Agentic AI Market - 2026-2033
Description
GLOBAL AGENTIC AI MARKET OVERVIEW
Global Agentic AI market was valued at US$ 4.54 billion in 2025 and is expected to reach US$ 98.26 billion by 2033, growing at a CAGR of 46.87% during the forecast period 2026–2033. The market is experiencing strong momentum as enterprises increasingly shift toward autonomous, goal-driven AI systems to manage complex workflows and decision-making processes.
Rapid advancements in large language models, agent orchestration frameworks, and RAG-enabled architectures are accelerating adoption across industries. Organizations are deploying agentic AI to improve operational efficiency, reduce manual intervention, and enable real-time intelligence. Growing emphasis on scalable automation and adaptive systems is further strengthening demand. Integration of agentic AI with enterprise software platforms is expanding use cases across IT, BFSI, healthcare, and manufacturing.
AGENTIC AI INDUSTRY TRENDS AND STRATEGIC INSIGHTS
• Asia-Pacific is the fastest growing region in the agentic AI market, capturing the share of 25.41% in 2025.
• By component, the software platforms is projected to be the largest market, holding a significant share of about 19.22% in 2025.
GLOBAL AGENTIC AI MARKET SIZE AND FUTURE OUTLOOK
• 2025 Market Size: US$ 4.54 Billion
• 2033 Projected Market Size: US$ 98.26 Billion
• CAGR (2026-2033): 46.87%
• Largest Market: North America
• Fastest Market: Asia-Pacific
For more detailed information, Request for Free sample (https://www.datamintelligence.com/download-sample/agentic-ai-market)
MARKET SCOPE
Metrics Details
By Component Software Platforms, AI Models & Frameworks, Agent Orchestration Engines, Tool Integration Layers, Services. Others
By Agent Type Single-Agent Systems, Multi-Agent Systems Autonomous Agents, Semi-Autonomous Agents, Collaborative Agents, Others
By Deployment Mode Cloud-Based, On-Premise, Hybrid
By Organization Size Large Enterprises, Small & Medium Enterprises (SMEs)
By Application IT & Telecommunications, BFSI (Banking, Financial Services & Insurance), Healthcare & Life Sciences, Retail & E-commerce, Manufacturing, Logistics & Transportation, Energy & Utilities, Media & Entertainment, Others
By Region North America, South America, Europe, Asia-Pacific, Middle East and Africa
Report Insights Covered Competitive Landscape Analysis, Company Profile Analysis, Market Size, Share, Growth
MARKET DYNAMICS
REAL-TIME KNOWLEDGE INTEGRATION ACCELERATING AGENTIC AI ADOPTION
Outdated and inaccurate information remains a critical challenge for enterprises, directly impacting compliance, decision quality, and operational efficiency. In 2025, the integration of AI agents with Retrieval Augmented Generation (RAG) is emerging as a key market driver by enabling access to real-time, verified data sources.
RAG-powered agents combine the reasoning capabilities of large language models with dynamic retrieval from regulatory databases, enterprise repositories, and external knowledge systems. For instance, compliance assistant agents can automatically pull the latest regulatory updates, interpret changes, and assess potential exposure across business operations.
This significantly reduces manual research effort while improving accuracy and consistency in compliance workflows. By grounding agent decisions in up-to-date information, enterprises can mitigate regulatory risks and avoid costly errors. Faster, data-backed decision-making also enhances audit readiness and governance outcomes. As trust, transparency, and accountability become essential for autonomous systems, RAG-integrated AI agents are accelerating enterprise adoption and driving overall market growth.
GROWTH OF AGENTIC AI MARKETPLACES AND PARTNER ECOSYSTEMS
The growth of agentic AI marketplaces and partner ecosystems is acting as a strong catalyst for overall market expansion by lowering entry barriers for enterprises. Much like the early evolution of mobile app stores, the emerging agent economy allows organizations to access ready-made AI agents instead of building solutions from scratch. Enterprises can now purchase, customize, and deploy pre-built agents tailored to specific business functions and workflows.
Platforms such as Hugging Face Agents and Microsoft Copilot Studio are leading this shift by offering plug-and-play agent solutions. These ecosystems enable faster deployment cycles and significantly reduce development complexity. The availability of partner-built agents also encourages innovation and specialization across industries. For small and mid-sized businesses, marketplaces make agentic AI more affordable and accessible. As ecosystem participation grows, network effects are accelerating adoption and driving sustained market growth.
SEGMENTATION ANALYSIS
The global agentic AI market is segmented based on component, agent type, deployment mode, organization size, application and region.
