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Uploaded byNobusuke Hanagasaki
PPTX, PDF37 views

Enterprise Agentic AI Reference Architecture 2026.pptx

Enterprise Agentic AI Reference Architecture 2026 は、企業における AI エージェントの設計・構築・運用に必要な技術要素とその関係性を体系化したリファレンスアーキテクチャです。 Harness Engineering、Context Engineering、MCP / A2A によるツール・エージェント連携、Knowledge & Retrieval、Sandbox などの実行環境、LLM / SLM、共有データ・インテリジェンス基盤、セキュリティ、ガバナンス、可観測性まで、2026年の Agentic AI システムを構成する主要要素をエンドツーエンドで可視化しています。企業IT部門、アーキテクト、開発者、AIエージェント導入を検討する組織向けの全体設計マップです。 Enterprise Agentic AI Reference Architecture 2026 provides a structured view of the technologies and architectural components required to design, build, and operate enterprise AI agents. It visualizes the end-to-end architecture of Agentic AI systems in 2026, including Harness Engineering, Context Engineering, tool and agent interoperability through MCP and A2A, Knowledge & Retrieval, execution environments such as sandboxes, LLMs and SLMs, shared data and intelligence platforms, security, governance, and observability. It is designed as an architecture map for enterprise IT teams, architects, developers, and organizations planning or implementing AI agents.

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1 GenAI Tech Solution Map Shared Data & Intelligence Platform Vector / Graph Solution catalog (marketplace) AI Agents Tools & Interoperability Orchestration Models Context Engineering Memory State / History Instructions / Prompt Function calling Code / Shell MCP Knowledge / Retrieval LLM Files Search / Vector RDBMS Skills Harness Engineering Plan/Execute Routes / workflows Web search Embeddings Agentic AI Platform Lakehouse Structured data Unstructured data Data Engineering Data Ingest Data Governance Apps / UI Security, Governance, Safety Guardrails Access Control Identity Chatbot Virtual expert Docs Q&A Provisioning Component library Observability Evaluation Files Approval / HITL SLM ERP/CRM ITSM Enterprise Apps Agent Infrastructure / Hosting Serverless Container VM On-premises Managed Service Data Science Analyze Train Deploy MLOps Custom LLM AI Services APIs Computer use A2A metadata … … Fine-tuning Development Environments Code/Prompt management CI/CD pipeline Agentic Coding Process Automation Creativity Decision Support GenAIOps Prompt library *powered by McKinsey & Company Network Responsible AI Loop / Todo Checkpoint / Resume Compaction Execution Environment Sandbox Semantic Model / Ontology Workspace Browser Runtime/Compute Enterprise Agentic AI Reference Architecture 2026
2 Gen AI shared data platform Vector / Graph Solution catalog (marketplace) AI Agents Tools Orchestration Models Context Engineering User Prompt State Long-Term Memory History Instructions / System Prompt Actions Function calling Code Interpreter MCP Knowledge (RAG) LLM Files Vector/Graph DB RDBMS Agent-as-a-Tool Reasoning Planning Routes/workflows Web search Embeddings Gen AI platform Lakehouse Structured data Unstructured data Data Engineering Data Ingest Data control Apps / UI Security, Governance, Safety Guardrails Content filtering Auth Chatbot Virtual expert Docs Q&A Provisioning Component library Observability Evaluation Files Monitoring SLM ERP/CRM ITSM Enterprise Apps Agent Hosting Serverless Container VM On-premises SaaS Data Science Analyze Train Deploy MLOps Custom LLM GenAI Tech Solution Map AI Services APIs Computer use A2A Deep Research metadata … … 2025 Fine-tuning Development Environments Code/Prompt management CI/CD pipeline Agentic Coding Process Automation Creativity Decision Support GenAIOps Prompt library *powered by McKinsey & Company Network Responsible AI