Agentic AI is experiencing significant growth as the US and China lead the global race in adopting autonomous systems, transitioning from task-based automation to decision-driven processes. According to GlobalData, the market is projected to grow at a 50.6% compound annual growth rate from 2024 to 2029, reaching $45.4 billion. This growth is driven by enterprise demand for autonomous decision-making and scalable AI infrastructure, with the Asia-Pacific region emerging as the largest market.
Introduction to Agentic AI
Agentic AI is entering a phase of hyper-growth as enterprises worldwide shift from traditional task-based automation to more advanced autonomous, decision-driven systems. This transition is being led by the United States and China, who are at the forefront of this technological race. According to a report by GlobalData, a prominent data and analytics company, this new class of self-correcting digital workers is set to redefine organizational approaches to scale, agility, and operational intelligence.
Market Projections and Growth Drivers
GlobalData’s report, titled “Market Opportunity Forecasts to 2029: Agentic AI,” forecasts that the global agentic AI market will grow at a compound annual growth rate (CAGR) of 50.6% from 2024 to 2029, reaching a market value of $45.4 billion by 2029. This rapid growth is driven by increasing enterprise demand for autonomous decision-making capabilities, multi-agent orchestration, and scalable cloud-native AI infrastructures. Organizations are accelerating their deployment of these systems from pilot phases to full production-grade systems.
From Generative AI to Autonomous Agents
While generative AI (GenAI) has revolutionized content creation, agentic AI is transforming enterprise action. Companies are moving beyond static, rule-based automation to adopt autonomous systems that plan, reason, self-correct, and coordinate complex workflows with minimal human intervention. Advances in orchestration engines, long-context large language models (LLMs), and memory-driven architectures are enabling these agents to execute comprehensive end-to-end business processes.
Rena Bhattacharyya, Chief Analyst and Practice Lead for Enterprise Technology & Services at GlobalData, notes that agentic AI is pushing enterprises beyond static automation toward systems that can plan, reason, and self-correct. This evolution is crucial as organizations seek tools that not only execute tasks but also handle complexity, learn from interactions, and drive operational agility at scale.
Regional Market Dynamics
The Asia-Pacific region has emerged as the largest market for agentic AI, with projected revenue of $3.0 billion by 2025, surpassing North America’s $2.6 billion. This growth is driven by government-backed AI initiatives, manufacturing automation, and widespread deployment in sectors such as financial services, the public sector, and healthcare. Countries like China, Japan, India, and South Korea are rapidly building AI infrastructure, supported by national LLM programs and emerging AI innovation zones.
Meanwhile, the United States remains a global innovation hub for agentic AI, with expected revenue of $2.3 billion in 2025. Leading enterprises and hyperscale technology companies are replacing traditional robotic process automation (RPA) with goal-driven, self-adapting agent systems across various core operations, including IT management, customer service, supply chain, and financial operations.
Business Impact and Future Outlook
Rohit Sharma, Lead Analyst, Technology at GlobalData, highlights that enterprises are no longer merely piloting agentic systems but are actively retiring rule-based automation in favor of autonomous digital colleagues. This shift is driven by the clear business value observed by early adopters, including up to 61% faster revenue growth in automated units and, in some cases, achieving 90% touchless operations across entire workflows.
As enterprises worldwide prioritize agility, continuous decision-making, and workforce augmentation, agentic AI is becoming a foundational pillar of digital transformation strategies. This sets the stage for widespread mainstream adoption through 2026 and beyond, as noted by Bhattacharyya.