SOFTWARE PLATFORMS AS THE FOUNDATION OF AGENTIC AI MARKET EXPANSION
The software platforms segment plays a pivotal role in driving the growth of the Agentic AI market by serving as the core layer that enables agent development, deployment, and orchestration. These platforms provide end-to-end environments for building autonomous and multi-agent systems without requiring deep AI engineering expertise. Integrated capabilities such as agent memory, tool management, and workflow orchestration accelerate enterprise adoption.
Software platforms also support seamless integration with enterprise applications, APIs, and data sources, expanding real-world use cases. Built-in governance, monitoring, and security features increase trust in agent-driven operations. By reducing development time and operational complexity, platforms lower total cost of ownership for organizations. This scalability makes agentic AI viable across both large enterprises and SMEs. As enterprises prioritize speed, flexibility, and control, software platforms continue to act as a primary engine of market growth.
CLOUD-BASED DEPLOYMENT ACCELERATING SCALABLE ADOPTION OF AGENTIC AI
The cloud-based deployment segment is a major driver of growth in the Agentic AI market by enabling scalable, flexible, and cost-efficient adoption of autonomous AI systems. Cloud platforms allow enterprises to deploy and manage AI agents without heavy upfront infrastructure investments. On-demand compute and storage support the intensive processing requirements of large language models and multi-agent workflows.
Cloud environments also enable rapid experimentation, continuous updates, and real-time performance optimization of agents. Seamless integration with cloud-native data sources and enterprise SaaS applications expands agent use cases. Built-in security, monitoring, and compliance tools increase enterprise confidence in cloud deployments. For small and mid-sized organizations, cloud-based delivery significantly lowers entry barriers. As enterprises increasingly favor agility and scalability, cloud-based deployment continues to accelerate overall market growth.
GEOGRAPHICAL PENETRATION
ASIA-PACIFIC DRIVING AGENTIC AI ADOPTION THROUGH ENTERPRISE-SCALE INNOVATION
Asia-Pacific is emerging as a key growth engine for the Agentic AI market, driven by rapid enterprise digital transformation and strong IT services innovation. In 2025, Coforge announced the launch of EvolveOps.AI, highlighting the region’s leadership in deploying agentic AI for real-world enterprise operations. The platform demonstrates how agentic AI enables end-to-end autonomous IT operations across complex hybrid cloud environments. Built on open-source technologies, such solutions lower adoption barriers and accelerate scalability for enterprises across the region. This combination of cost efficiency, technical expertise, and AI-first strategies is positioning Asia-Pacific as a major contributor to global market growth.
CHINA ACCELERATING AGENTIC AI GROWTH THROUGH COMMERCE-LED INNOVATION
China is emerging as a major force in driving the Agentic AI market by embedding autonomous agents directly into large-scale digital commerce ecosystems. In 2026, leading technology giants such as Alibaba, Tencent, and ByteDance are heavily investing in agentic AI to transform chatbots into end-to-end transaction engines. This shift toward “agentic commerce” enables AI systems to autonomously manage multi-step processes, from product discovery to payment completion.
Alibaba’s upgrade of its Qwen chatbot exemplifies this trend by allowing users to complete purchases, travel bookings, and service orders within a single interface. By connecting AI agents to platforms like Taobao, Fliggy, and Alipay, enterprises are demonstrating real-world scalability of agentic systems. This commerce-first approach is accelerating adoption, showcasing tangible ROI, and positioning China as a key driver of global Agentic AI market growth.
JAPAN ADVANCING AGENTIC AI ADOPTION THROUGH ECOSYSTEM-DRIVEN INNOVATION
Japan is driving Agentic AI market growth through large-scale ecosystem integration and consumer-facing deployments. In 2025, Rakuten Group, Inc. and Rakuten Mobile, Inc. launched Rakuten AI, marking a significant step toward mainstream agentic AI adoption. By embedding AI agents into Rakuten Link and offering web-based access, Rakuten is normalizing everyday interaction with autonomous AI. Planned rollout across Rakuten Ichiba further extends agentic AI into digital commerce and lifestyle services. This ecosystem-led strategy is accelerating user adoption and positioning Japan as a key contributor to global Agentic AI market expansion.
NORTH AMERICA DRIVING AGENTIC AI GROWTH THROUGH CLOUD MODERNIZATION AND ENTERPRISE EXECUTION
North America is driving Agentic AI market growth by focusing on practical execution rather than experimental adoption. In 2026, many U.S. enterprises continue to face constraints from legacy systems and fragmented data environments, limiting large-scale agentic AI deployment. Against this backdrop, NTT Data announced a multi-year strategic collaboration with Amazon Web Services to accelerate cloud modernization and responsible agentic AI adoption. The partnership emphasizes modernizing mission-critical workloads and building cloud-compliant foundations. This execution-led approach helps enterprises unlock tangible business value from agentic AI, particularly in regulated and high-growth sectors. As modernization initiatives scale, North America continues to play a central role in shaping enterprise-grade agentic AI adoption globally.
