에이전트형 AI 프레임워크 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the agentic AI frameworks market size is expected to grow from USD 2.99 billion in 2025 to USD 4.11 billion in 2026 and is forecast to reach USD 19.32 billion by 2031 at 36.3% CAGR over 2026-2031.

This report is Segmented by Framework Type (Open-Source Frameworks, and Proprietary Frameworks), Deployment Mode (Cloud-Hosted, and More), Organization Size (Large Enterprises, and Small and Medium Enterprises), End-User Industry (ICT and Software Development, Healthcare and Life Sciences, Retail and E-Commerce, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Agentic AI Frameworks Market Trends and Insights

Growing Demand for Autonomous Agents in Enterprise Workflows

Enterprise demand in the agentic AI frameworks market has moved beyond isolated chatbot pilots and into production systems that coordinate work across teams. IBM reported in May 2026 that 82% of C-suite executives identified functional silos as the main barrier to AI value extraction, and 60% planned next-generation delivery structures in which AI agents coordinate workflows across departments. That shift changes buying behavior because enterprises now want memory, tool use, approvals, and escalation paths in one governed flow. The value case is strongest where agents can manage repetitive handoffs between departments instead of answering one prompt at a time. This is also pushing organizations to redesign workflows before deployment, since agent performance depends on how tasks, context, and accountability move across the business. Projects that add agents to unchanged processes face a higher cancellation risk, so workflow architecture is becoming nearly as important as framework selection in the agentic AI frameworks market.

Rapid Advances in Generative AI Model Capabilities

Rapid model progress is widening the production scope of the agentic AI frameworks market. Frontier models now combine stronger tool use with longer context windows, reducing the manual prompting required to slow production deployment. Microsoft said its April 2026 release of GPT-5.5 on Microsoft Foundry was designed for more reliable agentic execution, stronger long-context reasoning, and better token efficiency. Microsoft also made Claude Opus 4.6 available in Foundry, with a 1-million-token context window for coding, agents, and enterprise workflows. These gains matter because they make multi-step orchestration more stable and lower the cost penalty that once limited agent pipelines to narrow pilots. Google DeepMind noted that compute available for the largest training runs rose by around 300,000x between 2012 and 2018 and continued to grow at an annual pace of around 4x through 2024, which helps explain why capability ceilings and efficiency are moving together.

Persistent Concerns Around AI Safety and Alignment

Safety and alignment remain a structural brake on the agentic AI frameworks market because multi-agent errors can compound across memory, tools, and chained decisions. The World Economic Forum said that evaluation and governance for AI agents still need stronger foundations, especially as systems operate with greater autonomy within business processes. The risk is not limited to wrong answers, since agents can also escalate privileges, expose data, or trigger actions that are hard to trace after several handoffs. This keeps regulated buyers focused on audit trails, human oversight, and runtime controls before they scale deployment. The August 2026 activation of the EU AI Act high-risk provisions adds another layer of caution for enterprises that need conformity documentation and incident logging. Until security teams can monitor agent behavior with the same confidence they apply to other enterprise systems, some high-value deployments in the agentic AI frameworks market will move more slowly than the technology itself.

Other drivers and restraints analyzed in the detailed report include:

1. Rising Investments by Big Tech and Venture Capital
2. Scalability Benefits of Framework-Agnostic Tooling
3. Lack of Skilled Workforce for Multi-Agent Orchestration

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Open-source frameworks held 63.81% of the agentic AI frameworks market share in 2025. That lead came from developers' preference for composability, auditability, and broad integration across models, vector stores, and enterprise data systems. LangChain said in October 2025 that LangChain and LangGraph reached 90 million combined monthly downloads and that 35% of Fortune 500 companies used its services. The same update pointed to production use across large enterprises, which helps explain why open-source tools still shape engineering standards even when buyers later purchase commercial support.

