Global Agentic AI in Enterprise IT Market Size, Share, Statistics Analysis Report By Product (Customer Relationship Management (CRM), Supply Chain Management (SCM), Business Intelligence (BI), Business Process Management (BPM), Content Management System (CMS), Enterprise Resource Planning (ERP), Others), By Deployment (Cloud, On Premise), By enterprise Size (Large Enterprises, SME''s), By Technology (Machine Learning (ML), Reinforcement Learning (RL), Deep Learning (DL), Natural Language Processing (NLP), Computer Vision, Others), By End Use (IT & Telecom, BFSI, Retail, Government/Public Sector, Energy & Utilities, Healthcare, Others), Region and Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends and Forecast 2025-2034

Report Overview

The Global Agentic AI in Enterprise IT Market size is expected to be worth around USD 182.9 Billion By 2034, from USD 4.1 Billion in 2024, growing at a CAGR of 46.20% during the forecast period from 2025 to 2034. In 2024, North America led the Agentic AI in Enterprise IT sector, capturing over 38.4% of the market share, generating approximately USD 1.5 billion in revenue.

The market for agentic AI in enterprise IT is rapidly expanding, driven by the technology’s ability to streamline operations and reduce the reliance on human intervention. Organizations across various industries are recognizing the potential of agentic AI to improve decision-making processes and operational efficiency. As such, enterprises are increasingly investing in agentic AI technologies to gain a competitive edge, adapt to market changes more swiftly, and improve overall productivity.

The growth of the agentic AI market can be attributed to several key factors. Firstly, the increasing complexity of business environments and the need for rapid decision-making support agentic AI adoption. Additionally, the push towards digital transformation across sectors fuels the demand for intelligent systems that can operate autonomously and manage large datasets with minimal errors.

Key Takeaways

• The Global Agentic AI in Enterprise IT Market is expected to reach a value of USD 182.9 Billion by 2034, growing from USD 4.1 Billion in 2024 at a CAGR of 46.20% during the forecast period from 2025 to 2034.
• In 2024, the Customer Relationship Management (CRM) segment held a dominant position, capturing more than 28.8% of the market share in the Agentic AI in Enterprise IT landscape.
• In 2024, the On Premise deployment segment also led the market, accounting for more than 60.4% of the market share in the agentic AI enterprise IT sector.
• In 2024, Large Enterprises held a dominant market position, capturing more than 75.7% of the share in the Agentic AI in Enterprise IT market.
• In 2024, the Natural Language Processing (NLP) segment was a leader in the enterprise IT market for agentic AI, holding more than 34.6% of the market share.
• In 2024, the IT & Telecom sector was the largest contributor to the enterprise IT market for agentic AI, accounting for more than 30.3% of the total share.
• In 2024, North America dominated the Agentic AI in Enterprise IT sector, with more than 38.4% market share, amounting to approximately USD 1.5 billion in revenue.
• The U.S. Agentic AI in Enterprise IT Market, valued at USD 1.25 billion in 2024, is expected to grow at a CAGR of 44.2%.

U.S. Market Growth Analysis

The market for Agentic AI in Enterprise IT in the U.S., which was valued at $1.25 billion in 2024, is forecasted to expand at a compound annual growth rate (CAGR) of 44.2%. This significant growth underscores the increasing reliance on agentic AI technologies within enterprise IT infrastructures.

Agentic AI technologies are being incorporated into enterprise IT applications to automate complex tasks and deliver strategic insights that traditional IT solutions couldn’t. This growing adoption is fueled by the demand for more dynamic, adaptable IT environments that can quickly respond to changing business needs and market conditions.

As the market matures, key industry players are investing heavily in research and development to innovate and improve agentic AI capabilities. This is further supported by a growing ecosystem of startups and established firms collaborating on developing scalable AI solutions that are secure and compliant with evolving regulatory standards.

In 2024, North America held a dominant market position in the Agentic AI in Enterprise IT sector, capturing more than a 38.4% share, amounting to a revenue of approximately USD 1.5 billion.

The region’s robust technological infrastructure, coupled with substantial investments from both public and private sectors in AI research and development, drives this significant market share. Additionally, the presence of leading AI technology giants and numerous startups focused on enterprise AI solutions further strengthens North America’s leading position.

North America’s regulatory environment, particularly in the U.S., is key to its dominance in AI. It provides a framework that promotes AI development while ensuring ethical standards and privacy guidelines are followed, creating a supportive atmosphere for businesses.

Moreover, North America’s advanced enterprise IT ecosystem is ripe for the integration of agentic AI technologies. Enterprises in sectors like finance, healthcare, and manufacturing are increasingly adopting AI to gain a competitive edge by automating decision-making, improving customer experiences, and optimizing operations.

Analysts’ Viewpoint

The adoption of agentic AI in enterprise IT is accelerating, driven by its potential to significantly boost productivity and efficiency. Businesses are increasingly recognizing the benefits of agentic AI, including its ability to automate complex processes and offer new levels of operational agility. Demand is particularly high in industries that require real-time data analysis and decision-making support, such as financial services, healthcare, and retail​.

A recent survey reveals that BT’s adoption of ServiceNow’s agentic AI platform has delivered remarkable results. Task resolution times have been slashed to under a minute, while paperwork has dropped by 55%. Additionally, the platform has boosted request handling efficiency by an impressive 80%.

Investment in agentic AI is seen as highly promising due to its potential to transform business operations and create competitive advantages. Investors are particularly interested in startups and companies that are pioneering the use of agentic AI to revolutionize industry standards and practices. As the technology matures, it presents substantial opportunities for ventures that can integrate these intelligent systems into their existing digital infrastructure to enhance efficiency and scalability​.

Impact of Agentic AI

• Enhanced Operational Efficiency: By automating complex workflows, agentic AI reduces manual tasks, leading to significant time and cost savings. This automation allows employees to focus on strategic initiatives, boosting overall productivity.
• Improved Decision-Making: Agentic AI systems analyze vast amounts of data to provide actionable insights, enabling businesses to make informed decisions swiftly. This capability is particularly valuable in dynamic markets where timely responses are crucial.
• Scalability and Adaptability: These AI agents can adjust to changing business environments, allowing companies to scale operations without significant additional resources. Their adaptability ensures that businesses remain resilient and competitive.
• Enhanced Customer Experience: By handling customer inquiries and support autonomously, agentic AI provides consistent and prompt service, leading to higher customer satisfaction and loyalty.
• Strategic Resource Allocation: With routine tasks managed by AI agents, human resources can be directed toward more strategic roles, fostering innovation and growth within the organization.

Product Analysis

In 2024, the Customer Relationship Management (CRM) segment held a dominant market position in the Agentic AI in Enterprise IT landscape, capturing more than a 28.8% share. This segment leads primarily due to its crucial role in automating customer interactions and enhancing personalized customer service.

CRM systems, when enhanced with agentic AI, allow businesses to analyze extensive customer data effectively, enabling predictive analytics to anticipate customer needs and preferences. This capability significantly improves customer engagement strategies, directly impacting sales and customer loyalty.

The supremacy of the CRM segment is further underscored by its integration across various industry verticals that prioritize customer-centric approaches. Retail, telecommunications, and financial services, in particular, have heavily invested in AI-driven CRM solutions to tailor their marketing efforts and improve customer service.

Moreover, advancements in AI technology have made CRM systems more intuitive and capable of handling complex tasks such as sentiment analysis and real-time decision-making. This has increased the attractiveness of CRM systems for companies aiming to harness deep insights from customer data to drive strategic decisions.

Deployment Analysis

In 2024, the On Premise deployment segment held a dominant position in the agentic AI enterprise IT market, capturing more than a 60.4% share. This significant market share is primarily attributed to the enhanced security and control that on-premise solutions offer to organizations.

Businesses in sectors like banking, government, and healthcare favor on-premise installations due to strict data privacy regulations and the sensitive nature of their data. On-premise solutions offer full control over infrastructure and data, driving their market dominance.

On-premise agentic AI systems offer reduced latency in data processing compared to cloud-based options. For enterprises needing real-time analysis and quick decision-making, the proximity of on-site servers accelerates the process. This is especially critical in industries where even small delays can cause major disruptions or financial losses.

The customization and integration capabilities of on-premise agentic AI systems make them highly attractive. Enterprises with unique IT environments benefit from tailored AI solutions that integrate seamlessly with legacy systems, offering flexibility and deep integration with existing hardware and software.

Enterprise Size Analysis

In 2024, the Large Enterprises segment held a dominant position in the Agentic AI in Enterprise IT market, capturing more than a 75.7% share. This substantial market dominance is attributed to the significant resources that large enterprises allocate to AI technologies.

These organizations have the capital necessary to invest in advanced AI systems and the infrastructure required to support their integration and ongoing evolution. Large enterprises are often at the forefront of adopting innovative technologies that promise to improve efficiency, reduce costs, and enhance decision-making processes.

Large enterprises dominate the sector due to their ability to attract top-tier AI talent. They can afford to hire experts who develop, implement, and manage advanced AI solutions tailored to their complex needs, giving them an edge over smaller companies.

Furthermore, large enterprises typically operate on a scale that justifies the investment in high-cost AI systems. The potential returns from automating processes, improving accuracy in data analysis, and enhancing customer engagements are significantly higher in large organizations due to their broader market reach and larger operational scopes.

Technology Analysis

In 2024, the Natural Language Processing (NLP) segment held a dominant market position in the enterprise IT market for agentic AI, capturing more than a 34.6% share. This leadership stems from the increasing adoption of NLP technologies across various industries seeking to enhance their interaction models and operational efficiencies.

NLP enables businesses to automate customer support, optimize search engines, and improve user interactions through advanced understanding and processing of human language. The demand for these capabilities has surged as organizations aim to provide more intuitive user experiences and streamline information-heavy tasks.

A key factor driving the prominence of the NLP segment is its role in enhancing customer experience and engagement. NLP applications like chatbots, sentiment analysis, and automated content generation improve interactions and provide valuable insights into customer behaviors and preferences.

Furthermore, the development of sophisticated algorithms and models in NLP has significantly reduced barriers to entry for its implementation in business processes. Improvements in language models, such as transformers and contextual understanding, have enhanced the accuracy and efficiency of NLP tools.

End Use Analysis

In 2024, the IT & Telecom segment held a dominant market position in the enterprise IT market for agentic AI, capturing more than a 30.3% share. This dominance is largely due to the critical need for advanced AI technologies to manage vast data flows and improve service delivery in these industries.

The rapid expansion of digital communication and data consumption has compelled IT and telecom companies to seek efficient ways to manage network traffic and customer queries. Agentic AI applications, such as intelligent traffic management systems and AI-driven customer support platforms, are essential for handling these tasks.

Additionally, cybersecurity is a major focus for the IT & Telecom sector, with enterprises investing heavily in AI-driven security solutions. Agentic AI technologies like anomaly detection and real-time threat analysis are critical for protecting infrastructure and customer data against increasingly sophisticated cyber-attacks.

Furthermore, the IT & Telecom sector’s commitment to innovation has fostered a conducive environment for AI integration. Many companies in this sector are at the forefront of AI research and application, often partnering with AI technology firms to develop new solutions that can provide them with a competitive edge.

Key Market Segments

By Product

• Customer Relationship Management (CRM)
• Supply Chain Management (SCM)
• Business Intelligence (BI)
• Business Process Management (BPM)
• Content Management System (CMS)
• Enterprise Resource Planning (ERP)
• Others

By Deployment

• Cloud
• On Premise

By Enterprise Size

• Large Enterprises
• SME”s

By Technology

• Machine Learning (ML)
• Reinforcement Learning (RL)
• Deep Learning (DL)
• Natural Language Processing (NLP)
• Computer Vision
• Others

By End Use

• IT & Telecom
• BFSI
• Retail
• Government/Public Sector
• Energy & Utilities
• Healthcare
• Others

By Regional Outlook

• North America
  • US
  • Canada
• Europe
  • Germany
  • France
  • The UK
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • South Korea
  • India
  • Australia
  • Singapore
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Rest of MEA

Driver

Enhancing Operational Efficiency

A significant driver for adopting agentic AI in enterprise IT is the pursuit of heightened operational efficiency. These intelligent agents can autonomously manage complex tasks, reducing the need for human intervention in routine processes.

For instance, in IT service management, agentic AI can handle tasks such as password resets, system monitoring, and software updates, allowing IT professionals to focus on more strategic initiatives. This shift not only streamlines operations but also leads to cost savings and improved service delivery. By automating repetitive tasks, businesses can achieve greater productivity and allocate resources more effectively.

Restraint

Ethical and Regulatory Concerns

Despite its advantages, the deployment of agentic AI faces significant ethical and regulatory challenges. The autonomous nature of these systems raises questions about data privacy, security, and accountability. Ensuring compliance with regulations such as the General Data Protection Regulation (GDPR) becomes complex when AI agents operate independently.

Additionally, the rapid evolution of AI technologies presents challenges related to accountability, especially in cases where AI systems make high-stakes decisions. Without clear accountability structures, it can be difficult to determine who is responsible when AI systems cause harm or make erroneous judgments. Establishing a transparent and accountable framework is crucial for public trust and for ensuring that AI serves the greater good, avoiding unintended negative consequences.