UNITED STATES: DRIVING AGENTIC AI GROWTH THROUGH ENTERPRISE-SCALE ENABLEMENT
United States is accelerating Agentic AI market growth by enabling enterprises to operationalize AI at scale without disrupting existing infrastructure. In 2026, IBM launched IBM Enterprise Advantage, an asset-based consulting service focused on building, governing, and scaling internal agentic AI platforms. The solution allows organizations to redesign workflows and deploy agentic applications across heterogeneous environments. Its compatibility with platforms such as Amazon Web Services, Google Cloud, Microsoft Azure, and IBM watsonx reduces adoption friction. This execution-focused approach is strengthening U.S. leadership in enterprise-grade agentic AI deployment.
CANADA AGENTIC AI INDUSTRY GROWTH
Canada is driving Agentic AI market growth by extending advanced AI capabilities to mid-market organizations. In 2025, MNP expanded its partnership with Microsoft to deliver agentic AI solutions tailored for mid-sized enterprises. Through the launch of MNP AI Foundry, clients are supported across the full AI lifecycle, from opportunity identification to large-scale deployment. The initiative focuses on scaling Microsoft 365 Copilot and related agents across business functions. This ecosystem-led, services-driven model is accelerating agentic AI adoption and market growth across Canada’s mid-market segment.
SUSTAINABILITY ANALYSIS
Sustainability is emerging as a critical consideration in the Agentic AI market as enterprises seek to balance automation benefits with environmental and social responsibility. Agentic AI systems help optimize resource utilization by reducing manual processes, improving energy efficiency, and minimizing operational waste across enterprise workflows.
Cloud-based and autonomous operations enable dynamic workload management, lowering compute and infrastructure inefficiencies. At the same time, growing focus on responsible AI ensures transparency, governance, and ethical decision-making within autonomous systems. Enterprises are increasingly aligning agentic AI deployments with long-term ESG goals and regulatory expectations. As sustainability-driven investments rise, agentic AI is positioned as a key enabler of efficient, resilient, and responsible digital transformation.
COMPETITIVE LANDSCAPE
• The global agentic AI market is characterized by a competitive landscape that includes both established and regional players.
• Key players include Microsoft, Google, Amazon Web Services, Anthropic, IBM, Salesforce, ServiceNow, NVIDIA, Accenture, Oracle and among others.
Key Developments
• In 2026, Microsoft Corp. announced new agentic AI solutions aimed at embedding intelligent automation across the retail value chain, enabling faster decision-making and more personalized shopper experiences. The solutions unify merchandising, marketing, store operations, and fulfillment through a connected intelligence layer that replaces fragmented workflows with coordinated execution. By delivering context-aware, proactive tools, Microsoft is accelerating retail’s shift toward a resilient, intelligence-driven operating model.
• In 2026, Cognizant announced the launch of Cognizant Agent Foundry, a solution designed to help enterprises build, deploy, and orchestrate autonomous AI agents at scale. The offering combines a flexible framework, reusable assets, and implementation services leveraging Cognizant and third-party IP. It enables continuous, agent-driven transformation by supporting adaptive operations, real-time decision-making, and personalized customer experiences across enterprise workflows.
Why Choose DataM?
• Data-Driven Insights: Dive into detailed analyses with granular insights such as pricing, market shares and value chain evaluations, enriched by interviews with industry leaders and disruptors.
• Post-Purchase Support and Expert Analyst Consultations: As a valued client, gain direct access to our expert analysts for personalized advice and strategic guidance, tailored to your specific needs and challenges.
• White Papers and Case Studies: Benefit quarterly from our in-depth studies related to your purchased titles, tailored to refine your operational and marketing strategies for maximum impact.
• Annual Updates on Purchased Reports: As an existing customer, enjoy the privilege of annual updates to your reports, ensuring you stay abreast of the latest market insights and technological advancements. Terms and conditions apply.
• Specialized Focus on Emerging Markets: DataM differentiates itself by delivering in-depth, specialized insights specifically for emerging markets, rather than offering generalized geographic overviews. This approach equips our clients with a nuanced understanding and actionable intelligence that are essential for navigating and succeeding in high-growth regions.
