The global agentic AI market size is calculated at USD 7.55 billion in 2025 and is forecasted to reach around USD 199.05 billion by 2034, accelerating at a CAGR of 43.84% from 2025 to 2034. The North America market size surpassed USD 2.42 billion in 2024 and is expanding at a CAGR of 43.97% during the forecast period. The market sizing and forecasts are revenue-based (USD Million/Billion), with 2024 as the base year.
The global agentic AI market size accounted for USD 5.25 billion in 2024 and is predicted to increase from USD 7.55 billion in 2025 to approximately USD 199.05 billion by 2034, expanding at a CAGR of 43.84% from 2025 to 2034. The market is growing due to rapid integration of AI in various industries, such as finance, transport, defense, and healthcare, due to their ability to fully automate tasks without human interaction.
The U.S. agentic AI market size was exhibited at USD 1.69 billion in 2024 and is projected to be worth around USD 44.10 billion by 2034, growing at a CAGR of 44.10% from 2025 to 2034.
What made North America the dominant region in the agentic AI market?
North America dominated the agentic AI market by holding the largest market share of 46% in 2024. This is mainly due to its robust technology landscape and significant investments in agentic AI systems across industries like finance, healthcare, retail, and telecom. AI agents are used for task automation and customer service. The U.S. government is also promoting agentic AI for defense and security applications, providing intelligence support for critical tasks. Moreover, increased investment in AI research and development is fueling innovation and market expansion.
What factors are influencing the growth of the agentic AI market in Asia Pacific?
Asia Pacific is expected to witness the fastest growth during the foreseeable period of 2025-2034. This growth is driven by the region's increasing digital infrastructure and government support for AI development across countries like India, China, and Japan. Start-ups and tech giants such as Alibaba, Baidu, and Tencent are developing their own AI environments supported by AI agents. Regional start-ups are implementing AI agents in various domains such as healthcare, finance, transportation, and smart city projects, further accelerating the regional market growth.
Rising digitalization in the financial sector opens up new growth avenues for market expansion in the region. Agentic AI can be used for fraud detection, risk management, and algorithmic trading, offering significant opportunities in the financial sector. Moreover, the development of smart cities contributes to market growth. Agentic AI can be integrated into smart city infrastructure for traffic management, energy optimization, and public safety.
Agentic AI refers to artificial intelligence systems that exhibit autonomous decision-making capabilities, goal-directed behaviour, and long-term planning like human agents. Unlike traditional AI, which reacts to specific inputs, agentic AI proactively initiates actions, adapts to new environments, and operates with a degree of self-governance. These systems are designed to understand goals, reason through complex tasks, learn from experience, and self-correct without requiring explicit instructions at every step. Applications span from autonomous robotics and intelligent assistants to dynamic process optimization in industrial and enterprise settings.
What is difference between Agentic AI and Generative AI?
| Feature | Agentic AI | Generative AI |
| Primary function | Goal-oriented action & decision-making | Content generation (text, code, images, etc.) |
| Autonomy | High: Operates with minimal human oversight | Variable: May require user prompts or guidance |
| Learning | Reinforced Learning: Improves through experience | Data-driven learning: Learns from existing data |
| Task complexity | High: Solves complex, multi-step problems | Moderate: Generates content but doesn’t handle complex tasks autonomously |
| Report Coverage | Details |
| Market Size by 2034 | USD 199.05 Billion |
| Market Size in 2025 | USD 7.55 Billion |
| Market Size in 2024 | USD 5.25 Billion |
| Market Growth Rate from 2025 to 2034 | CAGR of 43.84% |
| Dominating Region | North America |
| Fastest Growing Region | Asia Pacific |
| Base Year | 2024 |
| Forecast Period | 2025 to 2034 |
| Segments Covered | Application Domain, Technology Stack, End-User Industry, Deployment Mode, Intelligence Level, and Region |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
Increasing shift toward open-source models
The growth of the agentic AI market is significantly driven by the growing preference for open-source models, contrasting with the proprietary models often controlled by major tech companies. An open-source model is favoured by business-to-business companies owing to their operational costs. This is highly applicable for open-source models such as Anthropic and MISTral. Smaller models are increasingly used for well-defined and specific tasks. Companies can easily fine-tune AI models to minimize over-dependency on substantial third-party APIs. Also, smaller and open-source models have the potential to be fine-tuned for specific business-related tasks, which is highly beneficial for developers to adopt new perspectives, expanding market growth.
Moreover, open-source models are accessible and customizable, allowing developers to adapt them for specific tasks, leading to diverse applications. This contrasts with proprietary models, which can be restrictive. The collaborative nature of open-source projects accelerates development, as developers worldwide contribute to improving and expanding the capabilities of these models. This, in turn, lowers the barrier to entry for businesses, encouraging wider adoption and driving market expansion.
Over-dependency with the potential threat of job displacement
Despite having numerous benefits, over-dependency on agentic AI, coupled with the potential for job displacement, hinders market growth by creating several challenges. Public and governmental apprehension regarding job security can lead to stricter regulations and reduced investment in agentic AI technologies. The need for retraining and workforce adaptation also adds to the cost and complexity of implementation. Moreover, ethical concerns about fairness and bias in AI systems can erode public trust, further slowing market expansion. Therefore, addressing these issues through responsible development, transparent practices, and proactive workforce strategies is crucial for sustainable growth in the agentic AI market.
