超級自動化市場機會、成長動力、產業趨勢分析及 2025 - 2034 年預測

2024年，全球超級自動化市場規模達464億美元，預計2034年將以17.06%的複合年成長率成長，達到2,202億美元。隨著企業努力提升效率並最大限度地減少資源消耗，超級自動化正逐漸成為關鍵解決方案。透過利用人工智慧、機器學習和機器人流程自動化 (RPA)，超級自動化可以自動執行重複的勞動密集型任務，幫助企業消除瓶頸、減少錯誤並提高工作流程的精確度。這使得企業能夠快速回應市場變化，提高營運效率，從而提升生產力並推動更智慧的營運。

隨著各行各業經歷數位轉型，超級自動化發揮著至關重要的作用，它能夠實現流程自動化，促進即時決策，從而推動從傳統手動方法轉向更靈活的數位化工作流程。無論是在客戶服務或供應鏈管理領域，超級自動化都能加速營運。其可擴展的特性使企業無需進行大規模系統改造即可實現成長，使其成為企業緊跟技術進步和不斷變化的客戶期望的必備工具。

2024年，機器人流程自動化 (RPA) 領域創造了超過 156 億美元的收入，預計到 2034 年將超過 665 億美元。 RPA 透過自動化資料輸入和發票處理等日常任務來增強超自動化，使企業能夠更有效率地營運，避免人為錯誤的風險。 RPA 工具可以無縫整合到現有工作流程中，使企業無需徹底改造其技術基礎設施即可享受自動化的優勢。這使得 RPA 成為銀行和物流等重複性任務繁重且營運效率至關重要的行業的理想解決方案。

2024年，基於雲端的細分市場佔據了53%的佔有率。基於雲端的超級自動化解決方案提供靈活性和可訪問性，使其成為尋求快速部署和遠端功能的企業的理想選擇。這些系統無需大量基礎設施投資，使企業能夠擴展其自動化策略，同時降低硬體成本。此外，自動更新功能使團隊能夠即時協作，從而提高營運敏捷性和回應能力。

由於強大的數位基礎設施和政府對新興技術的大力支持，北美超級自動化市場在2024年佔據了36%的市場佔有率。各行各業的公司正在整合人工智慧、機器學習和機器人流程自動化，以增強營運靈活性並降低成本。這種轉變使企業能夠快速回應市場動態和不斷變化的客戶需求。教育機構、科技公司和產業領袖之間的合作促進了持續創新，而高技能勞動力的可用性則加速了實施。

全球超級自動化產業的主要參與者包括Google、甲骨文、ServiceNow、UiPath、Honeywell國際、微軟、SAP SE、Automation Anywhere、TCS 和 WorkFusion。為了維持並擴大市場佔有率，超級自動化產業的公司專注於多項策略性舉措。其中一個主要策略是擴展產品組合，整合先進的人工智慧、機器學習和機器人流程自動化 (RPA) 功能，以滿足多樣化的客戶需求。此外，各公司也與製造業、醫療保健業和物流業等行業的領導者建立策略合作夥伴關係，以打造客製化解決方案，以應對自動化領域的特定挑戰。

目錄

第1章：方法論與範圍

第2章：執行摘要

第3章：行業洞察

• 產業生態系統分析
• 川普政府關稅分析
  • 對貿易的影響
    • 貿易量中斷
    • 報復措施
  • 對產業的影響
    • 供應方影響（原料）
      • 主要材料價格波動
      • 供應鏈重組
      • 生產成本影響
    • 需求面影響（售價）
      • 價格傳導至終端市場
      • 市佔率動態
      • 消費者反應模式
  • 受影響的主要公司
  • 策略產業反應
    • 供應鏈重組
    • 定價和產品策略
    • 政策參與
  • 展望與未來考慮
• 供應商格局
  • RPA提供者
  • AI/ML解決方案供應商
  • BPM和工作流程平台
  • 雲端與整合推動者
  • ERP 和企業自動化供應商
• 利潤率分析
• 技術與創新格局
• 重要新聞和舉措
• 專利分析
• 監管格局
• 衝擊力
  • 成長動力
    • 提高營運效率的需求
    • 跨產業快速數位轉型
    • 對降低成本和可擴展性的需求日益增加
    • 業務流程日益複雜
  • 產業陷阱與挑戰
    • 大規模實施超自動化
    • 破壞超級自動化計劃的有效性
• 成長潛力分析
• 波特的分析
• PESTEL分析