Open-source leadership does not remove its own friction, since rapid release cycles and breaking API changes can create internal rework for teams already in production. That instability is helping proprietary vendors close the production gap, and proprietary frameworks are projected to grow at a 36.68% CAGR through 2031. Microsoft said the Foundry Agent Service supports LangGraph, the Claude Agent SDK, and the OpenAI Agents SDKs in a single, governed runtime, demonstrating how enterprise vendors are packaging framework flexibility within managed environments. In practice, the agentic AI frameworks market is separating into open-source tools that lead experimentation and proprietary platforms that gain ground when buyers need service levels, auditability, and centralized controls.

Cloud-hosted deployments held 71.32% of the agentic AI frameworks market in 2025. Cloud remains the default because managed services shorten setup time, provide fast access to frontier models, and scale with variable agent workloads. Google Cloud launched the Gemini Enterprise Agent Platform in April 2026, including Agent Studio, Agent Development Kit, Agent Runtime, Agent Identity, and Agent Gateway, demonstrating how platform vendors are packaging development and governance as a single service. Microsoft made similar moves by expanding Foundry and Microsoft 365 agent tooling, reinforcing its cloud leadership in rapid iteration and standard business workflows.

The agentic AI frameworks market size for on-premises and edge deployments is projected to expand at 36.63% CAGR through 2031. That growth reflects needs that public cloud cannot fully solve, including data sovereignty, low-latency inference, and protection of proprietary workflows. Smaller task-specific models and quantized variants are narrowing the capability gap between local and hosted deployments, reducing one of the old barriers to edge adoption. The result is an architecture split in which enterprises keep development and routine workflows in the cloud, while moving sensitive or time-critical use cases to on-premises and edge environments.

Geography Analysis

North America held 37.51% of the global agentic AI frameworks market share in 2025. The United States remains the single largest national market because it combines the deepest enterprise AI budgets, the highest vendor concentration, and the closest links to hyperscaler ecosystems. This creates a fast feedback loop among foundation model providers, cloud platforms, and enterprise buyers, enabling the region to deploy new orchestration tools to production faster than peers. Canada adds research depth through its AI clusters, while Mexico is gaining relevance as a near-shore deployment base for bilingual operational workflows.

Europe accounted for a substantial share of the global agentic AI frameworks market in 2025. Demand in Germany, the United Kingdom, and France centers on production-grade orchestration for industrial processes, enterprise software workflows, and regulated business functions. Procurement in the region places unusual emphasis on data sovereignty, private cloud deployment, and audit-ready documentation, which pushes buyers toward more structured platform choices. The coming enforcement of high-risk AI rules is not removing demand, but it is redirecting spend toward frameworks that can document actions, controls, and human oversight with less customization.

The agentic AI frameworks market in Asia-Pacific is projected to grow at a 37.28% CAGR through 2031. China is accelerating adoption through national targets for AI agent penetration and industrial deployment, while Japan is using its May 2026 AI Promotion Act to support a risk-based, yet innovation-oriented, path to production. India benefits from deep software engineering expertise and a large services base, which supports open-source adoption in outsourcing and financial workflows. The Middle East is building momentum through national AI programs in the United Arab Emirates and Saudi Arabia, while South America remains centered on Brazil and Argentina as early entry points. Across these regions, sovereignty rules and local operating needs are not simply barriers; they are steering the agentic AI frameworks market toward more auditable and locally adaptable deployment models.

