      • 11.7.5.2.4 Blockchain & Smart Contracts
    • 11.7.5.3 Segmentation By Application
      • 11.7.5.3.1 Retail & E-commerce
      • 11.7.5.3.2 Financial Services & Payments
      • 11.7.5.3.3 Travel & Hospitality
      • 11.7.5.3.4 Enterprise Procurement (B2B)
      • 11.7.5.3.5 Customer Support & Engagement
  • 11.7.6 Italy
    • 11.7.6.1 Segmentation By Interaction Model
      • 11.7.6.1.1 Consumer-to-Agent (C2A)
      • 11.7.6.1.2 Business-to-Agent (B2A)
      • 11.7.6.1.3 Agent-to-Agent (A2A)
    • 11.7.6.2 Segmentation By Technology
      • 11.7.6.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.6.2.2 Multi-Agent Systems
      • 11.7.6.2.3 On-Device AI
      • 11.7.6.2.4 Blockchain & Smart Contracts
    • 11.7.6.3 Segmentation By Application
      • 11.7.6.3.1 Retail & E-commerce
      • 11.7.6.3.2 Financial Services & Payments
      • 11.7.6.3.3 Travel & Hospitality
      • 11.7.6.3.4 Enterprise Procurement (B2B)
      • 11.7.6.3.5 Customer Support & Engagement
  • 11.7.7 Rest of Europe
    • 11.7.7.1 Segmentation By Interaction Model
      • 11.7.7.1.1 Consumer-to-Agent (C2A)
      • 11.7.7.1.2 Business-to-Agent (B2A)
      • 11.7.7.1.3 Agent-to-Agent (A2A)
    • 11.7.7.2 Segmentation By Technology
      • 11.7.7.2.1 Generative AI & Large Language Models (LLMs)
      • 11.7.7.2.2 Multi-Agent Systems
      • 11.7.7.2.3 On-Device AI
      • 11.7.7.2.4 Blockchain & Smart Contracts
    • 11.7.7.3 Segmentation By Application
      • 11.7.7.3.1 Retail & E-commerce
      • 11.7.7.3.2 Financial Services & Payments
      • 11.7.7.3.3 Travel & Hospitality
      • 11.7.7.3.4 Enterprise Procurement (B2B)
      • 11.7.7.3.5 Customer Support & Engagement

Chapter 12. Asia Pacific Market

• 12.1 Market Overview
• 12.2 Key Factors Impacting Market
  • 12.2.1 Market Drivers
  • 12.2.2 Market Restraints
  • 12.2.3 Market Opportunities
  • 12.2.4 Market Challenges
  • 12.2.5 Market Trends
  • 12.2.6 State of Competition
  • 12.2.7 Market Consolidation
  • 12.2.8 Key Customer Criteria
• 12.3 Product Life Cycle
• 12.4 Segmentation By Interaction Model
  • 12.4.1 Consumer-to-Agent (C2A)
  • 12.4.2 Business-to-Agent (B2A)
  • 12.4.3 Agent-to-Agent (A2A)
• 12.5 Segmentation By Technology
  • 12.5.1 Generative AI & Large Language Models (LLMs)
  • 12.5.2 Multi-Agent Systems
  • 12.5.3 On-Device AI
  • 12.5.4 Blockchain & Smart Contracts
• 12.6 Segmentation By Application
  • 12.6.1 Retail & E-commerce
  • 12.6.2 Financial Services & Payments
  • 12.6.3 Travel & Hospitality
  • 12.6.4 Enterprise Procurement (B2B)
  • 12.6.5 Customer Support & Engagement
• 12.7 Segmentation By Country
  • 12.7.1 China
    • 12.7.1.1 Segmentation By Interaction Model
      • 12.7.1.1.1 Consumer-to-Agent (C2A)
      • 12.7.1.1.2 Business-to-Agent (B2A)
      • 12.7.1.1.3 Agent-to-Agent (A2A)
    • 12.7.1.2 Segmentation By Technology
      • 12.7.1.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.1.2.2 Multi-Agent Systems
      • 12.7.1.2.3 On-Device AI
      • 12.7.1.2.4 Blockchain & Smart Contracts
    • 12.7.1.3 Segmentation By Application
      • 12.7.1.3.1 Retail & E-commerce
      • 12.7.1.3.2 Financial Services & Payments
      • 12.7.1.3.3 Travel & Hospitality
      • 12.7.1.3.4 Enterprise Procurement (B2B)
      • 12.7.1.3.5 Customer Support & Engagement
