超自動化市場：全球依技術、部署、產業垂直、組織規模、地區和預測分類

超自動化全球市場規模與預測

2024 年全球超自動化市場價值為 10.1 億美元，預計到 2032 年將達到 38.6 億美元，2026 年至 2032 年的複合年成長率為 18.25%。

超自動化是使用人工智慧、機器學習和 RPA 等先進技術來自動化複雜的業務流程，以提高效率並減少人工干預的需要。

其應用涵蓋醫療保健、製造業和金融等行業，透過自動化數據分析、流程監控和預測性維護，實現更快的決策、簡化的工作流程和提高準確性。

超自動化的未來在於提高人工智慧的整合度，將自動化擴展到更複雜的任務，實現自動駕駛系統，並刺激各行各業的創新，從而推動成本節約和生產力提高。

全球超自動化市場動態

影響全球超自動化市場的關鍵市場動態：

關鍵市場促進因素

效率需求日益成長：企業正在尋求透過自動化重複性任務來提高生產力、減少人為錯誤並降低營運成本的方法。超自動化透過整合先進技術實現無縫流程最佳化，從而滿足了這項需求。

人工智慧和機器學習的進步：隨著人工智慧和機器學習技術的成熟，它們能夠實現更複雜任務的自動化。這將推動超自動化的普及，使企業能夠大規模處理數據並做出智慧的即時決策。

RPA 的採用率不斷提升：機器人流程自動化 (RPA) 是超自動化的關鍵推動因素，可自動執行日常業務業務。 RPA 的採用減少了手動任務，使員工能夠專注於更高價值的業務，從而提高整體效率。

因應數位轉型：在正在經歷數位轉型的產業中，超自動化將成為現代化舊有系統、改善客戶體驗和推動創新的重要工具。對數位化敏捷性的需求將推動各行各業的市場成長。

主要挑戰

實施和整合複雜：超自動化需要將人工智慧、機器人流程自動化 (RPA)、機器學習等各種技術整合到現有系統中。這種複雜性可能導致相容性問題，並且需要大量的專業知識和投資才能順利實施。

安全和資料隱私問題：超自動化涉及大規模資料處理，因此保護敏感資訊至關重要。自動化系統中的漏洞可能使企業面臨網路攻擊和資料外洩的風險，使安全和隱私成為企業面臨的重大挑戰。

主要趨勢：

人工智慧驅動的決策：超自動化正在整合人工智慧，不僅可以自動化日常任務，還可以自動化複雜的決策流程。這一趨勢有助於企業預測結果、最佳化業務並提高即時決策的準確性。

低程式碼/無程式碼平台的使用增加：低程式碼和無程式碼平台的興起使非技術用戶更容易實現流程自動化，使超自動化民主化，並能夠在業務功能中快速部署自動化解決方案，而無需過度依賴 IT。

智慧型文件處理 (IDP) 的興起：超自動化正在利用智慧文件處理技術，自動提取、分類和管理文件中的非結構化資料。這一趨勢將提高醫療保健和金融等依賴大量文件製作的行業的效率。

目錄

第 1 章全球超自動化市場：簡介

• 市場概覽
• 研究範圍
• 先決條件

第2章執行摘要

第3章：已驗證的市場研究調查方法

• 資料探勘
• 驗證
• 第一手資料
• 資料來源列表

第4章 全球超自動化市場展望

• 概述
• 市場動態
  • 驅動程式
  • 限制因素
  • 機會
• 波特五力模型
• 價值鏈分析

第5章 全球超自動化市場（按部署）

• 概述
• 本地
• 雲端基礎

第6章 全球超自動化市場（按技術）

• 機器人流程自動化（RPA）
• 人工智慧（AI）和機器學習（ML）
• 業務流程管理 (BPM)
• 自然語言處理（NLP）
• 光學字元辨識 (OCR)
• 數位雙胞胎
• 智慧流程自動化（IPA）
• 預測分析

第7章 全球超自動化市場（依產業垂直分類）

• 銀行、金融服務和保險（BFSI）
• 醫療保健和生命科學
• 製造業
• 零售與電子商務
• 資訊科技和電訊
• 運輸/物流
• 能源與公共產業
• 政府/公共部門
• 房地產與建築