第4章：競爭格局

• 介紹
• 公司市佔率分析
• 競爭定位矩陣
• 戰略展望矩陣

第5章：市場估計與預測：依技術類型，2021 - 2034 年

• 機器人流程自動化（RPA）
• 人工智慧 (AI) 與機器學習 (ML)
• 業務流程管理 (BPM)
• 智慧型文檔處理（IDP）
• 低程式碼/無程式碼平台

第6章：市場估計與預測：按部署，2021 - 2034 年

• 基於雲端
• 本地

第7章：市場估計與預測：按解決方案，2021 - 2034 年

• 軟體
  • 自動化軟體
  • 智慧型文件處理（IDP）解決方案
  • 雲端自動化平台
  • 進階分析和報告工具
• 服務
  • 專業服務
    • 部署與整合
    • 諮詢
    • 支援與維護
  • 託管服務

第8章：市場估計與預測：依最終用途，2021 - 2034 年

• BFSI（銀行、金融服務和保險）
• 衛生保健
• 製造業
• 零售
• 資訊科技和電信
• 政府和公共部門
• 運輸和物流
• 其他

第9章：市場估計與預測：依組織規模，2021 - 2034 年

• 大型企業
• 中小企業（SME）

第10章：市場估計與預測：按地區，2021 - 2034 年

• 主要趨勢
• 北美洲
  • 美國
  • 加拿大
• 歐洲
  • 英國
  • 德國
  • 法國
  • 義大利
  • 西班牙
  • 俄羅斯
  • 北歐人
• 亞太地區
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳新銀行
  • 東南亞
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
• MEA
  • 阿拉伯聯合大公國
  • 沙烏地阿拉伯
  • 南非

第 11 章：公司簡介

• Allerin Tech
• Appian
• Automation Anywhere
• Catalytic
• Celonis
• Fortra
• Google
• Honeywell International
• Microsoft Corporation
• Mitsubishi Electric Corporation
• OneGlobe
• Oracle Corporation
• Redwood Software
• SAP SE
• ServiceNow
• SolveXia
• Tata Consultancy Services (TCS)
• UiPath
• Wipro Ltd
• WorkFusion

The Global Hyper Automation Market was valued at USD 46.4 billion in 2024 and is estimated to grow at a CAGR of 17.06% to reach USD 220.2 billion by 2034 as businesses strive to enhance efficiency and minimize resource consumption, hyper automation is emerging as a crucial solution. By leveraging AI, machine learning, and robotic process automation (RPA), it automates repetitive, labor-intensive tasks, helping organizations eliminate bottlenecks, reduce errors, and improve workflow precision. This allows companies to respond quickly to market changes and operate more efficiently, increasing productivity and driving smarter operations.

As industries undergo digital transformation, hyper automation plays a vital role by enabling the automation of processes and fostering real-time decision-making, facilitating a shift from traditional manual methods to more flexible, digital workflows. Whether in customer service or supply chain management, hyper automation accelerates operations. Its scalable nature enables businesses to grow without major system overhauls, making it an essential tool for companies aiming to keep pace with technological advancements and evolving customer expectations.

In 2024, the robotic process automation (RPA) segment generated over USD 15.6 billion in revenue and is expected to surpass USD 66.5 billion by 2034. RPA enhances hyper automation by automating mundane tasks, such as data entry and invoice processing, allowing organizations to run more efficiently without the risk of human error. RPA tools integrate seamlessly into existing workflows, offering organizations the benefits of automation without requiring a complete overhaul of their technological infrastructure. This makes RPA an attractive solution for industries burdened with repetitive tasks, such as banking and logistics, where operational efficiency is critical.

The cloud-based segment held a 53% share in 2024. Cloud-based hyper automation solutions offer flexibility and ease of access, making them ideal for businesses looking for fast deployment and remote capabilities. These systems eliminate the need for heavy infrastructure investments and enable organizations to scale their automation strategies while reducing hardware costs. Additionally, automatic updates allow teams to collaborate in real time, improving operational agility and responsiveness.

North America Hyper Automation Market held 36% share in 2024 fueled by robust digital infrastructure and strong government support for emerging technologies. Companies across various industries are integrating AI, machine learning, and robotic process automation to enhance operational flexibility and reduce costs. This shift enables businesses to respond rapidly to market dynamics and evolving customer demands. Collaborations between educational institutions, technology firms, and industry leaders foster continuous innovation, while the availability of a highly skilled workforce accelerates implementation.

Key players in the Global Hyper Automation Industry include Google, Oracle, ServiceNow, UiPath, Honeywell International, Microsoft Corporation, SAP SE, Automation Anywhere, TCS, and WorkFusion. To maintain and grow their market presence, companies in the hyper automation industry are focused on several strategic initiatives. One of the primary strategies is the expansion of their product portfolios, incorporating advanced AI, machine learning, and RPA capabilities to meet diverse customer needs. Companies are also forming strategic partnerships with industry leaders across sectors like manufacturing, healthcare, and logistics to create tailored solutions that address specific challenges in automation.

Table of Contents

Chapter 1 Methodology & Scope

• 1.1 Research design
  • 1.1.1 Research approach
  • 1.1.2 Data collection methods
• 1.2 Base estimates and calculations
  • 1.2.1 Base year calculation
  • 1.2.2 Key trends for market estimates
• 1.3 Forecast model
• 1.4 Primary research & validation
  • 1.4.1 Primary sources
  • 1.4.2 Data mining sources
• 1.5 Market definitions

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis, 2021 - 2034

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Trump administration tariff analysis
  • 3.2.1 Impact on trade
    • 3.2.1.1 Trade volume disruptions
    • 3.2.1.2 Retaliatory measures
  • 3.2.2 Impact on the industry
    • 3.2.2.1 Supply-side impact (raw materials)
      • 3.2.2.1.1 Price volatility in key materials
      • 3.2.2.1.2 Supply chain restructuring
      • 3.2.2.1.3 Production cost implications
    • 3.2.2.2 Demand-side impact (selling price)
      • 3.2.2.2.1 Price transmission to end markets
      • 3.2.2.2.2 Market share dynamics
      • 3.2.2.2.3 Consumer response patterns
  • 3.2.3 Key companies impacted
  • 3.2.4 Strategic industry responses
    • 3.2.4.1 Supply chain reconfiguration
    • 3.2.4.2 Pricing and product strategies
    • 3.2.4.3 Policy engagement
  • 3.2.5 Outlook and future considerations
• 3.3 Supplier landscape
  • 3.3.1 RPA Providers
  • 3.3.2 AI/ML Solution Vendors
  • 3.3.3 BPM & Workflow Platforms
  • 3.3.4 Cloud & Integration Enablers
  • 3.3.5 ERP & Enterprise Automation Vendors
• 3.4 Profit margin analysis
• 3.5 Technology & innovation landscape
• 3.6 Key news & initiatives
• 3.7 Patent analysis
• 3.8 Regulatory landscape
• 3.9 Impact forces
  • 3.9.1 Growth drivers
    • 3.9.1.1 Demand for enhanced operational efficiency
    • 3.9.1.2 Rapid digital transformation across industries
    • 3.9.1.3 Increasing need for cost reduction and scalability
    • 3.9.1.4 Rising complexity of business processes
  • 3.9.2 Industry pitfalls & challenges
    • 3.9.2.1 Implementing hyper automation at scale
    • 3.9.2.2 Undermining the effectiveness of hyper automation initiatives
• 3.10 Growth potential analysis
• 3.11 Porter's analysis
• 3.12 PESTEL analysis