  • 12.7.2 Japan
    • 12.7.2.1 Segmentation By Interaction Model
      • 12.7.2.1.1 Consumer-to-Agent (C2A)
      • 12.7.2.1.2 Business-to-Agent (B2A)
      • 12.7.2.1.3 Agent-to-Agent (A2A)
    • 12.7.2.2 Segmentation By Technology
      • 12.7.2.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.2.2.2 Multi-Agent Systems
      • 12.7.2.2.3 On-Device AI
      • 12.7.2.2.4 Blockchain & Smart Contracts
    • 12.7.2.3 Segmentation By Application
      • 12.7.2.3.1 Retail & E-commerce
      • 12.7.2.3.2 Financial Services & Payments
      • 12.7.2.3.3 Travel & Hospitality
      • 12.7.2.3.4 Enterprise Procurement (B2B)
      • 12.7.2.3.5 Customer Support & Engagement
  • 12.7.3 India
    • 12.7.3.1 Segmentation By Interaction Model
      • 12.7.3.1.1 Consumer-to-Agent (C2A)
      • 12.7.3.1.2 Business-to-Agent (B2A)
      • 12.7.3.1.3 Agent-to-Agent (A2A)
    • 12.7.3.2 Segmentation By Technology
      • 12.7.3.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.3.2.2 Multi-Agent Systems
      • 12.7.3.2.3 On-Device AI
      • 12.7.3.2.4 Blockchain & Smart Contracts
    • 12.7.3.3 Segmentation By Application
      • 12.7.3.3.1 Retail & E-commerce
      • 12.7.3.3.2 Financial Services & Payments
      • 12.7.3.3.3 Travel & Hospitality
      • 12.7.3.3.4 Enterprise Procurement (B2B)
      • 12.7.3.3.5 Customer Support & Engagement
  • 12.7.4 South Korea
    • 12.7.4.1 Segmentation By Interaction Model
      • 12.7.4.1.1 Consumer-to-Agent (C2A)
      • 12.7.4.1.2 Business-to-Agent (B2A)
      • 12.7.4.1.3 Agent-to-Agent (A2A)
    • 12.7.4.2 Segmentation By Technology
      • 12.7.4.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.4.2.2 Multi-Agent Systems
      • 12.7.4.2.3 On-Device AI
      • 12.7.4.2.4 Blockchain & Smart Contracts
    • 12.7.4.3 Segmentation By Application
      • 12.7.4.3.1 Retail & E-commerce
      • 12.7.4.3.2 Financial Services & Payments
      • 12.7.4.3.3 Travel & Hospitality
      • 12.7.4.3.4 Enterprise Procurement (B2B)
      • 12.7.4.3.5 Customer Support & Engagement
  • 12.7.5 Singapore
    • 12.7.5.1 Segmentation By Interaction Model
      • 12.7.5.1.1 Consumer-to-Agent (C2A)
      • 12.7.5.1.2 Business-to-Agent (B2A)
      • 12.7.5.1.3 Agent-to-Agent (A2A)
    • 12.7.5.2 Segmentation By Technology
      • 12.7.5.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.5.2.2 Multi-Agent Systems
      • 12.7.5.2.3 On-Device AI
      • 12.7.5.2.4 Blockchain & Smart Contracts
    • 12.7.5.3 Segmentation By Application
      • 12.7.5.3.1 Retail & E-commerce
      • 12.7.5.3.2 Financial Services & Payments
      • 12.7.5.3.3 Travel & Hospitality
      • 12.7.5.3.4 Enterprise Procurement (B2B)
      • 12.7.5.3.5 Customer Support & Engagement
  • 12.7.6 Malaysia
    • 12.7.6.1 Segmentation By Interaction Model
      • 12.7.6.1.1 Consumer-to-Agent (C2A)
      • 12.7.6.1.2 Business-to-Agent (B2A)
      • 12.7.6.1.3 Agent-to-Agent (A2A)
    • 12.7.6.2 Segmentation By Technology
      • 12.7.6.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.6.2.2 Multi-Agent Systems
      • 12.7.6.2.3 On-Device AI
      • 12.7.6.2.4 Blockchain & Smart Contracts
    • 12.7.6.3 Segmentation By Application
      • 12.7.6.3.1 Retail & E-commerce
      • 12.7.6.3.2 Financial Services & Payments