• Value of DataM Reports: Our reports offer specialized insights tailored to the latest trends and specific business inquiries. This personalized approach provides a deeper, strategic perspective, ensuring you receive the precise information necessary to make informed decisions. These insights complement and go beyond what is typically available in generic databases.
Target Audience 2026
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies
Global Agentic AI market was valued at US$ 4.54 billion in 2025 and is expected to reach US$ 98.26 billion by 2033, growing at a CAGR of 46.87% during the forecast period 2026–2033. The market is experiencing strong momentum as enterprises increasingly shift toward autonomous, goal-driven AI systems to manage complex workflows and decision-making processes.
Rapid advancements in large language models, agent orchestration frameworks, and RAG-enabled architectures are accelerating adoption across industries. Organizations are deploying agentic AI to improve operational efficiency, reduce manual intervention, and enable real-time intelligence. Growing emphasis on scalable automation and adaptive systems is further strengthening demand. Integration of agentic AI with enterprise software platforms is expanding use cases across IT, BFSI, healthcare, and manufacturing.
AGENTIC AI INDUSTRY TRENDS AND STRATEGIC INSIGHTS
• Asia-Pacific is the fastest growing region in the agentic AI market, capturing the share of 25.41% in 2025.
• By component, the software platforms is projected to be the largest market, holding a significant share of about 19.22% in 2025.
GLOBAL AGENTIC AI MARKET SIZE AND FUTURE OUTLOOK
• 2025 Market Size: US$ 4.54 Billion
• 2033 Projected Market Size: US$ 98.26 Billion
• CAGR (2026-2033): 46.87%
• Largest Market: North America
• Fastest Market: Asia-Pacific
For more detailed information, Request for Free sample (https://www.datamintelligence.com/download-sample/agentic-ai-market)
MARKET SCOPE
Metrics Details
By Component Software Platforms, AI Models & Frameworks, Agent Orchestration Engines, Tool Integration Layers, Services. Others
By Agent Type Single-Agent Systems, Multi-Agent Systems Autonomous Agents, Semi-Autonomous Agents, Collaborative Agents, Others
By Deployment Mode Cloud-Based, On-Premise, Hybrid
By Organization Size Large Enterprises, Small & Medium Enterprises (SMEs)
By Application IT & Telecommunications, BFSI (Banking, Financial Services & Insurance), Healthcare & Life Sciences, Retail & E-commerce, Manufacturing, Logistics & Transportation, Energy & Utilities, Media & Entertainment, Others
By Region North America, South America, Europe, Asia-Pacific, Middle East and Africa
Report Insights Covered Competitive Landscape Analysis, Company Profile Analysis, Market Size, Share, Growth
MARKET DYNAMICS
REAL-TIME KNOWLEDGE INTEGRATION ACCELERATING AGENTIC AI ADOPTION
Outdated and inaccurate information remains a critical challenge for enterprises, directly impacting compliance, decision quality, and operational efficiency. In 2025, the integration of AI agents with Retrieval Augmented Generation (RAG) is emerging as a key market driver by enabling access to real-time, verified data sources.
RAG-powered agents combine the reasoning capabilities of large language models with dynamic retrieval from regulatory databases, enterprise repositories, and external knowledge systems. For instance, compliance assistant agents can automatically pull the latest regulatory updates, interpret changes, and assess potential exposure across business operations.
This significantly reduces manual research effort while improving accuracy and consistency in compliance workflows. By grounding agent decisions in up-to-date information, enterprises can mitigate regulatory risks and avoid costly errors. Faster, data-backed decision-making also enhances audit readiness and governance outcomes. As trust, transparency, and accountability become essential for autonomous systems, RAG-integrated AI agents are accelerating enterprise adoption and driving overall market growth.
GROWTH OF AGENTIC AI MARKETPLACES AND PARTNER ECOSYSTEMS
The growth of agentic AI marketplaces and partner ecosystems is acting as a strong catalyst for overall market expansion by lowering entry barriers for enterprises. Much like the early evolution of mobile app stores, the emerging agent economy allows organizations to access ready-made AI agents instead of building solutions from scratch. Enterprises can now purchase, customize, and deploy pre-built agents tailored to specific business functions and workflows.
Platforms such as Hugging Face Agents and Microsoft Copilot Studio are leading this shift by offering plug-and-play agent solutions. These ecosystems enable faster deployment cycles and significantly reduce development complexity. The availability of partner-built agents also encourages innovation and specialization across industries. For small and mid-sized businesses, marketplaces make agentic AI more affordable and accessible. As ecosystem participation grows, network effects are accelerating adoption and driving sustained market growth.
SEGMENTATION ANALYSIS
The global agentic AI market is segmented based on component, agent type, deployment mode, organization size, application and region.
