Product Code: GVR-4-68040-589-1
U.S. Enterprise Agentic AI Market Trends:
The U.S. enterprise agentic AI market size was estimated at USD 769.5 million in 2024 and is expected to grow at a CAGR of 43.6% from 2025 to 2030. The market is driven by factors, including the increasing complexity of business environments and the essential need for rapid decision-making. Businesses are recognizing the potential of agentic AI to streamline operations and reduce reliance on human intervention. This has led to increased investments in agentic AI technologies as enterprises seek to gain a competitive edge, swiftly adapt to market changes, and improve overall productivity.
The demand for automation and efficiency is a primary driver for adopting enterprise agentic AI. These systems are capable of automating complex tasks that previously demanded significant human effort, which accelerates operations and improves accuracy, helping enterprises reduce costs in the U.S. market. In addition, the exponential growth of big data also fuels the adoption of agentic AI in the U.S., which uses advanced algorithms to analyze large datasets and provide insights for faster, more informed decision-making, giving businesses a competitive advantage. The rise of AI as a service is further democratizing access to agentic AI technologies, enabling U.S. companies of all sizes to implement AI solutions without high initial infrastructure investments.
Furthermore, AI's ability to enhance productivity and efficiency across various sectors is significant. In finance, agentic AI can handle rapid trading and fraud detection by analyzing massive amounts of data in real-time to facilitate quick decisions. Similarly, in healthcare, AI can assist doctors and specialists in diagnosing and recommending treatments for complex cases. Moreover, the integration of multiple automation systems to create end-to-end workflows powered by intelligent AI agents is expected to drive market growth.
U.S. Enterprise Agentic AI Market Report Segmentation
This report forecasts revenue growth at the country level and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the U.S. enterprise agentic AI market report based on technology, agent system, type, and application:
- Technology Outlook (Revenue, USD Million, 2018 - 2030)
- Machine Learning
- Natural Language Processing (NLP)
- Deep Learning
- Computer Vision
- Others
- Agent System Outlook (Revenue, USD Million, 2018 - 2030)
- Single Agent Systems
- Multi Agent Systems
- Type Outlook (Revenue, USD Million, 2018 - 2030)
- Ready-to-Deploy Agents
- Build-Your-Own Agents
- Application Outlook (Revenue, USD Million, 2018 - 2030)
- Customer Service and Virtual Assistants
- Robotics and Automation
- Healthcare
- Financial Services
- Security and Surveillance
- Gaming and Entertainment
- Marketing and sales
- Human Resources
- Legal and compliance
- Others
Table of Contents
Chapter 1. Methodology and Scope
- 1.1. Market Segmentation and Scope
- 1.2. Research Methodology
- 1.2.1. Information Procurement
- 1.3. Information or Data Analysis
- 1.4. Methodology
- 1.5. Research Scope and Assumptions
- 1.6. Market Formulation & Validation
- 1.7. Country Based Segment Share Calculation
- 1.8. List of Data Sources
Chapter 2. Executive Summary
- 2.1. Market Outlook
- 2.2. Segment Outlook
- 2.3. Competitive Insights
Chapter 3. U.S. Enterprise Agentic AI Market Variables, Trends, & Scope
- 3.1. Market Lineage Outlook
- 3.2. Market Dynamics
- 3.2.1. Market Driver Analysis
- 3.2.2. Market Restraint Analysis
- 3.2.3. Industry Challenge
- 3.3. U.S. Enterprise Agentic AI market Analysis Tools
- 3.3.1. Industry Analysis - Porter's
- 3.3.1.1. Bargaining power of the suppliers
- 3.3.1.2. Bargaining power of the buyers
- 3.3.1.3. Threats of substitution
- 3.3.1.4. Threats from new entrants
- 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
- 3.3.2.1. Political landscape
- 3.3.2.2. Economic and Social landscape
- 3.3.2.3. Technological landscape
- 3.4. Pain Point Analysis
Chapter 4. U.S. Enterprise Agentic AI Market: Technology Estimates & Trend Analysis
- 4.1. Segment Dashboard
- 4.2. U.S. Enterprise Agentic AI market: Technology Movement Analysis, 2024 & 2030 (USD Million)
- 4.3. Machine Learning
- 4.3.1. Machine Learning Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 4.4. Natural Language Processing (NLP)
- 4.4.1. Natural Language Processing (NLP) Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 4.5. Deep Learning
- 4.5.1. Deep Learning Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 4.6. Computer Vision
- 4.6.1. Computer Vision Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 4.7. Others
- 4.7.1. Others Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 5. U.S. Enterprise Agentic AI Market: Agent System Estimates & Trend Analysis
- 5.1. Segment Dashboard
- 5.2. U.S. Enterprise Agentic AI market: Agent System Movement Analysis, 2024 & 2030 (USD Million)
- 5.3. Single Agent Systems
- 5.3.1. Single Agent Systems Electronics U.S. Enterprise Agentic AI market: Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 5.4. Multi Agent Systems
- 5.4.1. Multi Agent Systems U.S. Enterprise Agentic AI market: Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 6. U.S. Enterprise Agentic AI Market: Type Estimates & Trend Analysis
- 6.1. Segment Dashboard
- 6.2. U.S. Enterprise Agentic AI market: Type Movement Analysis, 2024 & 2030 (USD Million)
- 6.3. Ready-to-Deploy Agents
- 6.3.1. Ready-to-Deploy Agents Electronics U.S. Enterprise Agentic AI market: Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 6.4. Build-Your-Own Agents
- 6.4.1. Build-Your-Own Agents U.S. Enterprise Agentic AI market: Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 7. U.S. Enterprise Agentic AI Market: Application Estimates & Trend Analysis
- 7.1. Segment Dashboard
- 7.2. U.S. Enterprise Agentic AI market: Application Movement Analysis, 2024 & 2030 (USD Million)
- 7.3. Customer Service and Virtual Assistants
- 7.3.1. Customer Service and Virtual Assistants Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.4. Robotics and Automation
- 7.4.1. Robotics and Automation Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.5. Healthcare
- 7.5.1. Healthcare Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.6. Financial Services
- 7.6.1. Financial Services Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.7. Security and Surveillance
- 7.7.1. Security and Surveillance Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.8. Gaming and Entertainment
- 7.8.1. Gaming and Entertainment Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.9. Marketing and sales
- 7.9.1. Marketing and sales Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.10. Human Resources
- 7.10.1. Human Resources Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.11. Legal and compliance
- 7.11.1. Legal and compliance Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
- 7.12. Others
- 7.12.1. Others Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
Chapter 8. Competitive Landscape
- 8.1. Company Categorization
- 8.2. Company Market Positioning
- 8.3. Participant's Overview
- 8.4. Financial Performance
- 8.5. Product Benchmarking
- 8.6. Company Heat Map Analysis
- 8.7. Strategy Mapping
- 8.8. Company Profiles/Listing
- 8.8.1. NVIDIA Corporation
- 8.8.1.1. Participant's Overview
- 8.8.1.2. Financial Performance
- 8.8.1.3. Product Benchmarking
- 8.8.1.4. Recent Developments
- 8.8.2. Accenture
- 8.8.2.1. Participant's Overview
- 8.8.2.2. Financial Performance
- 8.8.2.3. Product Benchmarking
- 8.8.2.4. Recent Developments
- 8.8.3. qBotica
- 8.8.3.1. Participant's Overview
- 8.8.3.2. Financial Performance
- 8.8.3.3. Product Benchmarking
- 8.8.3.4. Recent Developments
- 8.8.4. SAP SE or an SAP affiliate company
- 8.8.4.1. Participant's Overview
- 8.8.4.2. Financial Performance
- 8.8.4.3. Product Benchmarking
- 8.8.4.4. Recent Developments
- 8.8.5. Oracle
- 8.8.5.1. Participant's Overview
- 8.8.5.2. Financial Performance
- 8.8.5.3. Product Benchmarking
- 8.8.5.4. Recent Developments
- 8.8.6. OpenAI
- 8.8.6.1. Participant's Overview
- 8.8.6.2. Financial Performance
- 8.8.6.3. Product Benchmarking
- 8.8.6.4. Recent Developments
- 8.8.7. Capgemini
- 8.8.7.1. Participant's Overview
- 8.8.7.2. Financial Performance
- 8.8.7.3. Product Benchmarking
- 8.8.7.4. Recent Developments
- 8.8.8. Celonis
- 8.8.8.1. Participant's Overview
- 8.8.8.2. Financial Performance
- 8.8.8.3. Product Benchmarking
- 8.8.8.4. Recent Developments
- 8.8.9. Dataiku
- 8.8.9.1. Participant's Overview
- 8.8.9.2. Financial Performance
- 8.8.9.3. Product Benchmarking
- 8.8.9.4. Recent Developments
- 8.8.10. Shield AI
- 8.8.10.1. Participant's Overview
- 8.8.10.2. Financial Performance
- 8.8.10.3. Product Benchmarking
- 8.8.10.4. Recent Developments