      • 12.7.6.3.3 Travel & Hospitality
      • 12.7.6.3.4 Enterprise Procurement (B2B)
      • 12.7.6.3.5 Customer Support & Engagement
  • 12.7.7 Rest of Asia Pacific
    • 12.7.7.1 Segmentation By Interaction Model
      • 12.7.7.1.1 Consumer-to-Agent (C2A)
      • 12.7.7.1.2 Business-to-Agent (B2A)
      • 12.7.7.1.3 Agent-to-Agent (A2A)
    • 12.7.7.2 Segmentation By Technology
      • 12.7.7.2.1 Generative AI & Large Language Models (LLMs)
      • 12.7.7.2.2 Multi-Agent Systems
      • 12.7.7.2.3 On-Device AI
      • 12.7.7.2.4 Blockchain & Smart Contracts
    • 12.7.7.3 Segmentation By Application
      • 12.7.7.3.1 Retail & E-commerce
      • 12.7.7.3.2 Financial Services & Payments
      • 12.7.7.3.3 Travel & Hospitality
      • 12.7.7.3.4 Enterprise Procurement (B2B)
      • 12.7.7.3.5 Customer Support & Engagement

Chapter 13. LAMEA Market

• 13.1 Market Overview
• 13.2 Key Factors Impacting Market
  • 13.2.1 Market Drivers
  • 13.2.2 Market Restraints
  • 13.2.3 Market Opportunities
  • 13.2.4 Market Challenges
  • 13.2.5 Market Trends
  • 13.2.6 State of Competition
  • 13.2.7 Market Consolidation
  • 13.2.8 Key Customer Criteria
• 13.3 Product Life Cycle
• 13.4 Segmentation By Interaction Model
  • 13.4.1 Consumer-to-Agent (C2A)
  • 13.4.2 Business-to-Agent (B2A)
  • 13.4.3 Agent-to-Agent (A2A)
• 13.5 Segmentation By Technology
  • 13.5.1 Generative AI & Large Language Models (LLMs)
  • 13.5.2 Multi-Agent Systems
  • 13.5.3 On-Device AI
  • 13.5.4 Blockchain & Smart Contracts
• 13.6 Segmentation By Application
  • 13.6.1 Retail & E-commerce
  • 13.6.2 Financial Services & Payments
  • 13.6.3 Travel & Hospitality
  • 13.6.4 Enterprise Procurement (B2B)
  • 13.6.5 Customer Support & Engagement
• 13.7 Segmentation By Country
  • 13.7.1 Brazil
    • 13.7.1.1 Segmentation By Interaction Model
      • 13.7.1.1.1 Consumer-to-Agent (C2A)
      • 13.7.1.1.2 Business-to-Agent (B2A)
      • 13.7.1.1.3 Agent-to-Agent (A2A)
    • 13.7.1.2 Segmentation By Technology
      • 13.7.1.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.1.2.2 Multi-Agent Systems
      • 13.7.1.2.3 On-Device AI
      • 13.7.1.2.4 Blockchain & Smart Contracts
    • 13.7.1.3 Segmentation By Application
      • 13.7.1.3.1 Retail & E-commerce
      • 13.7.1.3.2 Financial Services & Payments
      • 13.7.1.3.3 Travel & Hospitality
      • 13.7.1.3.4 Enterprise Procurement (B2B)
      • 13.7.1.3.5 Customer Support & Engagement
  • 13.7.2 Argentina
    • 13.7.2.1 Segmentation By Interaction Model
      • 13.7.2.1.1 Consumer-to-Agent (C2A)
      • 13.7.2.1.2 Business-to-Agent (B2A)
      • 13.7.2.1.3 Agent-to-Agent (A2A)
    • 13.7.2.2 Segmentation By Technology
      • 13.7.2.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.2.2.2 Multi-Agent Systems
      • 13.7.2.2.3 On-Device AI
      • 13.7.2.2.4 Blockchain & Smart Contracts
    • 13.7.2.3 Segmentation By Application
      • 13.7.2.3.1 Retail & E-commerce
      • 13.7.2.3.2 Financial Services & Payments
      • 13.7.2.3.3 Travel & Hospitality
      • 13.7.2.3.4 Enterprise Procurement (B2B)
      • 13.7.2.3.5 Customer Support & Engagement
  • 13.7.3 UAE
    • 13.7.3.1 Segmentation By Interaction Model
      • 13.7.3.1.1 Consumer-to-Agent (C2A)
      • 13.7.3.1.2 Business-to-Agent (B2A)
      • 13.7.3.1.3 Agent-to-Agent (A2A)