SOFTWARE PLATFORMS AS THE FOUNDATION OF AGENTIC AI MARKET EXPANSION
The software platforms segment plays a pivotal role in driving the growth of the Agentic AI market by serving as the core layer that enables agent development, deployment, and orchestration. These platforms provide end-to-end environments for building autonomous and multi-agent systems without requiring deep AI engineering expertise. Integrated capabilities such as agent memory, tool management, and workflow orchestration accelerate enterprise adoption.
Software platforms also support seamless integration with enterprise applications, APIs, and data sources, expanding real-world use cases. Built-in governance, monitoring, and security features increase trust in agent-driven operations. By reducing development time and operational complexity, platforms lower total cost of ownership for organizations. This scalability makes agentic AI viable across both large enterprises and SMEs. As enterprises prioritize speed, flexibility, and control, software platforms continue to act as a primary engine of market growth.
CLOUD-BASED DEPLOYMENT ACCELERATING SCALABLE ADOPTION OF AGENTIC AI
The cloud-based deployment segment is a major driver of growth in the Agentic AI market by enabling scalable, flexible, and cost-efficient adoption of autonomous AI systems. Cloud platforms allow enterprises to deploy and manage AI agents without heavy upfront infrastructure investments. On-demand compute and storage support the intensive processing requirements of large language models and multi-agent workflows.
Cloud environments also enable rapid experimentation, continuous updates, and real-time performance optimization of agents. Seamless integration with cloud-native data sources and enterprise SaaS applications expands agent use cases. Built-in security, monitoring, and compliance tools increase enterprise confidence in cloud deployments. For small and mid-sized organizations, cloud-based delivery significantly lowers entry barriers. As enterprises increasingly favor agility and scalability, cloud-based deployment continues to accelerate overall market growth.
GEOGRAPHICAL PENETRATION
ASIA-PACIFIC DRIVING AGENTIC AI ADOPTION THROUGH ENTERPRISE-SCALE INNOVATION
Asia-Pacific is emerging as a key growth engine for the Agentic AI market, driven by rapid enterprise digital transformation and strong IT services innovation. In 2025, Coforge announced the launch of EvolveOps.AI, highlighting the region’s leadership in deploying agentic AI for real-world enterprise operations. The platform demonstrates how agentic AI enables end-to-end autonomous IT operations across complex hybrid cloud environments. Built on open-source technologies, such solutions lower adoption barriers and accelerate scalability for enterprises across the region. This combination of cost efficiency, technical expertise, and AI-first strategies is positioning Asia-Pacific as a major contributor to global market growth.
CHINA ACCELERATING AGENTIC AI GROWTH THROUGH COMMERCE-LED INNOVATION
China is emerging as a major force in driving the Agentic AI market by embedding autonomous agents directly into large-scale digital commerce ecosystems. In 2026, leading technology giants such as Alibaba, Tencent, and ByteDance are heavily investing in agentic AI to transform chatbots into end-to-end transaction engines. This shift toward “agentic commerce” enables AI systems to autonomously manage multi-step processes, from product discovery to payment completion.
Alibaba’s upgrade of its Qwen chatbot exemplifies this trend by allowing users to complete purchases, travel bookings, and service orders within a single interface. By connecting AI agents to platforms like Taobao, Fliggy, and Alipay, enterprises are demonstrating real-world scalability of agentic systems. This commerce-first approach is accelerating adoption, showcasing tangible ROI, and positioning China as a key driver of global Agentic AI market growth.
JAPAN ADVANCING AGENTIC AI ADOPTION THROUGH ECOSYSTEM-DRIVEN INNOVATION
Japan is driving Agentic AI market growth through large-scale ecosystem integration and consumer-facing deployments. In 2025, Rakuten Group, Inc. and Rakuten Mobile, Inc. launched Rakuten AI, marking a significant step toward mainstream agentic AI adoption. By embedding AI agents into Rakuten Link and offering web-based access, Rakuten is normalizing everyday interaction with autonomous AI. Planned rollout across Rakuten Ichiba further extends agentic AI into digital commerce and lifestyle services. This ecosystem-led strategy is accelerating user adoption and positioning Japan as a key contributor to global Agentic AI market expansion.