第8章。全球超自動化市場（按組織規模）

• 中小企業
• 主要企業

第9章全球超自動化市場（按地區）

• 概述
• 北美洲
  • 美國
  • 加拿大
  • 墨西哥
• 歐洲
  • 德國
  • 英國
  • 法國
  • 其他歐洲國家
• 亞太地區
  • 中國
  • 日本
  • 印度
  • 其他亞太地區
• 世界其他地區
  • 拉丁美洲
  • 中東和非洲

第10章全球超自動化市場的競爭格局

• 概述
• 各公司市場排名
• 主要發展策略

第10章 公司簡介

• UiPath
• Automation Anywhere
• Blue Prism
• IBM
• Microsoft
• Pegasystems
• Appian
• WorkFusion
• Kofax
• NICE Systems.

第11章 附錄

• 相關調查

Global Hyper Automation Market Size and Forecast

The Global Hyper Automation Market was valued at USD 1.01 Billion in 2024 and is projected to reach USD 3.86 Billion by 2032 growing at a CAGR of 18.25% from 2026 to 2032.

Hyper automation is the use of advanced technologies like AI, machine learning and RPA to automate complex business processes, enhancing efficiency and reducing the need for human intervention.

Its applications span industries like healthcare, manufacturing and finance, enabling faster decision-making, streamlining workflows and improving accuracy through automated data analysis, process monitoring and predictive maintenance.

The future of hyper automation lies in greater AI integration, expanding automation to more complex tasks, leading to self-operating systems and fostering innovation across industries, driving cost reduction and enhanced productivity.

Global Hyper Automation Market Dynamics

The key market dynamics that are shaping the global hyper automation market include:

Key Market Drivers:

Rising Demand for Efficiency: Organizations are seeking ways to enhance productivity by automating repetitive tasks, reducing human errors and cutting operational costs. Hyper automation addresses this need by integrating advanced technologies for seamless process optimization.

Advancements in AI and Machine Learning: As AI and machine learning technologies mature, they enable more complex tasks to be automated. This drives hyper automation adoption, allowing businesses to handle large-scale data and make intelligent, real-time decisions.

Increased Adoption of RPA: Robotic Process Automation (RPA) is a key enabler of hyper automation, automating routine business operations. Its growing implementation helps reduce manual work, allowing employees to focus on higher-value tasks, boosting overall efficiency.

Digital Transformation Initiatives: With industries undergoing digital transformation, hyper automation becomes a crucial tool for modernizing legacy systems, enhancing customer experiences and fostering innovation. The demand for digital agility accelerates the market's growth across sectors.

Key Challenges:

Complex Implementation and Integration: Implementing hyper automation requires integrating various technologies like AI, RPA and machine learning across existing systems. This complexity can lead to challenges in compatibility, requiring significant expertise and investment to ensure smooth adoption.

Security and Data Privacy Concerns: As hyper automation involves large-scale data processing, safeguarding sensitive information becomes crucial. Vulnerabilities in automation systems could expose businesses to cyberattacks or data breaches, making security and privacy major challenges for organizations.

Key Trends:

AI-Powered Decision Making: Hyper automation increasingly integrates AI to automate not just routine tasks but also complex decision-making processes. This trend helps businesses predict outcomes, optimize operations and enhance real-time decision accuracy.

Increased Use of Low-Code/No-Code Platforms: The rise of low-code and no-code platforms allows non-technical users to automate processes easily. This democratizes hyper automation, enabling faster deployment of automation solutions across different business functions without heavy IT dependency.

Expansion of Intelligent Document Processing (IDP): Hyper automation is leveraging intelligent document processing to automate the extraction, classification and management of unstructured data from documents. This trend enhances efficiency in industries relying on heavy documentation, like healthcare and finance.

Global Hyper Automation Market Regional Analysis

Here is a more detailed regional analysis of the global hyper automation market:

North America:

According to Verified Market Research, North America is expected to dominate the Global hyper automation market.

North America's strong focus on AI, machine learning and automation technologies drives its leadership in the hyper automation market globally.

The region benefits from early adoption of advanced solutions, fostering rapid digital transformation across various industries.

Leading technology companies based in North America continuously innovate, contributing significantly to the market's expansion and technological advancements.