    • 13.7.3.2 Segmentation By Technology
      • 13.7.3.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.3.2.2 Multi-Agent Systems
      • 13.7.3.2.3 On-Device AI
      • 13.7.3.2.4 Blockchain & Smart Contracts
    • 13.7.3.3 Segmentation By Application
      • 13.7.3.3.1 Retail & E-commerce
      • 13.7.3.3.2 Financial Services & Payments
      • 13.7.3.3.3 Travel & Hospitality
      • 13.7.3.3.4 Enterprise Procurement (B2B)
      • 13.7.3.3.5 Customer Support & Engagement
  • 13.7.4 Saudi Arabia
    • 13.7.4.1 Segmentation By Interaction Model
      • 13.7.4.1.1 Consumer-to-Agent (C2A)
      • 13.7.4.1.2 Business-to-Agent (B2A)
      • 13.7.4.1.3 Agent-to-Agent (A2A)
    • 13.7.4.2 Segmentation By Technology
      • 13.7.4.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.4.2.2 Multi-Agent Systems
      • 13.7.4.2.3 On-Device AI
      • 13.7.4.2.4 Blockchain & Smart Contracts
    • 13.7.4.3 Segmentation By Application
      • 13.7.4.3.1 Retail & E-commerce
      • 13.7.4.3.2 Financial Services & Payments
      • 13.7.4.3.3 Travel & Hospitality
      • 13.7.4.3.4 Enterprise Procurement (B2B)
      • 13.7.4.3.5 Customer Support & Engagement
  • 13.7.5 South Africa
    • 13.7.5.1 Segmentation By Interaction Model
      • 13.7.5.1.1 Consumer-to-Agent (C2A)
      • 13.7.5.1.2 Business-to-Agent (B2A)
      • 13.7.5.1.3 Agent-to-Agent (A2A)
    • 13.7.5.2 Segmentation By Technology
      • 13.7.5.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.5.2.2 Multi-Agent Systems
      • 13.7.5.2.3 On-Device AI
      • 13.7.5.2.4 Blockchain & Smart Contracts
    • 13.7.5.3 Segmentation By Application
      • 13.7.5.3.1 Retail & E-commerce
      • 13.7.5.3.2 Financial Services & Payments
      • 13.7.5.3.3 Travel & Hospitality
      • 13.7.5.3.4 Enterprise Procurement (B2B)
      • 13.7.5.3.5 Customer Support & Engagement
  • 13.7.6 Nigeria
    • 13.7.6.1 Segmentation By Interaction Model
      • 13.7.6.1.1 Consumer-to-Agent (C2A)
      • 13.7.6.1.2 Business-to-Agent (B2A)
      • 13.7.6.1.3 Agent-to-Agent (A2A)
    • 13.7.6.2 Segmentation By Technology
      • 13.7.6.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.6.2.2 Multi-Agent Systems
      • 13.7.6.2.3 On-Device AI
      • 13.7.6.2.4 Blockchain & Smart Contracts
    • 13.7.6.3 Segmentation By Application
      • 13.7.6.3.1 Retail & E-commerce
      • 13.7.6.3.2 Financial Services & Payments
      • 13.7.6.3.3 Travel & Hospitality
      • 13.7.6.3.4 Enterprise Procurement (B2B)
      • 13.7.6.3.5 Customer Support & Engagement
  • 13.7.7 Rest of LAMEA
    • 13.7.7.1 Segmentation By Interaction Model
      • 13.7.7.1.1 Consumer-to-Agent (C2A)
      • 13.7.7.1.2 Business-to-Agent (B2A)
      • 13.7.7.1.3 Agent-to-Agent (A2A)
    • 13.7.7.2 Segmentation By Technology
      • 13.7.7.2.1 Generative AI & Large Language Models (LLMs)
      • 13.7.7.2.2 Multi-Agent Systems
      • 13.7.7.2.3 On-Device AI
      • 13.7.7.2.4 Blockchain & Smart Contracts
    • 13.7.7.3 Segmentation By Application
      • 13.7.7.3.1 Retail & E-commerce
      • 13.7.7.3.2 Financial Services & Payments
      • 13.7.7.3.3 Travel & Hospitality
      • 13.7.7.3.4 Enterprise Procurement (B2B)
      • 13.7.7.3.5 Customer Support & Engagement

Chapter 14. Company Snapshots

• 14.1 Salesforce, Inc.
