The global agentic AI market report’s research methodology involved extensive secondary sources, directories, and various reputed open-source databases to identify and collect information useful for this technical and market-oriented study. In-depth interviews were conducted with various primary respondents, including agentic AI software providers, agentic AI service providers, embodied AI providers, individual end users, and enterprise end users; high-level executives of multiple companies offering agentic AI solutions; and industry consultants to obtain and verify critical qualitative and quantitative information and assess the market prospects and industry trends.
Secondary Research
Several secondary sources were referred to identify and gather information for the study during the secondary research process. These included annual reports; press releases and investor presentations of companies; white papers; certified publications such as Journal of Artificial Intelligence Research (JAIR), Transactions of the Association for Computational Linguistics (TACL), Journal of Machine Learning Research (JMLR), IEEE Transactions on Neural Networks and Learning Systems, Nature Machine Intelligence, Artificial Intelligence Journal (AIJ), ACM Transactions on Information Systems (TOIS), Pattern Recognition Journal, and Neural Computation (MIT Press); and articles from recognized associations and government publishing sources including but not limited to Association for Computational Linguistics (ACL), International Association for Machine Learning (IAMLE), Artificial Intelligence Industry Association (AIIA), International Speech Communication Association (ISCA), Natural Language Processing Association (NLPA), Machine Learning and AI Industry Research Association (MLAIRA), and AI Infrastructure Alliance (AIIA).
The secondary research was used to obtain key information about the industry’s value chain, the market’s monetary chain, the overall pool of key players, market classification and segmentation according to industry trends to the bottom-most level, regional markets, and key developments from the market and technology-oriented perspectives.
Primary Research
In the primary research process, diverse stakeholders from the supply and demand sides of the agentic AI ecosystem were interviewed to gather qualitative and quantitative insights specific to this market. From the supply side, key industry experts, such as chief executive officers (CEOs), vice presidents (VPs), marketing directors, technology & innovation directors, and technical leads from vendors offering agentic AI software & services, were consulted. Additionally, system integrators, service providers, and IT service firms that implement and support agentic AI were included in the study. Input was gathered from IT decision-makers, infrastructure managers, and business leaders of major enterprise end users to grasp user perspectives and adoption challenges across targeted industries.
The primary research ensured that all crucial parameters affecting the agentic AI market, from technological advancements and evolving use cases (workflow automation, inspection & monitoring, navigation & mobility, planning & decision support, etc.) to regulatory and compliance needs (GDPR, CCPA, Europe AI Act, AIDA, etc.), were considered. Each factor was thoroughly analyzed, verified through primary research, and evaluated to obtain precise quantitative and qualitative data for this market.
Once the initial market engineering phase was completed, including detailed calculations for market statistics, segment-specific growth forecasts, and data triangulation, an additional round of primary research was undertaken. This step was crucial for refining and validating critical data points, such as agentic AI offerings (software & services), industry adoption trends, the competitive landscape, and key market dynamics such as demand drivers (rapid adoption of LLM orchestration frameworks accelerating autonomous agent deployment, advances in edge AI and neuromorphic chips enabling real-time autonomy in physical systems, rising industrial use of autonomous robotics boosting efficiency in logistics, agriculture, and field services, and growing demand for cost-effective, continuous operations driving autonomous system investments), challenges (fragmented autonomy stacks and missing interoperability standards restricting system integration, legal and ethical gaps around autonomous actions delaying adoption in regulated sectors), and opportunities (autonomous agents scaling across BFSI, telecom, and manufacturing for digital transformation, expanding human-machine collaboration via agent-augmented collaborative robots [cobots], and emerging AI regulations unlocking new markets for compliant autonomy).
In the complete market engineering process, the top-down and bottom-up approaches and several data triangulation methods were extensively used to perform the market estimation and market forecast for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analysis was performed on the complete market engineering process to record the critical information/insights throughout the report.
Note: Three tiers of companies are defined based on their total revenue as of 2024; tier 1 = revenue more than USD 500
million, tier 2 = revenue between USD 500 million and 100 million, tier 3 = revenue less than USD 100 million
Source: MarketsandMarkets Analysis
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
The top-down and bottom-up approaches were employed to estimate and forecast the agentic AI market and its dependent submarkets. This multi-layered analysis was further reinforced through data triangulation, incorporating primary and secondary research inputs. The market figures were also validated against the existing MarketsandMarkets repository for accuracy.
Agentic AI Market : Top-Down and Bottom-Up Approach
Data Triangulation
After determining the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
Agentic AI refers to autonomous systems that can perceive context, make decisions, and execute multi-step actions to achieve defined goals, often with minimal human intervention. These agents operate across digital and physical environments, guided by software capable of planning, tool use, adaptive reasoning, and collaboration with other agents or systems. Whether applied in virtual workflows or embedded within embodied systems such as vehicles or robotics, the emphasis is on the agentic AI software orchestration layer that enables situational awareness, autonomy, and dynamic behavior across complex, real-world tasks.
Stakeholders
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Agentic AI software developers
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Agentic AI infrastructure providers
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Agentic AI integrated service providers
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Agentic AI training dataset providers
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Core data service providers
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Business analysts
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Cloud service providers
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Consulting service providers
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Enterprise end users
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Distributors and value-added resellers (VARs)
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Government agencies
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Independent software vendors (ISV)
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Managed service providers
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Market research and consulting firms
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Support & maintenance service providers
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System integrators (SIs)/migration service providers
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Language service providers
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Technology providers
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Academia & research institutions
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Investors & venture capital firms
Report Objectives
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To define, describe, and forecast the agentic AI market, by offering (software and services), agent role, technology, application, and end user
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To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing market growth
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To analyze the micro markets concerning individual growth trends, prospects, and their contribution to the total market
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To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the agentic AI market
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To assess market opportunities and provide details of the competitive landscape for stakeholders and market leaders
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To forecast the market size of segments for North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America
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To profile the key players and comprehensively analyze their market ranking and core competencies
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To analyze competitive developments, such as partnerships, product launches, and mergers & acquisitions, in the agentic AI market
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To analyze the impact of recession in the agentic AI market across all regions
Available Customizations
With the given market data, MarketsandMarkets offers customizations to meet the company’s specific needs.
Product Analysis
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Product matrix provides a detailed comparison of the product portfolio of each company.
Geographic Analysis as per Feasibility
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Further breakup of the North American market for Agentic AI
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Further breakup of the European market for Agentic AI
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Further breakup of the Asia Pacific market for Agentic AI
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Further breakup of the Middle Eastern & African market for Agentic AI
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Further breakup of the Latin American market for Agentic AI
Company Information
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Detailed analysis and profiling of additional market players (up to five)
Growth opportunities and latent adjacency in Agentic AI Market