Global Enterprise Agentic AI Market Size, Share & Industry Analysis Report By Agent System (Single Agent Systems, and Multi Agent Systems), By Technology, By Type, By Application, By Regional Outlook and Forecast, 2025 - 2032

The Global Enterprise Agentic AI Market size is expected to reach $46.30 billion by 2032, rising at a market growth of 45.4% CAGR during the forecast period.

Based on Agent System, the market is segmented into Single Agent Systems, and Multi Agent Systems. One of the leading implementations of single-agent AI is found in Salesforce’s Einstein GPT, which powers single-agent virtual assistants to handle customer queries, generate knowledge articles, and summarize interactions. These agents are integrated within CRM systems and operate independently without collaboration from other agents, delivering high reliability for routine enterprise interactions.

The major strategies followed by the market participants are partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In August, 2024, Accenture and S&P Global have partnered to advance generative AI in financial services, launching an AI learning program for S&P's 35,000 employees and enhancing AI development and benchmarking tools to drive responsible innovation and performance across the industry. Additionally, In April, 2025, Celonis has expanded its strategic partnership with Microsoft, introducing a zero-copy integration between Celonis Process Intelligence and Microsoft Fabric. This enables seamless data sharing, reduced storage costs, and real-time insights within Microsoft tools like Power BI and Copilot, empowering users to enhance AI applications with contextual business process data.

KBV Cardinal Matrix - Enterprise Agentic AI Market Competition Analysis

Based on the Analysis presented in the KBV Cardinal matrix; Google LLC, Microsoft Corporation, NVIDIA Corporation, and Amazon Web Services, Inc. are the forerunners in the Enterprise Agentic AI Market. In January, 2025, NVIDIA Corporation partners with IQVIA, Illumina, Mayo Clinic, and Arc Institute to advance healthcare AI, accelerating drug discovery, genomics, and digital pathology. AI agents, robotics, and computing innovations aim to enhance clinical trials, diagnostics, and patient care across the healthcare industry. Companies such as Oracle Corporation, Accenture PLC, and SAP SE are some of the key innovators in Enterprise Agentic AI Market.

Market Growth Factors

The escalating complexity of business operations and the imperative for cost optimization have intensified the demand for automation. Agentic AI, characterized by autonomous decision-making capabilities, addresses this need by streamlining processes and reducing reliance on human intervention. Organizations are increasingly adopting agentic AI to enhance operational efficiency. Hence, Rising Enterprise Demand For Automation And Efficiency is driving the growth of the market.

Additionally, Technological progress has been pivotal in advancing agentic AI capabilities. The development of sophisticated algorithms enhanced computational power, and the proliferation of big data have collectively facilitated the deployment of intelligent agents capable of complex decision-making. The rise of agentic AI has been largely catalyzed by the convergence of enabling technologies such as machine learning, large language models (LLMs), cloud computing, and edge computing. Therefore, Technological Advancements And Infrastructure Readiness is propelling the growth of the market.

Market Restraining Factors

One of the most formidable barriers to the adoption of agentic AI is its high implementation cost. These expenses include not only the upfront investment in infrastructure—such as computing resources, data lakes, and licensing fees—but also the ongoing operational costs related to model training, maintenance, and scaling. According to McKinsey’s 2023 AI Report, nearly 55% of enterprises cited the cost of AI deployment as a primary factor inhibiting expansion. Thus, while agentic AI offers a strong ROI potential in the long run, the high upfront and operational costs continue to restrain adoption, particularly in non-tech-first sectors like manufacturing or government.

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships, Collaborations & Agreements.

Agent System Outlook

Based on Agent System, the market is segmented into Single Agent Systems, and Multi Agent Systems. Multi Agent Systems (MAS) are an evolution of enterprise agentic AI, where multiple autonomous agents operate within the same environment, interacting, coordinating, or even competing to achieve individual or shared goals. MAS structures mirror human organizations more closely, allowing distributed decision-making, self-organization, and collective problem-solving across functions.

Technology Outlook

Based on Technology, the market is segmented into Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, and Other Technology. Natural Language Processing (NLP) has become central to the success of agentic AI systems in enterprises, especially those dealing with large volumes of unstructured text and human interaction. NLP enables AI agents to understand, generate, and respond in natural human language—thus enabling applications like customer support automation, knowledge management, and HR onboarding.

Type Outlook

Based on Type, the market is segmented into Ready-to-Deploy Agents, and Build-Your-Own Agents. Build-your-own agentic AI systems cater to enterprises seeking full control, customization, and scalability over their autonomous systems. These agents are typically developed in-house or with support from OEMs and AI consultancies, using foundational models, open-source libraries, and proprietary business logic. Unlike off-the-shelf solutions, these agents can be trained on organization-specific data, integrated with custom APIs, and designed for complex decision-making across distributed systems.

Application Outlook

Based on Application, the market is segmented into Customer Service & Virtual Assistants, Robotics & Automation, Financial Services, Healthcare, Security & Surveillance, Gaming & Entertainment, Marketing & Sales, Human Resources, and Legal, Compliance & Others. In the realm of robotics and automation, agentic AI facilitates the development of autonomous systems that can perform complex tasks with minimal human intervention. These systems are employed in various industries, including manufacturing and logistics, to optimize operations and increase efficiency.

Regional Outlook

Region-wise, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA. These tools allow agents to perform long-context memory tasks, access proprietary tools via API calls, and manage internal processes—boosting enterprise efficiency. For example, Microsoft has embedded autonomous agentic features into Microsoft 365 Copilot, enabling knowledge workers to perform tasks such as summarization, writing, and decision-making with minimal intervention.

Market Competition and Attributes

The Enterprise Agentic AI Market remains moderately competitive, driven by emerging startups and mid-sized firms innovating rapidly. Niche solutions and domain-specific applications foster differentiation. Collaboration with enterprises for custom deployments adds to competitiveness. However, lack of dominant players opens opportunities for new entrants to shape standards and gain significant early traction in this evolving landscape.

Recent Strategies Deployed in the Market

• Apr-2025: Capgemini SE announced the establishment of an AI Center of Excellence in Egypt to drive global generative and agentic AI innovation. Opening in May 2025, the hub will support R&D, partner with academia, and develop tailored AI solutions. It aims to double local staff and deliver industry-specific transformation for clients worldwide.
• Mar-2025: OpenAI, LLC unveiled the Responses API and Agents SDK to help developers build AI agents capable of tasks like web browsing, file searching, and automating workflows. These tools replace the Assistants API and offer advanced capabilities powered by GPT-4o models, aiming to bring more autonomy and reliability to enterprise AI agents.
• Mar-2025: Capgemini SE teamed up with NVIDIA, a computer manufacturer corporation to develop industry-specific AI agent solutions across sectors like healthcare, finance, and manufacturing. Leveraging NVIDIA’s NIM and agentic gallery, the collaboration aims to simplify AI deployment, boost productivity, and reduce costs, while ensuring trust, security, and compliance for enterprise adoption.
• Feb-2025: OpenAI, LLC announced the partnership with SoftBank Group, a internet services company to develop "Cristal intelligence," an advanced enterprise AI tailored for companies. SoftBank will invest $3 billion annually to deploy OpenAI solutions across its group. A joint venture, SB OpenAI Japan, will market Cristal intelligence to Japanese enterprises, enabling secure, customized AI agent deployment.
• Feb-2025: Capgemini SE teamed up with SAP, a software company to integrate generative AI into key business processes like HR, sales, procurement, and sustainability. Leveraging SAP BTP and Capgemini’s AI expertise, the collaboration aims to accelerate transformation, upskill employees, and deliver customized, efficient, and scalable enterprise solutions.

List of Key Companies Profiled

• NVIDIA Corporation
• SAP SE
• Oracle Corporation
• Accenture PLC
• OpenAI, LLC
• Capgemini SE
• Celonis GmbH
• Microsoft Corporation
• Google LLC (Alphabet Inc.)
• Amazon Web Services, Inc. (Amazon.com, Inc.)

Global Enterprise Agentic AI Market Report Segmentation

By Agent System

• Single Agent Systems
• Multi Agent Systems

By Technology

• Machine Learning
• Deep Learning
• Natural Language Processing (NLP)
• Computer Vision
• Other Technology

By Type

• Ready-to-Deploy Agents
• Build-Your-Own Agents

By Application

• Customer Service & Virtual Assistants
• Robotics & Automation
• Financial Services
• Healthcare
• Security & Surveillance
• Gaming & Entertainment
• Marketing & Sales
• Human Resources
• Legal, Compliance & Others

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