  • 14.1.1 Business Overview
  • 14.1.2 Key Information
  • 14.1.3 Company Focus on Agentic Commerce Market
  • 14.1.4 Strategic Insights
  • 14.1.5 Strategy Deployed
  • 14.1.6 Product & Service Portfolio
  • 14.1.7 Capability Overview
  • 14.1.8 Technology & Innovation Focus
  • 14.1.9 SWOT Analysis
  • 14.1.10 Customers / End Users
  • 14.1.11 Competitive Positioning
  • 14.1.12 Key Differentiators
  • 14.1.13 Portfolio Matrix
  • 14.1.14 Analyst View
  • 14.1.15 Future Outlook
• 14.2 Google LLC
  • 14.2.1 Business Overview
  • 14.2.2 Key Information
  • 14.2.3 Company Focus on Agentic Commerce Market
  • 14.2.4 Strategic Insights
  • 14.2.5 Strategy Deployed
  • 14.2.6 Product & Service Portfolio
  • 14.2.7 Capability Overview
  • 14.2.8 Technology & Innovation Focus
  • 14.2.9 SWOT Analysis
  • 14.2.10 Customers / End Users
  • 14.2.11 Competitive Positioning
  • 14.2.12 Key Differentiators
  • 14.2.13 Portfolio Matrix
  • 14.2.14 Analyst View
  • 14.2.15 Future Outlook
• 14.3 Microsoft Corporation
  • 14.3.1 Business Overview
  • 14.3.2 Key Information
  • 14.3.3 Company Focus on Agentic Commerce Market
  • 14.3.4 Strategic Insights
  • 14.3.5 Strategy Deployed
  • 14.3.6 Product & Service Portfolio
  • 14.3.7 Capability Overview
  • 14.3.8 Technology & Innovation Focus
  • 14.3.9 SWOT Analysis
  • 14.3.10 Customers / End Users
  • 14.3.11 Competitive Positioning
  • 14.3.12 Key Differentiators
  • 14.3.13 Portfolio Matrix
  • 14.3.14 Analyst View
  • 14.3.15 Future Outlook
• 14.4 Amazon Web Services, Inc.
  • 14.4.1 Business Overview
  • 14.4.2 Key Information
  • 14.4.3 Company Focus on Agentic Commerce Market
  • 14.4.4 Strategic Insights
  • 14.4.5 Strategy Deployed
  • 14.4.6 Product & Service Portfolio
  • 14.4.7 Capability Overview
  • 14.4.8 Technology & Innovation Focus
  • 14.4.9 SWOT Analysis
  • 14.4.10 Customers / End Users
  • 14.4.11 Competitive Positioning
  • 14.4.12 Key Differentiators
  • 14.4.13 Portfolio Matrix
  • 14.4.14 Future Outlook
• 14.5 Shopify Inc.
