에이전트형 AI 개발 플랫폼 : 시장 점유율 분석, 산업 동향 및 통계 데이터, 성장 예측(2026-2031년)

According to Mordor Intelligence, the agentic AI development platform market size is expected to grow from USD 10.75 billion in 2025 to USD 14.62 billion in 2026 and is forecast to reach USD 66.38 billion by 2031 at 35.34% CAGR over 2026-2031.

This report is Segmented by Component (Platform Software, Orchestration Middleware, Evaluation and Safety Tools, and More), Deployment (Public Cloud, Private Cloud, On-Premises, and More), End-User Industry (Healthcare and Life Sciences, and More), Organization Size (Large Enterprises, and Small and Med-Size Enterprises), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Agentic AI Development Platform Market Trends and Insights

Shift From Copilots to Autonomous Workflow Orchestration

Autonomous orchestration marks the clearest break between earlier copilot tools and the current agentic AI development platform market. Copilots mainly provide prompts and recommendations, while autonomous agents plan tasks, invoke tools, check results, and adjust their next actions with much less human input. That operating model requires a dedicated runtime, stronger state management, and tighter control over actions across enterprise systems. ServiceNow reported in 2026 that its Autonomous Workforce handled more than 90% of employee IT requests and resolved more than 100 million customer cases each month, which shows the operational scale now expected from enterprise agent deployments. Once workflows are built around a chosen runtime, replacement becomes difficult because integration testing, retraining, and workflow validation must be repeated.

Rapid Improvement in LLM Reasoning, Tool Use, and Multi-Agent Frameworks

The agentic AI development platform market has also advanced, as model and framework performance now enable more reliable completion of conditional workflows in production. Research on the AdaptOrch framework showed that topology-aware scheduling improved performance by 12-23% over static orchestration baselines, with the strongest gains in tasks that require sequential tool use and branching logic. A separate 2026 study on the DOVA framework found that adaptive thinking protocols reduced inference costs by 40-60% on routine tasks by skipping unnecessary extended reasoning. As model outputs converge, buyers are spending more time comparing topology design, memory management, and task coordination than comparing a single foundation model vendor. This is helping specialized runtime vendors in the agentic AI development platform market defend their position even when hyperscalers offer broader model access.

Governance, Auditability, and Security Gaps in Autonomous Agents

Security concerns remain one of the clearest brakes on the agentic AI development platform market because autonomous agents act across multiple systems where traditional controls were not designed to follow them. The MIT AI Agent Index reported in 2025 that only 1 of 200 reviewed production agents used cryptographic signing for action verification, underscoring the continued limitations of current auditability. OWASP published its MCP Security Top 10 in 2026 and formalized risks such as prompt injection via tool outputs and overly broad memory-retrieval permissions. These issues prompt enterprise security teams to request lineage tracking, rollback controls, and policy-based access enforcement before approving live use. Vendors that cannot show these controls often face longer sales cycles and higher proof-of-concept costs in regulated accounts.

Other drivers and restraints analyzed in the detailed report include:

1. Falling Deployment Friction Through Low-Code Builders And Managed Agent Runtimes
2. Rising Demand For Governed AI In Regulated Verticals
3. Legacy-System Integration Complexity And Unclear ROI Beyond Narrow Workflows

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

Segment Analysis

Platform software accounted for 76.39% of the agentic AI development platform market share in 2025, which shows that spending still centers on orchestration engines, agent runtimes, and LLM gateway layers. Enterprises treated this layer as core infrastructure, so buying behavior favored long-term platform commitments before implementation ecosystems had fully scaled. This pattern fits an early-cycle market where foundational control and workflow reliability matter more than adjacent tools. It also explains why platform decisions in the agentic AI development platform market tend to carry longer evaluation windows and higher switching barriers than many standard software purchases.

Professional services are projected to grow at a 36.14% CAGR through 2031, as deployment still requires connector work, memory schema design, governance policy setup, and cross-system authentication planning. Research on adaptive orchestration showed that topology-aware agent management can deliver 12-23% performance gains over static systems, and that finding is feeding demand for architecture design and tuning support. Orchestration middleware is gaining relevance as MCP and agent-to-agent protocol adoption increases the value of cross-protocol adapters and interoperability layers. Evaluation and safety tools are also moving from optional add-ons toward procurement requirements as buyers seek stronger validation, monitoring, and policy testing for production agents.

Public cloud captured 52.61% of the agentic AI development platform market size in 2025, making it the default starting point for many enterprise deployments. Managed runtimes from hyperscalers gave buyers a faster path to production because model access, orchestration tools, and infrastructure controls were already bundled in a single environment. Microsoft stated that Azure AI Foundry processed more than 100 trillion tokens in a single quarter in 2025, highlighting the extent to which early enterprise demand remained concentrated on public cloud infrastructure. The public cloud lead also reflects the fact that many organizations began with lower-risk pilots before deciding where stricter residency or latency controls were needed.

Hybrid and edge deployments are projected to grow at 36.09% CAGR through 2031 as more buyers run agents closer to data sources, operating systems, and regulated workloads. That push is strongest in industrial settings, public-sector environments, and sectors where round-trip latency or data-transfer rules make centralized cloud processing less practical. AWS expanded this path in 2026 with Bedrock AgentCore, a managed agent-harness platform, and early support for managed multi-agent pipelines. UiPath also released on-premises support for public-sector environments in May 2026, which shows that sovereign and air-gapped deployments are becoming a distinct part of the agentic AI development platform industry. Private cloud continues to matter most in financial services and healthcare, where system-of-record proximity and full audit trails remain central to deployment design.