Chapter 4 Competitive Landscape, 2024

• 4.1 Introduction
• 4.2 Company market share analysis
• 4.3 Competitive positioning matrix
• 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Technology Type, 2021 - 2034 (USD, Mn)

• 5.1 Robotic process automation (RPA)
• 5.2 Artificial intelligence (AI) and machine learning (ML)
• 5.3 Business process management (BPM)
• 5.4 Intelligent document processing (IDP)
• 5.5 Low-code/No-code platforms

Chapter 6 Market Estimates & Forecast, By Deployment, 2021 - 2034 (USD, Mn)

• 6.1 Cloud-based
• 6.2 On-premises

Chapter 7 Market Estimates & Forecast, By Solution, 2021 - 2034 (USD, Mn)

• 7.1 Software
  • 7.1.1 Automation software
  • 7.1.2 Intelligent document processing (IDP) solutions
  • 7.1.3 Cloud automation platforms
  • 7.1.4 Advanced analytics & reporting tools
• 7.2 Services
  • 7.2.1 Professional services
    • 7.2.1.1 Deployment & integration
    • 7.2.1.2 Consulting
    • 7.2.1.3 Support & maintenance
  • 7.2.2 Managed services

Chapter 8 Market Estimates & Forecast, By End Use, 2021 - 2034 (USD Mn)

• 8.1 BFSI (Banking, Financial Services, and Insurance)
• 8.2 Healthcare
• 8.3 Manufacturing
• 8.4 Retail
• 8.5 IT and Telecom
• 8.6 Government and public sector
• 8.7 Transportation and logistics
• 8.8 Others

Chapter 9 Market Estimates & Forecast, By Organization Size, 2021 - 2034 (USD, Mn)

• 9.1 Large enterprises
• 9.2 SME (Small and Medium Enterprises)

Chapter 10 Market Estimates & Forecast, By Region, 2021 - 2034 ($Mn, Units)

• 10.1 Key trends
• 10.2 North America
  • 10.2.1 U.S.
  • 10.2.2 Canada
• 10.3 Europe
  • 10.3.1 UK
  • 10.3.2 Germany
  • 10.3.3 France
  • 10.3.4 Italy
  • 10.3.5 Spain
  • 10.3.6 Russia
  • 10.3.7 Nordics
• 10.4 Asia Pacific
  • 10.4.1 China
  • 10.4.2 India
  • 10.4.3 Japan
  • 10.4.4 South Korea
  • 10.4.5 ANZ
  • 10.4.6 Southeast Asia
• 10.5 Latin America
  • 10.5.1 Brazil
  • 10.5.2 Mexico
  • 10.5.3 Argentina
• 10.6 MEA
  • 10.6.1 UAE
  • 10.6.2 Saudi Arabia
  • 10.6.3 South Africa

Chapter 11 Company Profiles

• 11.1 Allerin Tech
• 11.2 Appian
• 11.3 Automation Anywhere
• 11.4 Catalytic
• 11.5 Celonis
• 11.6 Fortra
• 11.7 Google
• 11.8 Honeywell International
• 11.9 Microsoft Corporation
• 11.10 Mitsubishi Electric Corporation
• 11.11 OneGlobe
• 11.12 Oracle Corporation
• 11.13 Redwood Software
• 11.14 SAP SE
• 11.15 ServiceNow
• 11.16 SolveXia
• 11.17 Tata Consultancy Services (TCS)
• 11.18 UiPath
• 11.19 Wipro Ltd
• 11.20 WorkFusion