Widespread use of cloud computing and RPA across businesses in North America accelerates automation adoption, improving operational efficiency and productivity.

Asia-Pacific:

According to Verified Market Research, Asia-Pacific is the fastest growing region in Global hyperautomation market.

The Asia-Pacific region is the most rapidly growing in the hyperautomation market, driven by increasing digital transformation initiatives and technological advancements.

Countries like China, India and Japan are adopting AI, RPA and automation solutions to enhance operational efficiency and competitiveness.

Growing investments in technology infrastructure and government support for automation further boost hyperautomation adoption in the Asia-Pacific region.

Rapid industrialization and a strong focus on improving productivity in sectors like manufacturing and logistics drive significant growth in this region.

Global Hyper Automation Market: Segmentation Analysis

The Global Hyper automation Market is segmented on the basis of Technology, Deployment, Industry Vertical, Organization Size and Geography.

Global Hyper Automation Market, by Technology

Robotic Process Automation (RPA)

Artificial Intelligence (AI) and Machine Learning (ML)

Business Process Management (BPM)

Natural Language Processing (NLP)

Optical Character Recognition (OCR)

Digital Twins

Intelligent Process Automation (IPA)

Predictive Analytics

Based on Technology, the hyper automation market is segmented into various advanced solutions like Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Business Process Management (BPM) and Natural Language Processing (NLP). Artificial intelligence (AI) and machine learning (ML) dominate the worldwide hyper automation market. AI/ML advances automation by enabling intelligent decision-making, increasing efficiency, and streamlining complicated procedures across sectors.

Global Hyper Automation Market, by Deployment

On-premise

Cloud-based

Based on Deployment, the hyper automation market is segmented into on-premise and cloud-based solutions. On-premise deployment provides greater control over data and security but requires significant infrastructure investment. Cloud-based deployment leads the global hyper automation market because to its scalability, flexibility, and cost-effectiveness. It facilitates easy integration of automation technologies and lowers infrastructure costs, resulting with higher usage.

Global Hyper Automation Market, by Industry Vertical

Banking, Financial Services and Insurance (BFSI)

Healthcare and Life Sciences

Manufacturing

Retail and eCommerce

IT and Telecom

Transportation and Logistics

Energy and Utilities

Government and Public Sector

Real Estate and Construction

Based on Industry Vertical, the hyper automation market spans diverse sectors including healthcare, manufacturing, finance, retail and logistics The BFSI industry leads the global hyper automation market due to the significant demand for automation in fraud detection, customer service, and compliance. The industrial sector regularly monitors process optimization.

Global Hyper Automation Market, by Organization Size

Small and Medium Enterprises (SMEs)

Large Enterprises

Based on Organization Size, the hyper automation market is divided into small and medium enterprises (SMEs) and large enterprises. Large organizations lead the global hyper automation market, owing to their extensive resources, complex processes, and increased automation adoption to improve efficiency and scalability. Small and medium-sized enterprises are also gradually increasing their utilization.

Global Hyper Automation Market, by Geography

North America

Europe

Asia-Pacific

Latin America

Middle East & Africa

Based on Geography, the hyperautomation market is notably segmented into North America, Europe, Asia-Pacific, Latin America and the Middle East & Africa. North America leads in adoption due to advanced technology infrastructure and early innovation. Europe follows with significant investments in digital transformation. Asia-Pacific is experiencing rapid growth, driven by increased technology adoption and industrialization. Latin America and the Middle East & Africa are gradually expanding as automation technologies become more accessible.

Key Players

The Global Hyper automation Market study report will provide valuable insight with an emphasis on the global market. The major players in the Hyper automation market include UiPath, Automation Anywhere, Blue Prism, IBM, Microsoft, Pegasystems, Appian, WorkFusion, Kofax, NICE Systems.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with its product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share and market ranking analysis of the above- mentioned players globally.

Hyper Automation Market Recent Developments

In May 2023, UiPath released its 2023.4 platform, introducing new AI-powered features aimed at enhancing automation capabilities. This update included generative AI support, advanced developer tools and improved document understanding capabilities, allowing organizations to automate processes more efficiently and effectively.

