智能体人工智慧总体拥有成本 (TCO) 和投资报酬率 (ROI) 评估，市场数据概览：2025 年第三季度

本报告探讨并分析了智能体人工智慧市场，提供了智能体人工智慧实施的总体拥有成本 (TCO) 和投资回报率 (ROI) 时间表等信息，以及实施智能体人工智慧的营销和信息传递策略。

关键问题解答

• 智能体人工智慧系统包含哪些组件？
• 每种智慧体人工智慧部署的关键成本推动因素是什么？
• 智能体人工智慧的投资报酬率时间表如何因用例而异？
• 智能体人工智慧的实施时间表如何影响投资报酬率预测？
• 每种智慧体人工智慧实施的关键价值推动因素是什么？

本产品旨在与 "智能体人工智慧总拥有成本 (TCO) 和投资回报率 (ROI) 评估" （MD-AGAI-101）配合使用。

目录

主要发现

最新资讯

研究方法

主要预测

总拥有成本区隔

智能体人工智慧实施的营运历程

智能体人工智慧系统架构

影响总拥有成本 (TCO) 的关键因素

智能体人工智慧用例矩阵

用例概述

用于人力资源咨询的低成本单智能体系统的五年总拥有成本

用于製造供应链管理的高成本多智能体系统的五年总拥有成本

用于海上石油钻井平台的边缘部署高成本多智能体系统的五年总拥有成本预测性维护

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