超自动化市场：全球依技术、部署、产业垂直、组织规模、地区和预测划分

超自动化全球市场规模与预测

2024 年全球超自动化市场价值为 10.1 亿美元，预计到 2032 年将达到 38.6 亿美元，2026 年至 2032 年的复合年增长率为 18.25%。

超自动化是使用人工智慧、机器学习和 RPA 等先进技术来自动化复杂的业务流程，以提高效率并减少人工干预的需要。

其应用涵盖医疗保健、製造业和金融等行业，透过自动化数据分析、流程监控和预测性维护，实现更快的决策、简化的工作流程和提高准确性。

超自动化的未来在于提高人工智慧的整合度，将自动化扩展到更复杂的任务，实现自动驾驶系统，并刺激各行各业的创新，从而推动成本节约和生产力提高。

全球超自动化市场动态

影响全球超自动化市场的关键市场动态：

关键市场驱动因素

效率需求日益增长：企业正在寻求透过自动化重复性任务来提高生产力、减少人为错误并降低营运成本的方法。超自动化透过整合先进技术实现无缝流程最佳化，从而满足了这项需求。

人工智慧和机器学习的进步：随着人工智慧和机器学习技术的成熟，它们能够实现更复杂任务的自动化。这将推动超自动化的普及，使企业能够大规模处理数据并做出智慧的即时决策。

RPA 的采用率不断提升：机器人流程自动化 (RPA) 是超自动化的关键推动因素，可自动执行日常业务业务。 RPA 的采用减少了手动任务，使员工能够专注于更高价值的业务，从而提高整体效率。

因应数位转型：在正在经历数位转型的产业中，超自动化将成为现代化旧有系统、改善客户体验和推动创新的重要工具。对数位化敏捷性的需求将推动各行各业的市场成长。

主要挑战

实施和整合复杂：超自动化需要将人工智慧、机器人流程自动化 (RPA)、机器学习等各种技术整合到现有系统中。这种复杂性可能导致相容性问题，并且需要大量的专业知识和投资才能顺利实施。

安全和资料隐私问题：超自动化涉及大规模资料处理，因此保护敏感资讯至关重要。自动化系统中的漏洞可能使企业面临网路攻击和资料外洩的风险，使安全和隐私成为企业面临的重大挑战。

主要趋势：

人工智慧驱动的决策：超自动化正在整合人工智慧，不仅可以自动化日常任务，还可以自动化复杂的决策流程。这一趋势有助于企业预测结果、优化业务并提高即时决策的准确性。

低程式码/无程式码平台的使用增加：低程式码和无程式码平台的兴起使非技术用户更容易实现流程自动化，使超自动化民主化，并能够在业务功能中快速部署自动化解决方案，而无需过度依赖 IT。

智慧型文件处理 (IDP) 的兴起：超自动化正在利用智慧文件处理技术，自动提取、分类和管理文件中的非结构化资料。这一趋势将提高医疗保健和金融等依赖大量文件製作的行业的效率。

目录

第 1 章全球超自动化市场：简介

• 市场概览
• 研究范围
• 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

• 资料探勘
• 验证
• 第一手资料
• 资料来源列表

第四章 全球超自动化市场展望

• 概述
• 市场动态
  • 驱动程式
  • 限制因素
  • 机会
• 波特五力模型
• 价值链分析

第五章 全球超自动化市场（按部署）

• 概述
• 本地
• 云端基础

第六章 全球超自动化市场（按技术）

• 机器人流程自动化（RPA）
• 人工智慧（AI）和机器学习（ML）
• 业务流程管理 (BPM)
• 自然语言处理（NLP）
• 光学字元辨识 (OCR)
• 数位双胞胎
• 智慧流程自动化（IPA）
• 预测分析

第七章 全球超自动化市场（依产业垂直划分）

• 银行、金融服务和保险（BFSI）
• 医疗保健和生命科学
• 製造业
• 零售与电子商务
• 资讯科技和电讯
• 运输/物流
• 能源与公共产业
• 政府/公共部门
• 房地产与建筑

第八章。全球超自动化市场（按组织规模）

• 中小企业
• 大公司

第九章全球超自动化市场（按地区）

• 概述
• 北美洲
  • 美国
  • 加拿大
  • 墨西哥
• 欧洲
  • 德国
  • 英国
  • 法国
  • 其他欧洲国家
• 亚太地区
  • 中国
  • 日本
  • 印度
  • 其他亚太地区
• 世界其他地区
  • 拉丁美洲
  • 中东和非洲

第十章全球超自动化市场的竞争格局

• 概述
• 各公司市场排名
• 主要发展策略

第十章 公司简介

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

第十一章 附录

• 相关调查

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