In September 2023, Automation Anywhere announced enhancements to its AI-powered automation solutions, focusing on integrating generative AI capabilities to streamline business processes. This update aimed to empower users to create automations using natural language prompts, thus democratizing automation development across organizations.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL HYPER AUTOMATION MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL HYPER AUTOMATION MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL HYPER AUTOMATION MARKET, BY Deployment

• 5.1 Overview
• 5.2 On-premise
• 5.3 Cloud-based

6 GLOBAL HYPER AUTOMATION MARKET, BY TECHNOLOGY

• 6.1 Robotic Process Automation (RPA)
• 6.2 Artificial Intelligence (AI) and Machine Learning (ML)
• 6.3 Business Process Management (BPM)
• 6.4 Natural Language Processing (NLP)
• 6.5 Optical Character Recognition (OCR)
• 6.6 Digital Twins
• 6.7 Intelligent Process Automation (IPA)
• 6.8 Predictive Analytics

7 Global Hyper Automation Market, by Industry Vertical

• 7.1 Banking, Financial Services and Insurance (BFSI)
• 7.2 Healthcare and Life Sciences
• 7.3 Manufacturing
• 7.4 Retail and eCommerce
• 7.5 IT and Telecom
• 7.6 Transportation and Logistics
• 7.7 Energy and Utilities
• 7.8 Government and Public Sector
• 7.9 Real Estate and Construction

8 Global Hyper Automation Market, by Organization Size

• 8.1 Small and Medium Enterprises (SMEs)
• 8.2 Large Enterprises

9 GLOBAL HYPER AUTOMATION MARKET, BY GEOGRAPHY

• 9.1 Overview
• 9.2 North America
  • 9.2.1 U.S.
  • 9.2.2 Canada
  • 9.2.3 Mexico
• 9.3 Europe
  • 9.3.1 Germany
  • 9.3.2 U.K.
  • 9.3.3 France
  • 9.3.4 Rest of Europe
• 9.4 Asia Pacific
  • 9.4.1 China
  • 9.4.2 Japan
  • 9.4.3 India
  • 9.4.4 Rest of Asia Pacific
• 9.5 Rest of the World
  • 9.5.1 Latin America
  • 9.5.2 Middle East and Africa

10 GLOBAL HYPER AUTOMATION MARKET COMPETITIVE LANDSCAPE

• 10.1 Overview
• 10.2 Company Market Ranking
• 10.3 Key Development Strategies

10 COMPANY PROFILES

• 11.1 UiPath
  • 11.1.1 Overview
  • 11.1.2 Financial Performance
  • 11.1.3 Product Outlook
  • 11.1.4 Key Developments
• 11.2 Automation Anywhere
  • 11.2.1 Overview
  • 11.2.2 Financial Performance
  • 11.2.3 Product Outlook
  • 11.2.4 Key Developments
• 11.3 Blue Prism
  • 11.3.1 Overview
  • 11.3.2 Financial Performance
  • 11.3.3 Product Outlook
  • 11.3.4 Key Developments
• 11.4 IBM
  • 11.4.1 Overview
  • 11.4.2 Financial Performance
  • 11.4.3 Product Outlook
  • 11.4.4 Key Developments
• 11.5 Microsoft
  • 11.5.1 Overview
  • 11.5.2 Financial Performance
  • 11.5.3 Product Outlook
  • 11.5.4 Key Developments
• 11.6 Pegasystems
  • 11.6.1 Overview
  • 11.6.2 Financial Performance
  • 11.6.3 Product Outlook
  • 11.6.4 Key Developments
• 11.7 Appian
  • 11.7.1 Overview
  • 11.7.2 Financial Performance
  • 11.7.3 Product Outlook
  • 11.7.4 Key Developments
• 11.8 WorkFusion
  • 11.8.1 Overview
  • 11.8.2 Financial Performance
  • 11.8.3 Product Outlook
  • 11.8.4 Key Developments
• 11.9 Kofax
  • 11.9.1 Overview
  • 11.9.2 Financial Performance
  • 11.9.3 Product Outlook
  • 11.9.4 Key Developments
• 11.10 NICE Systems.
  • 11.10.1 Overview
  • 11.10.2 Financial Performance
  • 11.10.3 Product Outlook
  • 11.10.4 Key Developments

11 Appendix

• 11.1 Related Research