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市场调查报告书
商品编码
1938292
超自动化市场 - 全球产业规模、份额、趋势、机会及预测(按技术类型、部署类型、最终用户、地区和竞争格局划分,2021-2031 年)Hyperautomation Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Technical Type, By Deployment Type, By End User, By Region & Competition, 2021-2031F |
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全球超自动化市场预计将从 2025 年的 458.5 亿美元成长到 2031 年的 1,284.4 亿美元,复合年增长率为 18.73%。
超自动化是指将人工智慧 (AI)、机器学习和机器人流程自动化 (RPA) 等各种技术进行策略性整合,以检测和自动化各种业务和 IT 流程。推动这一市场发展的关键因素包括提高营运效率的迫切需求以及透过消除人工工作流程来降低营运成本的需求。此外,各组织正在加速采用这些框架,以确保业务敏捷性,并将传统基础设施与现代数位环境无缝整合。这不再是昙花一现的趋势,而是正在成为一种持续的策略转型。
| 市场概览 | |
|---|---|
| 预测期 | 2027-2031 |
| 市场规模:2025年 | 458.5亿美元 |
| 市场规模:2031年 | 1284.4亿美元 |
| 复合年增长率:2026-2031年 | 18.73% |
| 成长最快的细分市场 | 云 |
| 最大的市场 | 北美洲 |
儘管有这样的机会,市场仍面临一个重大障碍:能够设计和维护如此复杂、整合生态系统的专业人才严重短缺。实施如此广泛的策略需要当今全球劳动力市场中罕见的专业技术水平。世界经济论坛预测,到2025年,63%的雇主会将技能缺口视为有效业务转型的一大障碍。人才短缺会造成瓶颈,限制自动化计划的扩充性,并延缓许多公司实现投资收益的时间。
机器人流程自动化 (RPA) 与人工智慧的整合正在从根本上改变全球超自动化市场,赋予系统管理非结构化资料和执行复杂决策任务的能力。与仅限于基于规则活动的传统 RPA 不同,生成式人工智慧的整合使自动化框架能够适应不断变化的工作流程、理解自然语言并产生程式码,从而扩展了可自动化流程的范围。这种协同作用正在推动从简单的任务执行向智慧自主系统的转变,而这些系统正迅速成为企业营运现代化的标准。根据 UiPath 于 2024 年 9 月发布的《2024 年自动化专业人士现状报告》,90% 的自动化专业人士目前正在使用人工智慧来改进工作流程,或计划在未来一年内采用人工智慧,这表明该行业正在向高价值的整合解决方案转型。
此外,加速企业数位转型和旧有系统现代化已成为第二个关键支柱,推动企业以统一、敏捷的环境取代孤立的架构。超自动化提供了必要的编配层,以弥合旧有系统与现代云端原生应用之间的差距,从而确保业务永续营运和扩充性。根据 Camunda 于 2024 年 1 月发布的《2024 年流程协作现况》报告,96% 的 IT 和业务领导者认为自动化对其公司的数位转型至关重要。这种承诺也体现在大量的资本投入上,企业力求在竞争中保持优势。 IBM 报告称,到 2024 年,59% 的已在使用人工智慧的公司计划加快并扩大对该技术的投资,以支持这些策略倡议。
全球超自动化市场成长的一大障碍是能够设计和维护整合技术生态系统的专业人才严重短缺。超自动化需要无缝整合不同的技术,例如机器人流程自动化 (RPA)、人工智慧和机器学习,这造成了复杂性,需要具备高水平跨职能专业知识的人才。如今,这类专业人才供不应求,如果缺乏了解如何整合互通工具的人才,企业在将自动化从孤立任务扩展到企业级工作流程时将面临巨大挑战。
人才短缺直接阻碍了市场扩张,导致计划延期和实施风险增加。 2024年底,电脑产业协会(CompTIA)指出了这种人才缺口,45%的专家认为网路安全是最主要的技能缺口,而37%的专家则认为软体开发是关键的技能短缺。这些缺口使得企业难以安全地部署和客製化超自动化平台。因此,企业被迫推迟数位转型,导致对自动化解决方案的整体需求下降,并推迟投资收益的实现。
透过低程式码/无程式码平台实现的开发民主化,正从根本上改变自动化主导的归属,使其从集中式 IT 部门转移到业务部门。借助直觉的视觉化介面,非技术员工(通常被称为「公民开发人员」)可以快速建置和部署应用程序,从而解决紧迫的业务问题。这减少了技术积压,而这种易用性正在推动企业快速采用低程式码/无程式码平台,这些企业希望在不相应增加专业工程人员的情况下扩展数位化能力。微软在 2024 年 10 月的 Power Platform 社群大会上宣布,其低程式码生态系统的每月有效用户已达 4,800 万,这充分体现了员工直接参与数位转型策略的能力日益增强。
同时,流程挖掘在自动化工作流程发现方面的广泛应用正成为成功实施超自动化计画的关键前提。企业不再基于主观假设或静态文件进行自动化,而是利用流程智慧创建实际工作流程的资料驱动地图,并在实施前识别瓶颈和低效环节。这种客观的可见性确保了诸如自主代理之类的先进技术能够在优化的基础上运行,而不是仅仅加速执行有缺陷的流程。根据 Celonis 于 2024 年 10 月发布的《2025 年流程优化报告》,89% 的受访企业领导者表示,人工智慧必须深入了解业务流程的执行方式才能产生有效的结果。
The Global Hyperautomation Market is projected to experience substantial growth, expanding from USD 45.85 Billion in 2025 to USD 128.44 Billion by 2031, representing a CAGR of 18.73%. Hyperautomation involves the strategic orchestration of various technologies, such as artificial intelligence, machine learning, and robotic process automation, to detect and automate a broad spectrum of business and IT processes. The primary forces driving this market include the urgent need for operational efficiency and the imperative to lower operating costs by removing manual workflows. Additionally, organizations are increasingly deploying these frameworks to secure business agility and enable the smooth integration of legacy infrastructure with modern digital environments, establishing this as a lasting strategic shift rather than a temporary trend.
