Agentic Artificial Intelligence (AI) is rapidly moving from early experimentation toward mainstream adoption, with global demand for autonomous, decision-capable systems now entering a hyper-growth phase. The technology, designed to plan, reason, and self-correct without constant human input, is redefining how businesses approach automation, operational agility, and large-scale digital transformation.
GlobalData forecasts that the global agentic AI market will expand at a Compound Annual Growth Rate (CAGR) of 50.6% between 2024 and 2029, reaching an estimated $45.4 billion by 2029, as enterprises transition their deployments from pilot projects to full-scale production systems. This rapid acceleration has been fueled by growing enterprise demand for autonomous decision-making, multi-agent orchestration, and scalable cloud-native AI infrastructure.
Agentic AI represents a leap beyond the earlier phases of artificial intelligence. While generative AI revolutionized content creation, agentic AI transforms action, enabling autonomous systems to manage complex business workflows and make logic-based decisions with minimal human oversight. This evolution is underpinned by advances in orchestration engines, long-context large language models (LLMs), and memory-driven AI architectures that help these systems execute multi-step processes end-to-end.
“Agentic AI is moving enterprises beyond static, rule-based automation toward systems that can plan, reason, and self-correct,” said Rena Bhattacharyya, Chief Analyst and Practice Lead for Enterprise Technology and Services at GlobalData. “This evolution matters because organizations are no longer looking for tools that simply execute tasks— they need autonomous digital workers that can handle complexity, learn from interactions, and drive real operational agility at scale.”
Global Leaders, Regional Growth
According to GlobalData’s analysis, the Asia-Pacific region has emerged as the largest agentic AI market in 2025, generating about $3.0 billion in revenue, edging ahead of North America’s $2.6 billion. Government-backed AI initiatives, manufacturing automation drives, and robust adoption across financial services, public sector, and healthcare have propelled this growth. Countries such as China, Japan, India, and South Korea are rapidly building AI innovation ecosystems supported by national LLM programs and AI research hubs.
The United States remains a critical innovation hub, with early-mover enterprises and leading hyperscalers embedding agentic capabilities across core operations such as IT management, customer service, supply chain, and finance, reinforcing its position at the forefront of autonomous AI development.
Rohit Sharma, Lead Analyst of Technology at GlobalData, notes the paradigm shift among enterprises: “Enterprises are no longer piloting agentic systems but actively retiring rule-based automation in favor of autonomous digital colleagues.”
Enterprise AI Adoption Trends and Business Impact
The agentic AI surge reflects broader trends in enterprise AI adoption. According to McKinsey, 88% of organizations use AI in at least one business function, signaling that AI is becoming ubiquitous across corporate operations, not just in isolated use cases. Meanwhile, separate surveys indicate that AI adoption across global companies has risen sharply to 78% in 2025, with many firms progressing from basic usage to advanced AI integration.
Enterprises are also beginning to quantify business benefits. Analysts report measurable productivity gains and efficiency improvements when AI is integrated into workflows: workers using AI tools report time savings equivalent to 40–60 minutes per day, boosting organizational throughput, according to OpenAI. These performance improvements underscore why companies are shifting AI budgets from experimentation to growth and scaling of autonomous systems.
Market research suggests that agentic AI adoption is already underway, with around 29% of organizations claiming to use AI agents for autonomous automation and another 38% planning deployments within the next 12 months. This pattern reinforces a broader industry trend where enterprises are increasingly looking beyond basic automation and generative capabilities toward systems that can enhance decision-making and drive value across complex processes.
Beyond Task Automation
This shift from Robotic Process Automation (RPA) and rule-based AI to agentic systems aligns with broader automation trends. Traditional RPA solutions, which automate repetitive tasks, continue to grow, but enterprise leaders now seek AI that can interpret, adapt, and collaborate across systems. Analysts describe this blend as “intelligent automation,” where AI interprets and orchestrates workflows and RPA executes tasks, resulting in exponential improvements in efficiency and customer experience.
Beyond internal operations, agentic AI is influencing external functions. A Morgan Stanley analysis predicts that by 2030, nearly half of U.S. online shoppers will use AI agents for personalised shopping assistance, potentially adding $115 billion to U.S. e-commerce revenue, highlighting agentic AI’s potential impact beyond traditional enterprise back-office functions.
Risks and Adoption Challenges
Despite rapid interest, experts caution that not all agentic AI initiatives will succeed. A Gartner analysis earlier this year 2025 warned that over 40% of agentic AI projects may be canceled by 2027 due to unclear business value, high costs, and premature deployment, suggesting that careful planning and governance are crucial for scaling.
The transition to autonomous AI also raises questions around trust, governance, and integration. As agentic systems assume more decision responsibilities, enterprises must ensure robust data infrastructure, model governance, and ethical frameworks to mitigate risks and sustain enterprise confidence.
Outlook
GlobalData predicts that as enterprises prioritise agility, continuous decisioning, and workforce augmentation, agentic AI will become a foundational pillar of digital transformation strategies, ushering in widespread adoption through 2026 and beyond.
With AI budgets expanding, core technologies maturing, and measurable business impact emerging, agentic AI is positioning itself as the next evolutionary step in enterprise intelligence — one that transforms automation from task execution to autonomous strategic action.