1. OpenAI LLC
2. Microsoft Corporation
3. Google LLC
4. Anthropic PBC
5. Meta Platforms Inc.
6. Amazon.com Inc.
7. Hugging Face Inc.
8. NVIDIA Corporation
9. IBM Corporation
10. Salesforce Inc.
11. Cohere Inc.
12. Adept AI Labs Inc.
13. Replit Inc.
14. Pinecone Systems Inc.
15. LangChain Inc.
16. Inflection AI Inc.
17. Mistral AI SAS
18. LangFuse GmbH
19. Conductor Technologies Inc.
20. Cerebras Systems Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Growing Demand for Autonomous Agents in Enterprise Workflows
  • 4.2.2 Rapid Advances in Generative AI Model Capabilities
  • 4.2.3 Rising Investments by Big Tech and Venture Capital
  • 4.2.4 Scalability Benefits of Framework-Agnostic Tooling
  • 4.2.5 Emergence of AI Function Calling Standards
  • 4.2.6 Integration of Agentic Frameworks into Low-Code Platforms
• 4.3 Market Restraints
  • 4.3.1 Persistent Concerns Around AI Safety and Alignment
  • 4.3.2 Lack of Skilled Workforce for Multi-Agent Orchestration
  • 4.3.3 High Compute Costs for Large-Scale Agent Simulations
  • 4.3.4 Fragmentation Due to Divergent Prompt Engineering Dialects
• 4.4 Impact of Macroeconomic Factors on the Market
• 4.5 Industry Value Chain Analysis
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power of Suppliers
  • 4.8.2 Bargaining Power of Buyers
  • 4.8.3 Threat of New Entrants
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Framework Type
  • 5.1.1 Open-Source Frameworks
  • 5.1.2 Proprietary Frameworks
• 5.2 By Deployment Mode
  • 5.2.1 Cloud-Hosted
  • 5.2.2 On-Premises and Edge
• 5.3 By Organization Size
  • 5.3.1 Large Enterprises
  • 5.3.2 Small and Medium Enterprises
• 5.4 By End-User Industry
  • 5.4.1 ICT and Software Development
  • 5.4.2 Financial Services
  • 5.4.3 Healthcare and Life Sciences
  • 5.4.4 Manufacturing and Industrial
  • 5.4.5 Retail and E-Commerce
  • 5.4.6 Media and Entertainment
• 5.5 By Geography
  • 5.5.1 North America
    • 5.5.1.1 United States
    • 5.5.1.2 Canada
    • 5.5.1.3 Mexico
  • 5.5.2 South America
    • 5.5.2.1 Brazil
    • 5.5.2.2 Argentina
    • 5.5.2.3 Rest of South America
  • 5.5.3 Europe
    • 5.5.3.1 United Kingdom
    • 5.5.3.2 Germany
    • 5.5.3.3 France
    • 5.5.3.4 Italy
    • 5.5.3.5 Spain
    • 5.5.3.6 Rest of Europe
  • 5.5.4 Asia-Pacific
    • 5.5.4.1 China
    • 5.5.4.2 Japan
    • 5.5.4.3 India
    • 5.5.4.4 South Korea
    • 5.5.4.5 Rest of Asia-Pacific
  • 5.5.5 Middle East and Africa
    • 5.5.5.1 Middle East
      • 5.5.5.1.1 United Arab Emirates
      • 5.5.5.1.2 Saudi Arabia
      • 5.5.5.1.3 Rest of Middle East
    • 5.5.5.2 Africa
      • 5.5.5.2.1 South Africa
      • 5.5.5.2.2 Egypt
      • 5.5.5.2.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 OpenAI LLC
  • 6.4.2 Microsoft Corporation
  • 6.4.3 Google LLC
  • 6.4.4 Anthropic PBC
  • 6.4.5 Meta Platforms Inc.
  • 6.4.6 Amazon.com Inc.
  • 6.4.7 Hugging Face Inc.
  • 6.4.8 NVIDIA Corporation
  • 6.4.9 IBM Corporation
  • 6.4.10 Salesforce Inc.
  • 6.4.11 Cohere Inc.
  • 6.4.12 Adept AI Labs Inc.
  • 6.4.13 Replit Inc.
  • 6.4.14 Pinecone Systems Inc.
  • 6.4.15 LangChain Inc.
  • 6.4.16 Inflection AI Inc.
  • 6.4.17 Mistral AI SAS
  • 6.4.18 LangFuse GmbH
  • 6.4.19 Conductor Technologies Inc.
  • 6.4.20 Cerebras Systems Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment