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市场调查报告书
商品编码
1857182

基于代理的人工智慧：新兴趋势与机会

Agentic AI: Emerging Trends and Opportunities
出版日期: | 出版商: Frost & Sullivan | 英文 32 Pages | 商品交期: 最快1-2个工作天内

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简介目录

基于代理的人工智慧改变了公司的价值曲线

基于代理的人工智慧正在重塑企业人工智慧格局，它超越了传统的生成模型，发展出能够推理、规划并执行复杂工作流程的自主系统。企业正透过将代理商嵌入工作流程、客户旅程和IT维运，从实验阶段迈向生产级人工智慧部署。本报告探讨了推动实际应用的关键趋势，包括特定任务的人工智慧代理、多代理协作、企业整合方法以及信任与安全框架。

UiPath、Zoho、Microsoft 和 ServiceNow 等供应商支援在 IT 服务管理 (ITSM)、客户支援、财务和人力资源等领域部署代理商。越来越多的企业正在将这些代理商整合到生产环境中，利用 API、编配层和混合策略来实现扩充性和可控性。

随着智能体经济的成熟，早期投资于生命週期编配、信任框架和内建整合的相关人员将获得竞争优势。本报告提供策略洞察和实际应用案例，帮助企业领导者引领以智慧体为基础的AI时代。

基于代理的人工智慧产业三大战略挑战的影响

颠覆性技术

原因

  • 基于代理的人工智慧从根本上颠覆了人工智慧系统的运作方式，使它们能够在无需持续人工监督的情况下自主执行任务、进行互动和做出决策。
  • 这与主要专注于内容生成的传统人工智慧系统相比，是一次巨大的飞跃。基于代理的人工智慧对企业尤其具有吸引力，因为它可以透过自动化复杂任务显着降低人事费用并提高生产力。

弗罗斯特的观点

  • 平台供应商可以开发工具和框架，使代理商能够透过 API、预先建置的加速器和整合层与企业系统和外部服务进行交互，并可以提供代理编配平台，使多个专业代理能够协作完成复杂任务。
  • 服务提供者有机会开发专门的基础设施服务和客製化代理，将代理整合到企业工作流程中，并建立​​管治和安全服务以确保合规性。

地缘政治混乱

原因

  • 随着全球经济摩擦持续，各国政府正在实施制裁和贸易关税，以减少对海外开发的技术（硬体和软体）的依赖。
  • 因此，世界各国政府都在大力推动国内运算基础设施和人工智慧发展，并制定了严格的在地化要求。

弗罗斯特的观点

  • 主权人工智慧是数位保护主义抬头的结果，也是人工智慧基础设施、数据和人才被视为国家安全资产（而不仅仅是技术能力）的转变的结果。
  • 人工智慧生态系统中的商业机会正在不断扩大，从建立在地化资料集和本地运算基础设施，到建立特定区域的人工智慧模型，再到提供服务以帮助企业遵守全球管治和合规要求。

内部挑战

原因

  • 企业人工智慧的普及仍然受到资料碎片化的阻碍，许多公司都在努力建立统一的资料基础。

如果没有统一、高品质、即时的数据基础，人工智慧模型就缺乏产生准确、可操作见解所需的全面数据集。

弗罗斯特的观点

  • 随着人工智慧的发展，资料生命週期管理变得与人工智慧模型本身同等重要。

技术供应商和服务提供者有机会提供资料服务，例如标註任务、合成资料产生、资料管理（将各种资料来源整合到整合管道中）和资料监控服务，以确保资料健康。

成长驱动因素

提高效率和降低成本是基于代理的人工智慧被采用的经济驱动因素。

  • 从日益增长的业务和客户资料中提取可操作价值的能力将推动基于代理的人工智慧的普及应用。
  • 技术和基础设施的日益普及

成长限制因素

  • 缺乏信任会减缓企业采用率。
  • 明确的投资报酬率 (ROI)
  • 缺乏领导承诺
  • 法律规范和道德规范方面缺乏清晰性

目录

议程

  • 策略要务
  • 为什么成长变得越来越难？
  • The Strategic Imperative 8（TM）
  • 基于代理的人工智慧产业三大战略挑战的影响

成长机会分析

  • 说明
  • 人工智慧唯一不变的就是变化。
  • 人工智慧：全球企业的优先技术
  • 人工智慧系统的演进：传统人工智慧、生成式人工智慧与基于代理的人工智慧
  • 什么是基于代理的人工智慧？
  • 基于代理的人工智慧的主要特征
  • 成长驱动因素
  • 成长抑制因素
  • 基于代理的人工智慧技术栈
  • 说明基于代理的人工智慧技术栈
  • 基于代理的人工智慧的新趋势
  • 特定任务型人工智慧代理：简介
  • 特定任务型人工智慧代理：新兴应用案例
  • 特定任务型人工智慧代理：基于代理的人工智慧在主要工业领域的部署
  • 特定任务型人工智慧代理：将基于代理的人工智慧引入其他领域
  • 基于代理的人工智慧的主要范例
  • 多人工智慧代理：协作系统的兴起
  • 多人工智慧代理：理解不同的方法
  • 多人工智慧代理：协作系统的兴起：主要供应商的生态系统
  • 企业整合基于代理的人工智慧
  • 信任与安全：资料安全问题以及评估投资报酬率的能力仍然是人工智慧普及应用的挑战。
  • 信任与安全：基于代理的人工智慧带来了超越传统IT安全威胁的新型风险
  • 建议的信任与安全威胁缓解方法
  • 新的经营模式：基于结果的代理即服务

采取行动的公司

  • 采取行动的主要企业：微软
  • 采取行动的主要企业：ServiceNow
  • 采取行动的主要企业：Zoho
  • 采取行动的主要企业：UiPath

成长机会领域

  • 成长机会 1：基于代理的 AI 服务

附录与后续步骤

  • 成长机会的益处和影响
  • 下一步
  • 附件清单
  • 免责声明
简介目录
Product Code: PG1M-69

Agentic AI Transforming the Enterprise Value Curve

Agentic AI is redefining the enterprise AI landscape by moving beyond traditional and generative models toward autonomous systems that can reason, plan, and act across complex workflows. Enterprises are increasingly moving from experimentation to production-grade AI deployments, embedding agents within workflows, customer journeys, and IT operations. This report explores key trends such as task-specific AI agents, multi-agent collaboration, enterprise integration approaches, and trust & safety frameworks, driving real-world adoption.