NORTH AMERICA DRIVING AGENTIC AI GROWTH THROUGH CLOUD MODERNIZATION AND ENTERPRISE EXECUTION
North America is driving Agentic AI market growth by focusing on practical execution rather than experimental adoption. In 2026, many U.S. enterprises continue to face constraints from legacy systems and fragmented data environments, limiting large-scale agentic AI deployment. Against this backdrop, NTT Data announced a multi-year strategic collaboration with Amazon Web Services to accelerate cloud modernization and responsible agentic AI adoption. The partnership emphasizes modernizing mission-critical workloads and building cloud-compliant foundations. This execution-led approach helps enterprises unlock tangible business value from agentic AI, particularly in regulated and high-growth sectors. As modernization initiatives scale, North America continues to play a central role in shaping enterprise-grade agentic AI adoption globally.
UNITED STATES: DRIVING AGENTIC AI GROWTH THROUGH ENTERPRISE-SCALE ENABLEMENT
United States is accelerating Agentic AI market growth by enabling enterprises to operationalize AI at scale without disrupting existing infrastructure. In 2026, IBM launched IBM Enterprise Advantage, an asset-based consulting service focused on building, governing, and scaling internal agentic AI platforms. The solution allows organizations to redesign workflows and deploy agentic applications across heterogeneous environments. Its compatibility with platforms such as Amazon Web Services, Google Cloud, Microsoft Azure, and IBM watsonx reduces adoption friction. This execution-focused approach is strengthening U.S. leadership in enterprise-grade agentic AI deployment.
CANADA AGENTIC AI INDUSTRY GROWTH
Canada is driving Agentic AI market growth by extending advanced AI capabilities to mid-market organizations. In 2025, MNP expanded its partnership with Microsoft to deliver agentic AI solutions tailored for mid-sized enterprises. Through the launch of MNP AI Foundry, clients are supported across the full AI lifecycle, from opportunity identification to large-scale deployment. The initiative focuses on scaling Microsoft 365 Copilot and related agents across business functions. This ecosystem-led, services-driven model is accelerating agentic AI adoption and market growth across Canada’s mid-market segment.
SUSTAINABILITY ANALYSIS
Sustainability is emerging as a critical consideration in the Agentic AI market as enterprises seek to balance automation benefits with environmental and social responsibility. Agentic AI systems help optimize resource utilization by reducing manual processes, improving energy efficiency, and minimizing operational waste across enterprise workflows.
Cloud-based and autonomous operations enable dynamic workload management, lowering compute and infrastructure inefficiencies. At the same time, growing focus on responsible AI ensures transparency, governance, and ethical decision-making within autonomous systems. Enterprises are increasingly aligning agentic AI deployments with long-term ESG goals and regulatory expectations. As sustainability-driven investments rise, agentic AI is positioned as a key enabler of efficient, resilient, and responsible digital transformation.
COMPETITIVE LANDSCAPE
• The global agentic AI market is characterized by a competitive landscape that includes both established and regional players.
• Key players include Microsoft, Google, Amazon Web Services, Anthropic, IBM, Salesforce, ServiceNow, NVIDIA, Accenture, Oracle and among others.
Key Developments
• In 2026, Microsoft Corp. announced new agentic AI solutions aimed at embedding intelligent automation across the retail value chain, enabling faster decision-making and more personalized shopper experiences. The solutions unify merchandising, marketing, store operations, and fulfillment through a connected intelligence layer that replaces fragmented workflows with coordinated execution. By delivering context-aware, proactive tools, Microsoft is accelerating retail’s shift toward a resilient, intelligence-driven operating model.
• In 2026, Cognizant announced the launch of Cognizant Agent Foundry, a solution designed to help enterprises build, deploy, and orchestrate autonomous AI agents at scale. The offering combines a flexible framework, reusable assets, and implementation services leveraging Cognizant and third-party IP. It enables continuous, agent-driven transformation by supporting adaptive operations, real-time decision-making, and personalized customer experiences across enterprise workflows.
Why Choose DataM?
• Data-Driven Insights: Dive into detailed analyses with granular insights such as pricing, market shares and value chain evaluations, enriched by interviews with industry leaders and disruptors.
• Post-Purchase Support and Expert Analyst Consultations: As a valued client, gain direct access to our expert analysts for personalized advice and strategic guidance, tailored to your specific needs and challenges.
• White Papers and Case Studies: Benefit quarterly from our in-depth studies related to your purchased titles, tailored to refine your operational and marketing strategies for maximum impact.
• Annual Updates on Purchased Reports: As an existing customer, enjoy the privilege of annual updates to your reports, ensuring you stay abreast of the latest market insights and technological advancements. Terms and conditions apply.
• Specialized Focus on Emerging Markets: DataM differentiates itself by delivering in-depth, specialized insights specifically for emerging markets, rather than offering generalized geographic overviews. This approach equips our clients with a nuanced understanding and actionable intelligence that are essential for navigating and succeeding in high-growth regions.