Geography Analysis

North America held 38.73% of the agentic AI development platform market share in 2025, maintaining its revenue leadership. The region benefits from hyperscaler infrastructure, a large enterprise software buyer base, and a regulatory environment favoring voluntary governance. Microsoft reported over 70,000 Azure AI Foundry customer organizations in 2025, highlighting the scale of its enterprise base. OpenAI launched its Frontier enterprise platform in March 2026 with adopters like HP, Intuit, Oracle, and Uber. ServiceNow's USD 1 billion in AWS Marketplace transactions in 2026 indicates cloud marketplaces are becoming key distribution channels.

Asia-Pacific is projected to grow at 36.34% CAGR through 2031, driven by enterprise deployment in China, productivity-led adoption in India, and practical implementation in Japan. NTT Docomo Business planned to offer 200 agent types to enterprise customers in 2026, reflecting structured deployments in Japan. South Korea is advancing in semiconductor manufacturing and financial services, with private cloud models addressing data-sovereignty concerns. The region is transitioning from experimentation to production workflows and compliance-focused models.

Europe's tighter regulations are shaping the agentic AI development platform market. The EU AI Act enforcement for high-risk systems began in August 2026, alongside increased auditability under the Digital Operational Resilience Act. Germany, the UK, and France lead deployments due to large enterprise bases and compliance spending. European Commission data shows enterprise adaptation budgets of EUR 2.1-4.5 million (USD 2.37-5.09 million) over 18 months for EU AI Act readiness. South America shows early adoption, with Brazil and Argentina gaining traction. The Middle East and Africa are growing through sovereign AI investments, telecom deployments, and banking use cases, led by the UAE, Saudi Arabia, South Africa, and Egypt, though spending remains lower than in other regions through 2031.

1. Microsoft Corporation
2. Amazon Web Services, Inc.
3. Google LLC
4. OpenAI, L.L.C.
5. Anthropic PBC
6. Salesforce, Inc.
7. ServiceNow, Inc.
8. International Business Machines Corporation
9. Oracle Corporation
10. SAP SE
11. UiPath, Inc.
12. Databricks, Inc.
13. Snowflake Inc.
14. C3.ai, Inc.
15. Dataiku, Inc.
16. LangChain, Inc.
17. LlamaIndex, Inc.
18. Kore.ai, Inc.
19. Aisera, Inc.
20. Stack AI, 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 Shift From Copilots to Autonomous Workflow Orchestration
  • 4.2.2 Rapid Improvement in LLM Reasoning, Tool Use, and Multi-Agent Frameworks
  • 4.2.3 Falling Deployment Friction Through Low-Code Builders and Managed Agent Runtimes
  • 4.2.4 Rising Demand for Governed AI in Regulated Verticals
  • 4.2.5 Standardization Around MCP and Emerging Agent-to-Agent Protocols
  • 4.2.6 ERP and Workflow-System Modernization Creating a New Agent Control Plane Opportunity
• 4.3 Market Restraints
  • 4.3.1 Governance, Auditability, and Security Gaps in Autonomous Agents
  • 4.3.2 Legacy-System Integration Complexity and Unclear ROI Beyond Narrow Workflows
  • 4.3.3 Token-Intensive Inference Economics and Agent-Sprawl FinOps Pressure
  • 4.3.4 Evaluation Gaps for Multi-Agent Systems and Weak Traceability of Agent Memory
• 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 Component
  • 5.1.1 Platform Software
  • 5.1.2 Orchestration Middleware
  • 5.1.3 Evaluation and Safety Tools
  • 5.1.4 Professional Services
• 5.2 By Deployment Model
  • 5.2.1 Public Cloud
  • 5.2.2 Private Cloud
  • 5.2.3 On-premises
  • 5.2.4 Hybrid and Edge
• 5.3 By End-user Industry
  • 5.3.1 BFSI
  • 5.3.2 Healthcare and Life Sciences
  • 5.3.3 Retail and E-Commerce
  • 5.3.4 Manufacturing
  • 5.3.5 Media and Entertainment
  • 5.3.6 Government and Public Sector
  • 5.3.7 Other End-user Industries
• 5.4 By Organization Size
  • 5.4.1 Large Enterprises
  • 5.4.2 Small and Mid-size Enterprises (SMEs)
• 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 Microsoft Corporation
  • 6.4.2 Amazon Web Services, Inc.
  • 6.4.3 Google LLC
  • 6.4.4 OpenAI, L.L.C.
  • 6.4.5 Anthropic PBC
  • 6.4.6 Salesforce, Inc.
  • 6.4.7 ServiceNow, Inc.
  • 6.4.8 International Business Machines Corporation
  • 6.4.9 Oracle Corporation
  • 6.4.10 SAP SE
  • 6.4.11 UiPath, Inc.
  • 6.4.12 Databricks, Inc.
  • 6.4.13 Snowflake Inc.
  • 6.4.14 C3.ai, Inc.
  • 6.4.15 Dataiku, Inc.
  • 6.4.16 LangChain, Inc.
  • 6.4.17 LlamaIndex, Inc.
  • 6.4.18 Kore.ai, Inc.
  • 6.4.19 Aisera, Inc.
  • 6.4.20 Stack AI, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment