According to a new Omdia forecast, the enterprise agentic AI market is poised to grow from US$1.5 billion in 2025 to US$41.8 billion by 2030, dramatically out-stripping traditional generative AI in its growth rate. Omdia finds that while generative AI’s compound annual growth rate (CAGR) between 2022-2027 is projected at about 90%, agentic AI is expected to surge at around 175% CAGR in the 2024-2029 period highlighting strong enterprise demand for automation, productivity, and cost reduction.
Why Agentic AI Is Accelerating Faster
Several factors are driving this shift:
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Prior infrastructure investments in generative AI have created a foundation that makes it easier and faster for enterprises to adopt agentic AI tools.
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Enterprise priorities are shifting more toward automation. Early adopters cite reduced cost and increased employee productivity as key benefits.
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Use cases like automated code development and virtual assistants are among the fastest growing, offering direct, measurable returns.
Key Forecast Figures & Market Projections
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The agentic AI segment is projected to reach 31% of the total generative AI market by 2030, up from only 6% in 2025.
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Among agentic AI use cases, automated code generation is expected to be the largest, reaching approximately US$8.2 billion by 2030, followed by virtual assistants / customer self-support agents at about US$7.7 billion.
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The enterprise market will benefit from faster deployment cycles and quicker ROI thanks to existing generative AI tools and platforms already in place.
What This Means for Businesses & Technology Leaders
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Companies still investing heavily in traditional generative AI need to consider whether they are prepared for the agentic AI wave; failing to adapt may mean missing out on significant efficiency and competitive gains.
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Technology roadmaps should include agentic AI use cases like AI agents, automation of routine workflows, and conversation-driven tools.
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Metrics and investments need updating: success shouldn’t be measured just by novelty of generative AI artifacts, but by real automation, cost savings, and productivity improvements.
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Risk and governance are still important: as agentic AI grows, ensuring safety, transparency, and reliability remains crucial.
Conclusion
Omdia’s analysis makes clear that agentic AI isn’t just a subset of generative AI—it is outpacing it in terms of growth, adoption, and enterprise value. With strong drivers like automation, infrastructure readiness, and measurable ROI, agentic AI is set to take a much larger share of the AI landscape by 2030. Enterprises that adapt early will likely benefit the most.
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