| Market Overview | |
|---|---|
| Forecast Period | 2027-2031 |
| Market Size 2025 | USD 45.85 Billion |
| Market Size 2031 | USD 128.44 Billion |
| CAGR 2026-2031 | 18.73% |
| Fastest Growing Segment | Cloud |
| Largest Market | North America |
Despite these opportunities, the market faces a significant hurdle due to an acute shortage of skilled professionals qualified to design and sustain these complex, converged ecosystems. The implementation of such extensive strategies demands a level of technical expertise that is currently rare in the global workforce. According to the World Economic Forum, 63% of employers in 2025 identified skills gaps as the main barrier to effective business transformation. This scarcity of talent creates a bottleneck that restricts the scalability of automation projects and postpones the realization of return on investment for numerous enterprises.
Market Driver
The convergence of Robotic Process Automation (RPA) with Artificial Intelligence is fundamentally transforming the Global Hyperautomation Market by empowering systems to manage unstructured data and execute complex decision-making tasks. Unlike traditional RPA, which is typically restricted to rule-based activities, the incorporation of generative AI enables automation frameworks to adapt to changing workflows, interpret natural language, and generate code, thereby broadening the range of automatable processes. This synergy is rapidly becoming the standard for modernizing enterprise operations, shifting from simple task execution to intelligent, autonomous systems. In the September 2024 'State of the Automation Professional Report 2024' by UiPath, 90% of automation professionals confirmed they are currently using or plan to use AI within the next year to improve their workflows, highlighting the industry's move toward high-value integrated solutions.
Furthermore, accelerated enterprise digital transformation and legacy modernization act as a second critical pillar, driving organizations to replace siloed architectures with unified, agile environments. Hyperautomation provides the essential orchestration layer required to bridge the gap between legacy systems and modern cloud-native applications, ensuring both business continuity and scalability. According to Camunda's '2024 State of Process Orchestration' report from January 2024, 96% of IT and business leaders asserted that automation is vital to their digital transformation efforts. As companies strive to remain competitive, this commitment is reflected in significant capital allocation; IBM reported in 2024 that 59% of enterprises already working with AI intend to accelerate and increase investment in the technology to support these strategic initiatives.
Market Challenge
A major obstacle hindering the growth of the Global Hyperautomation Market is the severe shortage of skilled professionals capable of architecting and maintaining converged technology ecosystems. Hyperautomation necessitates the seamless integration of distinct technologies, including Robotic Process Automation (RPA), artificial intelligence, and machine learning, creating a complexity that demands a workforce with advanced, cross-functional expertise. Currently, such expertise is in short supply, and without personnel who understand how to orchestrate these interoperable tools, organizations encounter significant difficulties in scaling automation from isolated tasks to enterprise-wide workflows.
This talent deficit directly restricts market expansion by delaying project timelines and elevating implementation risks. In late 2024, the Computing Technology Industry Association (CompTIA) highlighted this disparity, noting that 45% of professionals identified cybersecurity as the area with the widest skills gap, while 37% cited software development as a critical shortage. These gaps render organizations unable to securely deploy or customize hyperautomation platforms. Consequently, businesses are forced to slow their digital transformation initiatives, reducing the overall demand for automation solutions and postponing the realization of return on investment.
Market Trends
The democratization of development via Low-Code and No-Code platforms is fundamentally shifting the ownership of automation from centralized IT departments to business units. By leveraging intuitive visual interfaces, non-technical employees-often referred to as citizen developers-can rapidly build and deploy applications to solve immediate operational challenges, thereby alleviating technical backlogs. This accessibility has driven massive adoption rates across enterprises aiming to scale their digital capabilities without proportional increases in specialized engineering staff. As evidence of this expansion, Microsoft announced at the 'Power Platform Community Conference' in October 2024 that the monthly active user base for its low-code ecosystem had reached 48 million, reflecting the workforce's growing ability to contribute directly to digital transformation strategies.
Simultaneously, the widespread application of process mining for automated workflow discovery is emerging as a critical prerequisite for successful hyperautomation initiatives. Rather than automating based on subjective assumptions or static documentation, organizations are now deploying process intelligence to create data-driven maps of their actual workflows, identifying bottlenecks and inefficiencies prior to implementation. This objective visibility ensures that advanced technologies, such as autonomous agents, operate on optimized foundations rather than merely accelerating flawed procedures. According to Celonis's '2025 Process Optimization Report' from October 2024, 89% of business leaders surveyed indicated that artificial intelligence must possess a deep understanding of how business processes execute to deliver effective outcomes.
Report Scope
In this report, the Global Hyperautomation Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Hyperautomation Market.
Global Hyperautomation Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: