The Trends and Drivers 2026: The Global Agentic AI Economy report provides a strategic qualitative review of the emerging agentic AI economy as enterprise AI moves from content generation toward controlled, multi-step execution across business workflows, software environments, service operations, IT, cybersecurity, customer support, procurement, finance and knowledge work.
This report is designed for decision-makers seeking a clear view of how agentic AI is developing as a new enterprise execution layer. It evaluates the market across foundation models, cloud infrastructure, agent-development platforms, enterprise software, workflow orchestration, automation, tool use, data integration, identity, evaluation, observability, cost control, AI governance and professional services. The analysis distinguishes practical agentic systems from conventional chatbots and deterministic robotic process automation, focusing on agents that can pursue objectives, call tools, retain context and complete bounded workflows under defined controls.
The report highlights that the agentic AI economy is still in an early production phase. Enterprise experimentation is broad, while scaled deployment remains concentrated in narrower workflow areas where data are available, permissions can be constrained and actions can be reviewed or reversed. The report explains why near-term adoption is likely to progress from assistance to bounded action and then to coordinated execution, rather than immediately shifting to fully autonomous enterprise operations.
This product will be delivered within 2 business days.
This report is designed for decision-makers seeking a clear view of how agentic AI is developing as a new enterprise execution layer. It evaluates the market across foundation models, cloud infrastructure, agent-development platforms, enterprise software, workflow orchestration, automation, tool use, data integration, identity, evaluation, observability, cost control, AI governance and professional services. The analysis distinguishes practical agentic systems from conventional chatbots and deterministic robotic process automation, focusing on agents that can pursue objectives, call tools, retain context and complete bounded workflows under defined controls.
The report highlights that the agentic AI economy is still in an early production phase. Enterprise experimentation is broad, while scaled deployment remains concentrated in narrower workflow areas where data are available, permissions can be constrained and actions can be reviewed or reversed. The report explains why near-term adoption is likely to progress from assistance to bounded action and then to coordinated execution, rather than immediately shifting to fully autonomous enterprise operations.
This product will be delivered within 2 business days.
Table of Contents
- Executive Summary
- Market Overview
- Agentic AI Market Definition and Scope
- The Interconnected Agentic AI Stack
- Models, Compute, Data, Tools, Orchestration, Applications and Assurance
- Key Industry Trends and Demand Drivers
- Technology and Service Evolution
- Business Models and Economics
- Competitive Landscape and Key Industry Players
- Regional Assessment
- Government Strategies, Regulation and AI Governance
- Market Challenges and Execution Constraints
- Strategic Opportunities
- Industry Growth Outlook through 2030
Executive Summary
The global agentic AI economy is emerging as enterprise AI moves beyond retrieval, drafting and question-answering into controlled execution across digital workflows. The report explains how agentic AI spans models, compute, data, tools, orchestration, enterprise applications, automation, security, assurance and professional services. Adoption is expanding, but the market remains early. The strongest production use cases are concentrated in digital, repetitive and reversible workflows such as IT operations, cybersecurity, customer support, software engineering, research, employee support and internal service processes. The strategic shift is the creation of an execution layer that can connect data, software and human approvals, with agents handling bounded tasks while people retain accountability for sensitive decisions, exceptions and high-consequence actions.The report highlights that growth through 2030 will be shaped by control, integration and economics rather than technical possibility alone. Agentic AI can create material workflow value, but organisations must solve data readiness, tool access, identity, evaluation, observability, cost attribution, security, process ownership and governance before scaling. Competition will remain structurally plural, with model providers, cloud platforms, enterprise software vendors, automation companies, assurance providers and systems integrators competing across different layers of the stack. The most durable positions will sit with providers that control trusted workflow context, support interoperable agent estates, prove task completion, manage fully loaded workflow cost and enable safe delegation under clear human accountability.