  • 14.5.1 Business Overview
  • 14.5.2 Key Information
  • 14.5.3 Company Focus on Agentic Commerce Market
  • 14.5.4 Strategic Insights on Agentic Commerce Market
  • 14.5.5 Strategy Deployed
  • 14.5.6 Product & Service Portfolio
  • 14.5.7 Capability Overview
  • 14.5.8 Technology & Innovation Focus
  • 14.5.9 SWOT Analysis
  • 14.5.10 Customers / End Users
  • 14.5.11 Competitive Positioning
  • 14.5.12 Key Differentiators
  • 14.5.13 Portfolio Matrix
  • 14.5.14 Analyst View
  • 14.5.15 Future Outlook
• 14.6 Adobe Inc.
  • 14.6.1 Business Overview
  • 14.6.2 Key Information
  • 14.6.3 Company Focus on Agentic Commerce Market
  • 14.6.4 Strategic Insights
  • 14.6.5 Strategy Deployed
  • 14.6.6 Product & Service Portfolio
  • 14.6.7 Capability Overview
  • 14.6.8 Technology & Innovation Focus
  • 14.6.9 SWOT Analysis
  • 14.6.10 Customers / End Users
  • 14.6.11 Competitive Positioning
  • 14.6.12 Key Differentiators
  • 14.6.13 Portfolio Matrix
  • 14.6.14 Analyst View
  • 14.6.15 Future Outlook
• 14.7 Stripe, Inc.
  • 14.7.1 Business Overview
  • 14.7.2 Key Information
  • 14.7.3 Company Focus on Agentic Commerce Market
  • 14.7.4 Strategic Insights
  • 14.7.5 Strategy Deployed
  • 14.7.6 Product & Service Portfolio
  • 14.7.7 Capability Overview
  • 14.7.8 Technology & Innovation Focus
  • 14.7.9 SWOT Analysis
  • 14.7.10 Customers / End Users
  • 14.7.11 Competitive Positioning
  • 14.7.12 Key Differentiators
  • 14.7.13 Portfolio Matrix
  • 14.7.14 Analyst View
  • 14.7.15 Future Outlook
• 14.8 OpenAI, L.L.C.
  • 14.8.1 Business Overview
  • 14.8.2 Key Information
  • 14.8.3 Company Focus
  • 14.8.4 Strategic Insights
  • 14.8.5 Strategy Deployed
  • 14.8.6 Product & Service Portfolio
  • 14.8.7 Capability Overview
  • 14.8.8 Technology & Innovation Focus
  • 14.8.9 SWOT Analysis
  • 14.8.10 Customers / End Users
  • 14.8.11 Competitive Positioning
  • 14.8.12 Key Differentiators
  • 14.8.13 Portfolio Matrix
  • 14.8.14 Analyst View
  • 14.8.15 Future Outlook
• 14.9 SAP SE
  • 14.9.1 Business Overview
  • 14.9.2 Key Information
  • 14.9.3 Company Focus on Agentic Commerce Market
  • 14.9.4 Strategic Insights
  • 14.9.5 Strategy Deployed
  • 14.9.6 Product & Service Portfolio
  • 14.9.7 Capability Overview
  • 14.9.8 Technology & Innovation Focus
  • 14.9.9 SWOT Analysis
  • 14.9.10 Customers / End Users
  • 14.9.11 Competitive Positioning
  • 14.9.12 Key Differentiators
  • 14.9.13 Portfolio Matrix
  • 14.9.14 Analyst View
  • 14.9.15 Future Outlook
• 14.10 Visa Inc.
  • 14.10.1 Business Overview
  • 14.10.2 Key Information
  • 14.10.3 Company Focus on Agentic Commerce Market
  • 14.10.4 Strategic Insights
  • 14.10.5 Strategy Deployed
  • 14.10.6 Product & Service Portfolio
  • 14.10.7 Capability Overview
  • 14.10.8 Technology & Innovation Focus
  • 14.10.9 SWOT Analysis
  • 14.10.10 Customers / End Users
  • 14.10.11 Competitive Positioning
  • 14.10.12 Key Differentiators
  • 14.10.13 Portfolio Matrix
  • 14.10.14 Analyst View
  • 14.10.15 Future Outlook

Chapter 15. Winning Imperatives