人工智慧驅動的自動化與業務轉型：利用自主代理將目標轉化為可衡量的成果

AI-driven Automation and Business Transformation: Transforming Objectives into Concrete Results through the Mobilization of Autonomous Agents

出版日期: 2025年09月08日 | 出版商:

IDATE | 英文 42 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

本報告分析了現代經濟中人工智慧融合所驅動的組織轉型，並評估了各機構為端到端自動化做好準備的程度。報告還重點闡述了人工智慧如何從獨立應用發展成為貫穿營運的核心服務，並與創新週期、全球投資流動以及不斷擴大的國家參與相契合。

本研究檢視了監管架構的整合及其對治理的影響，並探討了可追溯性、人工監督、技術責任、演算法公平性和數位主權等問題。此外，研究也檢視了支援智慧自動化的技術和組織模型，包括能夠設定目標、規劃任務並與人類同事協同工作的AI代理，這種協同模式有助於提升員工的各項技能。

透過對供應鏈、金融、醫療保健、汽車、零售和電信等行業的案例研究，該報告還指出了關鍵的成功因素，例如強大的數據治理、透明度、資源共享和有效的變革管理。

此外，本報告還提供了 2025-2035 年自適應工作流程、邊緣運算和混合量子技術的展望，包括對估值方法和投資回報率模型的分析。

This report analyses organisational transformations driven by the integration of AI into the contemporary economy and assesses the ability of institutions to adapt to end-to-end automation. It highlights the transition from isolated applications to integrated platforms that position AI as a cross-cutting service at the core of operations, aligned with innovation cycles, global investment flows, and increasing state involvement.

The study explores the consolidation of regulatory frameworks and their implications for governance, addressing issues such as traceability, human oversight, technical accountability, algorithmic fairness, and digital sovereignty. It also examines the technological and organisational models that underpin intelligent automation, including AI agents capable of setting objectives, planning tasks, and working alongside human colleagues in a co-piloting model that supports broad-based skills development.

Through sector-specific use cases - spanning supply chains, finance, healthcare, automotive, retail, and telecommunications - the report identifies key success factors: robust data governance, transparency, resource sharing, and effective change management. It further incorporates an analysis of valuation methods and ROI models, while outlining prospective trajectories for 2025-2035, including adaptive workflows, edge computing, and hybrid quantum technologies.