• Value of DataM Reports: Our reports offer specialized insights tailored to the latest trends and specific business inquiries. This personalized approach provides a deeper, strategic perspective, ensuring you receive the precise information necessary to make informed decisions. These insights complement and go beyond what is typically available in generic databases.
Target Audience 2026
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies
Table of Contents
180 Pages
- 1. Methodology and Scope
- 1.1. Research Data
- 1.1.1. Secondary Data
- 1.1.2. Primary Data
- 1.1.3. CAGR Analysis
- 1.2. Market Size Estimation Methodology
- 1.2.1. Bottom-Up Approach
- 1.2.2. Top-Down Approach
- 1.3. Market Breakdown & Data Triangulation
- 1.4. Research Assumptions
- 1.5. Limitations
- 2. Definition and Overview
- 2.1. Study Objectives
- 2.2. Market Definition
- 2.3. Market Scope
- 2.4. Stakeholder Analysis
- 2.5. Currency Considered
- 2.6. Study Period
- 3. Executive Summary
- 3.1. Key Takeaways
- 3.2. Top To Bottom Analysis
- 3.3. Market Share Analysis
- 3.4. Data Points from Key Primary Interviews
- 3.5. Data Points from Key Secondary Databases
- 3.6. Market Snapshot
- 3.7. Geographical Snapshot
- 4. Dynamics
- 4.1. Impacting Factors
- 4.1.1. Drivers
- 4.1.1.1. Real-Time Knowledge Integration Accelerating Agentic AI Adoption
- 4.1.1.2. Growth of Agentic AI Marketplaces and Partner Ecosystems
- 4.1.2. Restraints
- 4.1.2.1. Lack of Standardized Agent Governance Frameworks
- 4.1.3. Impact Analysis – Drivers and Restraints
- 4.1.4. Opportunity
- 4.1.4.1. Integration with Legacy Enterprise Systems
- 4.1.4.2. Rising Demand for AI-Driven Workflow Marketplaces
- 4.1.5. Trends
- 4.1.6. Challenges
- 5. Industry Analysis
- 5.1. Porter’s Five Force Analysis
- 5.2. Political Factors
- 5.3. Social Factors
- 5.3.1. Changing Consumer Trends
- 5.3.2. Population Growth
- 5.3.3. Demographic Shifts
- 5.4. Economic Factors
- 5.4.1. Interest Rates
- 5.4.2. Disposable Incomes
- 5.4.3. Inflation
- 5.4.4. GDP
- 5.4.5. Exchange Rates
- 5.4.6. Unemployment Rates
- 5.5. Geopolitical Factors
- 5.6. Supply/Value Chain Analysis
- 5.7. Pricing Analysis
- 5.8. Tariff Analysis
- 5.8.1. Overview Of Relevant Tariffs
- 5.8.2. Trade Policies Influencing the Market
- 5.8.3. Cost Impact Factors
- 5.8.4. Supply Chain Disruptions
- 5.9. Regulatory Analysis
- 5.10. Technology Landscape
- 5.11. Go-To-Market (GTM) Strategy
- 5.12. Innovation & R&D Trends
- 5.13. Sustainability and ESG Analysis
- 5.14. Key Strategic Initiatives
- 5.14.1. Emerging Players and Startups
- 5.14.2. Major Players
- 5.15. DMI Opinion
- 6. By Component
- 6.1. Introduction
- 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 6.1.2. Market Attractiveness Index, By Component
- 6.2. Software Platforms *
- 6.2.1. Introduction
- 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
- 6.3. AI Models & Frameworks
- 6.4. Agent Orchestration Engines
- 6.5. Tool Integration Layers
- 6.6. Services
- 6.7. Others
- 7. By Agent Type
- 7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Agent Type
- 7.1.2. Market Attractiveness Index, By Agent Type
- 7.2. Single-Agent Systems *
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
- 7.3. Multi-Agent Systems
- 7.4. Autonomous Agents
- 7.5. Semi-Autonomous Agents
- 7.6. Collaborative Agents
- 7.7. Others
- 8. By Deployment Mode
- 8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 8.1.2. Market Attractiveness Index, By Deployment Mode
- 8.2. Cloud-Based *
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
- 8.3. On-Premise
- 8.4. Hybrid
- 9. By Organization Size
- 9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 9.1.2. Market Attractiveness Index, By Organization Size
- 9.2. Large Enterprises *
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
- 9.3. Small & Medium Enterprises (SMEs)
- 10. By Application
- 10.1. Introduction