Opportunity

Revolutionizing Customer Service

Agentic AI presents a substantial opportunity to transform customer service operations. By deploying AI-powered conversational agents, businesses can provide faster, more accurate, and personalized responses to customer inquiries.

These agents can handle a wide range of tasks, from answering frequently asked questions to processing transactions, thereby enhancing the customer experience. Additionally, they can operate 24/7, ensuring that customer support is always available. This continuous availability not only improves customer satisfaction but also allows human agents to focus on more complex and value-added interactions.

Challenge

Integration with Existing Systems

Integrating agentic AI into existing enterprise IT infrastructures poses a significant challenge. Many organizations operate on legacy systems that may not be compatible with advanced AI technologies. Ensuring seamless interoperability between new AI agents and existing software requires substantial effort and resources.

Moreover, the complexity of implementation can lead to disruptions in business operations during the transition period. Organizations must carefully plan and execute integration strategies, which may involve upgrading current systems, retraining staff, and possibly reengineering business processes to fully leverage the benefits of agentic AI.

Emerging Trends

One emerging trend is the integration of agentic AI into customer service. Companies are deploying AI agents that handle customer inquiries, process transactions, and resolve issues in real-time, enhancing customer satisfaction and reducing the workload on human staff.

In supply chain management, agentic AI systems monitor inventory levels, predict demand fluctuations, and optimize logistics by autonomously coordinating with suppliers and distributors. This leads to reduced operational costs and improved efficiency.

Cybersecurity is another area benefiting from agentic AI. AI agents can detect anomalies, respond to threats, and implement security measures without waiting for human directives, providing a proactive defense against cyber attacks.

Business Benefits

• Boosting Efficiency: Agentic AI can handle repetitive tasks like updating client records or processing invoices. This allows employees to focus on more important work, leading to better productivity.
• Quick Decision-Making: By analyzing large amounts of data in real-time, agentic AI helps businesses make informed decisions swiftly, keeping them competitive in fast-paced markets.
• Cutting Costs: Automating complex workflows with agentic AI reduces the need for manual labor and minimizes errors, leading to significant cost savings.
• Improving Customer Service: Agentic AI provides personalized support to customers around the clock, enhancing their experience and satisfaction.
• Adapting to Changes: Agentic AI systems can adjust to changing market conditions in real-time, ensuring businesses remain flexible and responsive.

Key Player Analysis

Amazon Web Services (AWS) is a major player in the Agentic AI space, offering a broad range of cloud-based services that include machine learning and AI capabilities. AWS’s key strength lies in its scalability, robust infrastructure, and access to powerful computing resources, enabling enterprises to integrate AI into their systems without heavy upfront investments in hardware.

Google LLC, with its deep expertise in AI and machine learning, has positioned itself as a leader in the enterprise IT market. Through its Google Cloud platform, the company offers AI-driven solutions such as AutoML, TensorFlow, and BigQuery, empowering enterprises to build powerful AI applications.

Nvidia Corporation has earned a reputation as a pioneer in AI, particularly in the realm of high-performance computing and AI-driven hardware. Known for its graphics processing units (GPUs), Nvidia’s hardware is widely used to accelerate AI workloads, making it an essential player in Agentic AI adoption.

Top Key Players in the Market

• Microsoft Corporation
• Amazon Web Services, Inc.
• Google LLC
• Nvidia Corporation
• Salesforce, Inc.
• International Business Machines Corporation (IBM)
• Oracle Corporation
• UiPath
• Automation Anywhere
• Aisera, Inc.
• Others

Recent Developments

• January 2025- UiPath is integrating AI with robotic process automation to enhance flexibility across sectors. UiPath has also expanded its collaboration with Microsoft through the integration of Microsoft Azure OpenAI Service.
• June 2024: Automation Anywhere Launched the AI + Automation Enterprise System with second-generation GenAI Process Models and new AI Agents to manage complex tasks autonomously. This system is designed to improve efficiency across business workflows, including customer service, finance, IT, and HR.
• In 2024: Salesforce’s Agentforce, an Agentic AI-powered tool, was implemented by OpenTable to enhance customer experience through predictive capabilities and streamlined workflows
• In 2024: Google Invested in developing embedded Agentic AI solutions to optimize enterprise functions such as supply chain management and customer support. These systems are expected to integrate real-time decision-making at scale.

Report Scope