Vendors like UiPath, Zoho, Microsoft, and ServiceNow are enabling agent deployments across ITSM, customer support, finance, and HR. Enterprises are increasingly integrating these agents into production environments, leveraging APIs, orchestration layers, and hybrid strategies for scalability and control.

As the agent economy matures, stakeholders who invest early in lifecycle orchestration, trust frameworks, and embedded integration will gain a competitive advantage. This report offers strategic insights and real-world use cases to help business leaders lead in the Agentic AI era.

The Impact of the Top 3 Strategic Imperatives on the Agentic AI Industry

Disruptive Technologies

Why

  • Agentic AI is fundamentally disrupting how AI systems operate by enabling them to autonomously perform tasks, interact and make decisions, without constant human oversight.
  • This is a significant leap from traditional AI systems that primarily focus on content generation. Agentic AI is particularly appealing to businesses because it significantly reduces labor costs and enhances productivity by automating complex tasks.

Frost Perspective

  • Platform vendors can develop tools and frameworks that enable agents to interact with enterprise systems and external services through APIs, pre-built accelerators and integration layers. Also, they can offer agent orchestration platforms where multiple specialized agents collaborate on complex tasks.
  • Opportunities exist for service providers to develop specialized infrastructure services and bespoke agents, integrate agents into enterprise workflows, and build governance and security services to ensure compliance.

Geopolitical Chaos

Why

  • Ongoing friction between global economies has led governments to introduce sanctions and trade tariffs and reduce dependence on technology (hardware and software) developed overseas.
  • This has led governments worldwide to push for homegrown computing infrastructure and AI development with strict localization mandates.

Frost Perspective

  • Sovereign AI is a result of rising digital protectionism, a shift where AI infrastructure, data, and talent are seen as national security assets rather than just technological capabilities.
  • Opportunities span the AI ecosystem, from creating localized datasets and local compute infrastructure, to building region-specific AI models, to offering services to help enterprises adapt global governance and compliance.

Internal Challenges

Why

  • Enterprise AI implementation continues to be hindered by data fragmentation, with many enterprises struggling to establish a unified data foundation.

Without a unified, high-quality, and real-time data infrastructure, AI models lack the comprehensive datasets needed to generate accurate and actionable insights.

Frost Perspective

  • As AI evolves, managing the data lifecycle has become as critical as the AI models.

Opportunities for technology vendors and service providers exist in offering data services, such as labeling tasks and synthetic data generation, data management (i.e., integration of diverse data sources into unified pipelines), and data monitoring services to ensure data health.

Growth Drivers

Efficiency improvements and cost reductions represent compelling economic drivers for agentic AI adoption

  • Ability to extract actionable value from the growing volumes of enterprise and customer data drives Agentic AI uptake
  • Increasing availability of enabling technologies and infrastructure

Growth Restraints

  • Lack of trust slows enterprise adoption
  • Clear return on investment (ROI)
  • Lack of leadership commitment
  • Lack of clarity concerning regulatory frameworks and ethical practices

Table of Contents

Agenda

  • Strategic Imperatives
  • Why is it Increasingly Difficult to Grow?
  • The Strategic Imperative 8™
  • The Impact of the Top 3 Strategic Imperatives on the Agentic AI Industry

Growth Opportunity Analysis

  • Glossary
  • With AI, the Only Constant Is 'Change'
  • AI: A Technology Priority for Global Enterprises
  • Evolution of AI Systems: Traditional vs Generative vs Agentic
  • What is Agentic AI?
  • Key Characteristics of Agentic AI
  • Growth Drivers
  • Growth Restraints
  • Agentic AI Tech Stack
  • Agentic AI Tech Stack-Explained
  • Emerging Agentic AI Trends
  • Task-Specific AI Agents: An Introduction
  • Task-Specific AI Agents: Emerging Use Cases
  • Task-Specific AI Agents: Agentic AI Deployments Across Key Industry Sectors
  • Task-Specific AI Agents: Agentic AI Deployments Across Other Sectors
  • Key Examples of Agentic AI Deployments
  • Emergence of Multi-AI Agent Collaboration Systems
  • Multi-AI Agents: Understanding Different Approaches
  • Emergence of Multi-AI Agent Collaboration Systems: Key Vendor Ecosystem
  • Enterprise Integration of Agentic AI
  • Trust and Safety: Data Concerns and Ability to Assess ROI Continue to Challenge AI Adoption
  • Trust and Safety: Agentic AI Introduces a New Category of Risks, Going Beyond Traditional IT Security Threats
  • Trust and Safety: Recommended Approaches for Threat Mitigation
  • Emerging Business Model: Outcome-Based Agent-as-a-Service

Companies to Action

  • Key Companies to Action: Microsoft
  • Key Companies to Action: ServiceNow
  • Key Companies to Action: Zoho
  • Key Companies to Action: UiPath

Growth Opportunity Universe

  • Growth Opportunity 1: Agentic AI Services

Appendix & Next Steps

  • Benefits and Impacts of Growth Opportunities
  • Next Steps
  • List of Exhibits
  • Legal Disclaimer