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市場調查報告書
商品編碼
1857182

基於代理的人工智慧：新興趨勢與機遇

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個工作天內

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簡介目錄

基於代理的人工智慧改變了公司的價值曲線

基於代理的人工智慧正在重塑企業人工智慧格局，它超越了傳統的生成模型，發展出能夠推理、規劃並執行複雜工作流程的自主系統。企業正透過將代理商嵌入工作流程、客戶旅程和IT維運，從實驗階段邁向生產級人工智慧部署。本報告探討了推動實際應用的關鍵趨勢，包括特定任務的人工智慧代理、多代理協作、企業整合方法以及信任與安全框架。

UiPath、Zoho、Microsoft 和 ServiceNow 等供應商支援在 IT 服務管理 (ITSM)、客戶支援、財務和人力資源等領域部署代理商。越來越多的企業正在將這些代理商整合到生產環境中，利用 API、編配層和混合策略來實現擴充性和可控性。

隨著智慧體經濟的成熟，早期投資於生命週期編配、信任框架和內建整合的相關人員將獲得競爭優勢。本報告提供策略洞察和實際應用案例，幫助企業領導者引領以智慧體為基礎的AI時代。

基於代理的人工智慧產業三大戰略挑戰的影響

顛覆性技術

原因

  • 基於代理的人工智慧從根本上顛覆了人工智慧系統的運作方式，使它們能夠在無需持續人工監督的情況下自主執行任務、進行互動和做出決策。
  • 這與主要專注於內容生成的傳統人工智慧系統相比，是一次巨大的飛躍。基於代理的人工智慧對企業尤其具有吸引力，因為它可以透過自動化複雜任務顯著降低人事費用並提高生產力。

弗羅斯特的觀點

  • 平台供應商可以開發工具和框架，使代理商能夠透過 API、預先建置的加速器和整合層與企業系統和外部服務進行交互，並可以提供代理編配平台，使多個專業代理能夠協作完成複雜任務。
  • 服務提供者有機會開發專門的基礎設施服務和客製化代理，將代理整合到企業工作流程中，並建立​​管治和安全服務以確保合規性。

地緣政治混亂

原因

  • 隨著全球經濟摩擦持續，各國政府正在實施制裁和貿易關稅，以減少對海外開發的技術（硬體和軟體）的依賴。
  • 因此，世界各國政府都在大力推動國內運算基礎設施和人工智慧發展，並制定了嚴格的在地化要求。

弗羅斯特的觀點

  • 主權人工智慧是數位保護主義抬頭的結果，也是人工智慧基礎設施、數據和人才被視為國家安全資產（而不僅僅是技術能力）的轉變的結果。
  • 人工智慧生態系統中的商業機會正在不斷擴大，從建立在地化資料集和本地運算基礎設施，到建立特定區域的人工智慧模型，再到提供服務以幫助企業遵守全球管治和合規要求。

內部挑戰

原因

  • 企業人工智慧的普及仍然受到資料碎片化的阻礙，許多公司都在努力建立統一的資料基礎。

如果沒有統一、高品質、即時的數據基礎，人工智慧模型就缺乏產生準確、可操作見解所需的全面資料集。

弗羅斯特的觀點

  • 隨著人工智慧的發展，資料生命週期管理變得與人工智慧模型本身同等重要。

技術供應商和服務提供者有機會提供資料服務，例如標註任務、合成資料產生、資料管理（將各種資料來源整合到整合管道中）和資料監控服務，以確保資料健康。

成長促進因素

提高效率和降低成本是基於代理的人工智慧被採用的經濟促進因素。

  • 從日益成長的業務和客戶資料中提取可操作價值的能力將推動基於代理的人工智慧的普及應用。
  • 技術和基礎設施的日益普及

成長限制因素

  • 缺乏信任會減緩企業採用率。
  • 明確的投資報酬率 (ROI)
  • 缺乏領導承諾
  • 法律規範和道德規範方面缺乏清晰性

目錄

議程

  • 策略要務
  • 為什麼成長變得越來越難？
  • The Strategic Imperative 8（TM）
  • 基於代理的人工智慧產業三大戰略挑戰的影響

成長機會分析

  • 說明
  • 人工智慧唯一不變的就是變化。
  • 人工智慧：全球企業的優先技術
  • 人工智慧系統的演進：傳統人工智慧、生成式人工智慧與基於代理的人工智慧
  • 什麼是基於代理的人工智慧？
  • 基於代理的人工智慧的主要特徵
  • 成長促進因素
  • 成長抑制因素
  • 基於代理的人工智慧技術棧
  • 說明基於代理的人工智慧技術棧
  • 基於代理的人工智慧的新趨勢
  • 特定任務型人工智慧代理：簡介
  • 特定任務型人工智慧代理：新興應用案例
  • 特定任務型人工智慧代理：基於代理的人工智慧在主要工業領域的部署
  • 特定任務型人工智慧代理：將基於代理的人工智慧引入其他領域
  • 基於代理的人工智慧的主要範例
  • 多人工智慧代理：協作系統的興起
  • 多人工智慧代理：理解不同的方法
  • 多人工智慧代理：協作系統的興起：主要供應商的生態系統
  • 企業整合基於代理的人工智慧
  • 信任與安全：資料安全問題以及評估投資報酬率的能力仍然是人工智慧普及應用的挑戰。
  • 信任與安全：基於代理的人工智慧帶來了超越傳統IT安全威脅的新型風險
  • 建議的信任與安全威脅緩解方法
  • 新的經營模式：基於結果的代理即服務

採取行動的公司

  • 採取行動的主要企業：微軟
  • 採取行動的主要企業：ServiceNow
  • 採取行動的主要企業：Zoho
  • 採取行動的主要企業：UiPath

成長機會領域

  • 成長機會 1：基於代理的 AI 服務

附錄與後續步驟

  • 成長機會的益處和影響
  • 下一步
  • 附件清單
  • 免責聲明
簡介目錄
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