- 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.1.2. Market Attractiveness Index, By Application
- 10.2. IT & Telecommunications *
- 10.2.1. Introduction
- 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
- 10.3. BFSI (Banking, Financial Services & Insurance)
- 10.4. Healthcare & Life Sciences
- 10.5. Retail & E-commerce
- 10.6. Manufacturing
- 10.7. Logistics & Transportation
- 10.8. Energy & Utilities
- 10.9. Media & Entertainment
- 10.10. Others
- 11. By Region
- 11.1. Introduction
- 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 11.1.2. Market Attractiveness Index, By Region
- 11.2. North America
- 11.2.1. Introduction
- 11.2.2. Key Region-Specific Dynamics
- 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Agent Type
- 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
- 11.2.8.1. US
- 11.2.8.2. Canada
- 11.2.8.3. Mexico
- 11.3. Europe
- 11.3.1. Introduction
- 11.3.2. Key Region-Specific Dynamics
- 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Agent Type
- 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
- 11.3.8.1. Germany
- 11.3.8.2. UK
- 11.3.8.3. France
- 11.3.8.4. Russia
- 11.3.8.5. Spain
- 11.3.8.6. Italy
- 11.3.8.7. Norway
- 11.3.8.8. Netherlands
- 11.3.8.9. Sweden
- 11.3.8.10. Denmark
- 11.3.8.11. Belgium
- 11.3.8.12. Switzerland
- 11.3.8.13. Austria
- 11.3.8.14. Poland
- 11.3.8.15. Finland
- 11.3.8.16. Rest of Europe
- 11.4. Latin America
- 11.4.1. Introduction
- 11.4.2. Key Region-Specific Dynamics
- 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Agent Type
- 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
- 11.4.8.1. Brazil
- 11.4.8.2. Argentina
- 11.4.8.3. Rest of Latin America
- 11.5. Asia-Pacific
- 11.5.1. Introduction
- 11.5.2. Key Region-Specific Dynamics
- 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Agent Type
- 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
- 11.5.8.1. China
- 11.5.8.2. India
- 11.5.8.3. Japan
- 11.5.8.4. Australia
- 11.5.8.5. South Korea
- 11.5.8.6. New Zealand
- 11.5.8.7. Indonesia
- 11.5.8.8. Malaysia
- 11.5.8.9. Philippines
- 11.5.8.10. Singapore
- 11.5.8.11. Thailand
- 11.5.8.12. Vietnam
- 11.5.8.13. Rest of Asia-Pacific
- 11.6. Middle East and Africa
- 11.6.1. Introduction
- 11.6.2. Key Region-Specific Dynamics
- 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Agent Type
- 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
- 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.6.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
- 11.6.8.1. UAE
- 11.6.8.2. Saudi Arabia
- 11.6.8.3. South Africa
- 11.6.8.4. Israel
- 11.6.8.5. Egypt
- 11.6.8.6. Turkey
- 11.6.8.7. Qatar
- 11.6.8.8. Kuwait
- 11.6.8.9. Oman
- 11.6.8.10. Bahrain
- 11.6.8.11. Rest of Middle East and Africa
- 12. Competitive Landscape
- 12.1. Competitive Scenario
- 12.2. Market Share Analysis – Global
- 12.3. Market Share Analysis – North America
- 12.4. Market Share Analysis - Europe
- 12.5. Market Share Analysis – Asia-Pacific
- 12.6. Mergers and Acquisitions Analysis
- 12.7. Partner Identification Analysis
- 12.8. Investment & Funding Landscape
- 12.9. Strategic Alliances & Innovation Pipeline
- 13. Company Profiles
- 13.1. Microsoft Corporation*
- 13.1.1. Company Overview
- 13.1.2. Product Portfolio and Description
- 13.1.3. Revenue Analysis
- 13.1.4. Pricing Analysis
- 13.1.5. SWOT Analysis
- 13.1.6. Recent Developments
- 13.1.6.1. Major Deals
- 13.1.6.2. M&A
- 13.1.6.3. Collaboration
- 13.1.6.4. Acquisition
- 13.1.6.5. Joint Ventures
- 13.1.6.6. Innovations
- 13.1.7. Recent News
- 13.1.7.1. Events
- 13.1.7.2. Conferences
- 13.1.7.3. Symposiums
- 13.1.7.4. Webinars
- 13.2. Google
- 13.3. Amazon Web Services
- 13.4. Anthropic
- 13.5. IBM
- 13.6. Salesforce
- 13.7. ServiceNow
- 13.8. NVIDIA
- 13.9. Accenture
- 13.10. Oracle (LIST NOT EXHAUSTIVE)
- 14. Appendix
- 14.1. About Us and Services
- 14.2. Contact Us
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