How will AI agents help connect with the physical world?
A significant opportunity for the market lies in the integration of AI agents with the physical world. AI agents are increasingly being deployed with Internet of Things (IoT) devices and physical world environments, such as homes and offices, where AI agents can work without human intervention. A real-world example includes collaborations between tech giants like NVIDIA and GE Healthcare on agentic robotic systems for X-ray and ultrasound technologies. These AI agents analyze medical imaging and interact with the physical world, creating lucrative opportunities for substantial market growth in the foreseeable future.
Why did the cognitive agents segment dominate the agentic AI market in 2024?
The cognitive agents (virtual assistants & co-pilots) segment dominated the market with the largest market share of 34% in 2024. This dominance stems from their ability to make autonomous decisions without human interaction, thereby reducing human workload. Designed to mimic human cognitive processes, these agents utilize reasoning, logic, and decision-making based on existing data to execute tasks with precise planning. This makes cognitive agents widely applicable in customer relationship management, enterprise resource planning, and supply chain management.
The autonomous systems segment is expected to witness the fastest growth during the forecast period. This is primarily due to its increasing recognition across various industries for its ability to manage complex situations with minimal human interaction, thereby boosting efficiency. Another key driver for the segment's growth is the development of advanced foundation models like GPT-4, Gemini, and Claude, which facilitate the sophisticated building of AI agents.
How does the learning & adaptation frameworks segment lead the Agentic AI market?
The learning & adaptation frameworks segment led the market while holding the largest share of 29% in 2024. Learning and adaptation frameworks are crucial because they enable AI agents to make data-driven decisions and enhance their performance over time, allowing them to operate effectively in complex environments across various industries. These frameworks are essential for building effective and scalable AI agent systems. Machine learning and deep learning are prime examples of these frameworks, increasingly used to build AI agents applicable in smart cities, manufacturing and logistics hubs, healthcare, and the financial sector, thereby enhancing their capabilities.
The planning & goal management engines segment is expected to grow at the fastest CAGR during the projection period. This growth is driven by factors such as complex task automation, workflow optimization, and a goal-oriented approach that enhances Return on Investment (ROI). This is made possible through the integration of technologies like Large Language Models (LLMs), Robotic Process Automation (RPA), and autonomous tool orchestration, resulting in highly adaptive and goal-oriented systems.
What made technology & software the dominant segment in the market?
The technology & software segment dominated the agentic AI market with the largest market share of 38% in 2024. This dominance is attributed to the direct impact of AI agents on automating tasks like code generation, bug finding, and optimization, which accelerates development cycles and reduces costs. The technology & software sector provides essential tools, frameworks, and platforms for building and deploying agentic AI systems, contributing significantly to its growth. Moreover, the potential of agentic AI to create new business models and expand offerings across various sectors, aligning with consumer expectations, is a key driver for this segment's expansion.
Moreover, agentic AI is widely used in tech and software development for intelligent process automation, software testing, and customer support. The segment's growth is fueled by the need for efficient, scalable solutions, with companies using Agentic AI to automate tasks, improve decision-making, and enhance customer experiences.
The healthcare & life sciences segment is expected to witness the fastest growth over the forecast period, driven by agentic AI's capacity to cut costs and reduce staff burnout through automation. This technology streamlines administrative tasks and optimizes resource allocation. Furthermore, Agentic AI accelerates drug discovery by offering quick, precise simulations, which directly address the time-consuming and intricate processes inherent in traditional methods.
Why did the cloud-based agentic AI segment dominate the market in 2024?
The cloud-based agentic AI segment dominated the agentic AI market, holding the largest market share of 62% in 2024, thanks to its scalability and flexibility. Cloud deployment enhances collaboration, accessibility, and focus on core business processes. Cloud providers handle infrastructure complexities, allowing businesses to concentrate on innovative AI solutions. These platforms also facilitate data sharing and knowledge management, boosting overall efficiency for Agentic AI deployments.
The hybrid architectures segment is expected to expand at a significant CAGR in the upcoming period. This is mainly due to its flexible method of controlling the distribution of the workspace, which allows for tailoring tasks and forwarding others to autonomous systems. This is highly effective for time-sensitive and mission-critical tasks, ensuring high consistency.
How does the hybrid (BDI) agents segment dominate the agentic AI market?
The hybrid agents segment dominated the market with the largest share of 41% in 2024. This dominance is due to its combination of traditional programming with large language models, enabling precise execution and thoughtful decision-making. It allows for security protocols and calculations to be handled by conventional programming while leveraging LLMs for adaptability and dynamic responses, showcasing its ability to handle a diverse array of tasks.
The deliberative agents segment is expected to witness the fastest growth during the foreseeable period of 2025-2034. The growth of the segment is driven by their sophisticated decision-making capabilities, which involve analyzing options, assessing potential outcomes, and selecting the best actions for complex tasks. This approach makes them highly applicable in real-world applications such as supply chain management, finance, healthcare, and smart home systems.
By Application Domain
By Technology Stack
By End-User Industry
By Deployment Mode
By Intelligence Level
By Region
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