智能體人工智慧總體擁有成本 (TCO) 和投資報酬率 (ROI) 評估，市場數據概覽：2025 年第三季度

本報告探討並分析了智能體人工智慧市場，提供了智能體人工智慧實施的總體擁有成本 (TCO) 和投資回報率 (ROI) 時間表等信息，以及實施智能體人工智慧的營銷和信息傳遞策略。

關鍵問題解答

• 智能體人工智慧系統包含哪些組件？
• 每種智慧體人工智慧部署的關鍵成本推動因素是什麼？
• 智能體人工智慧的投資報酬率時間表如何因用例而異？
• 智能體人工智慧的實施時間表如何影響投資報酬率預測？
• 每種智慧體人工智慧實施的關鍵價值推動因素是什麼？

本產品旨在與 "智能體人工智慧總擁有成本 (TCO) 和投資回報率 (ROI) 評估" （MD-AGAI-101）配合使用。

目錄

主要發現

最新資訊

研究方法

主要預測

總擁有成本區隔

智能體人工智慧實施的營運歷程

智能體人工智慧系統架構

影響總擁有成本 (TCO) 的關鍵因素

智能體人工智慧用例矩陣

用例概述

用於人力資源諮詢的低成本單智能體系統的五年總擁有成本

用於製造供應鏈管理的高成本多智能體系統的五年總擁有成本

用於海上石油鑽井平台的邊緣部署高成本多智能體系統的五年總擁有成本預測性維護

Actionable Benefits:

• Understand the Total Cost of Ownership (TCO) and the Return on Investment (ROI) timelines for Agentic Artificial Intelligence (AI) implementation.
• Build marketing and messaging strategy for Agentic AI implementation linking TCO and value creation.
• Identify major TCO drivers for Agentic AI implementation.
• Benchmark in-house Agentic AI solution TCO/ROI.

Critical Questions Answered:

• What does an Agentic AI system stack look like?
• What are the major cost drivers for different Agentic AI deployments?
• How does the Agentic AI ROI timeline depend on use cases?
• How will the Agentic AI implementation timeline affect ROI expectations?
• What are the main drivers of value creation within each Agentic AI implementation?

Research Highlights:

• Agentic AI ROI and TCO analysis across three deployment scenarios.
• Agentic AI TCO segmented by eight different cost drivers.
• Agentic AI value creation through headcount reduction and process efficiency.

Who Should Read This?

• Enterprise leaders assessing Agentic AI implementation scenarios and exploring commercial opportunities.
• AI product managers and marketing leaders aiming to enhance their understanding of Agentic AI ROI & TCO.
• Strategists aiming to align Agentic AI monetization strategies with ROI timelines, use case value creation, and other factors.

TABLE OF CONTENTS

This product is meant to be read in conjunction with Agentic AI Total Cost of Ownership TCO and Return on Investment ROI Assessment MD-AGAI-101

Key Findings

Whats New

Methodology

Significant Forecasts

Total Cost of Ownership Breakdown

Agentic AI Implementation Operational Journey

Agentic AI System Stack

Major Factors Impacting Total Cost of Ownership TCO

Agentic AI Use Case Matrix

Use Case Overview

5-Year TCO for Low-Impact Single Agent System for HR Inquiries

5-Year TCO for High-Impact Multi-Agent System for Manufacturing Supply Chain Management

5-Year TCO for Edge-Deployed High-Impact Multi-Agent System for Predictive Maintenance on Offshore Oil Rig