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世界经济论坛 & 凯捷:2026 AI 智能体落地:可信采用、授权与规模化实战手册(中译版)(38页).pdf

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1、AI Agents in Action:A Playbook for Trusted Adoption,Authorization and Scaling I N S I G H T R E P O R TM A Y 2 0 2 6In collaboration withCapgeminiImages:Getty ImagesDisclaimer This document is published by the World Economic Forum as a contribution to a project,insight area or interaction.The findin

2、gs,interpretations and conclusions expressed herein are a result of a collaborative process facilitated and endorsed by the World Economic Forum but whose results do not necessarily represent the views of the World Economic Forum,nor the entirety of its Members,Partners or other stakeholders.2026 Wo

3、rld Economic Forum.All rights reserved.No part of this publication may be reproduced or transmitted in any form or by any means,including photocopying and recording,or by any information storage and retrieval system.ContentsForeword 3Executive summary 4Introduction 51 Agent guidelines 71.1 Establish

4、ing a shared language for autonomy,8 authority and consequence1.2 Allocating decision rights and accountability across the life cycle 91.3 Defining when agentic systems are the appropriate solution 91.4 Sequencing adoption and prioritizing early use cases 101.5 Deployment contexts and baseline gover

5、nance 111.6 Defining the humanagent operating model 121.7 From enterprise guidelines to deployment authorization 122 ACAP:The Agent Capability and Authorization Profile 142.1 ACAP structure and how to use it 162.2 System design and assessment 172.3 Prepare and deploy 232.4 Monitor and improve 27Conc

6、lusion 30Appendix:ACAP summary playbook 31Contributors 34Endnotes 37AI Agents in Action2ForewordArtificial intelligence(AI)agents have left research laboratories to become a permanent fixture in organizational workflows.This shift has outpaced our existing governance frameworks.Where the first publi

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1. **核心问题**:AI代理的授权滞后于能力发展,需建立可审计、可执行的授权模型。 2. **解决方案**:提出**ACAP(代理能力与授权档案)**,作为部署级授权工具,连接企业政策、系统设计与运营监督。 3. **关键框架**: - **代理指南**:定义自主权、权限、后果事件等术语,明确决策权分配与部署场景分级(单组织/跨组织/跨平台)。 - **生命周期管理**:分三阶段(设计评估→部署准备→监控改进),通过阶段门控确保授权与风险匹配。 4. **核心数据**: - 部署风险取决于**工具访问权限**与**上下文**,而非仅模型能力(如数据泄露、过度授权等风险)。 - 早期用例需选择**低后果、可逆**场景,并建立**性能基准**(如人类对比、任务完成率)以扩展权限。 5. **治理重点**:通过**最小权限原则**、**经济边界**(如成本上限)及**可追溯日志**确保安全,避免监督疲劳与自动化偏差。
AI代理如何授权? 代理能力如何评估? 代理部署风险如何管控?
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