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市场调查报告书
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1750510

智慧过程自动化市场机会、成长动力、产业趋势分析及 2025 - 2034 年预测

Intelligent Process Automation Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025 - 2034
出版日期: | 出版商: Global Market Insights Inc. | 英文 170 Pages | 商品交期: 2-3个工作天内

价格
简介目录

2024年，全球智慧流程自动化 (IPA) 市场规模达152亿美元，预计到2034年将以14.3%的复合年增长率成长，达到488亿美元。这一快速成长主要得益于各行各业数位转型的日益普及，以及对人工智慧和机器学习等先进技术日益增长的需求，这些技术旨在优化业务营运。企业面临着提升营运效率、削减成本和提供更好客户体验的压力，所有这些都在加速向智慧自动化的转变。 IPA解决方案使企业能够消除手动重复性任务，并透过数据驱动的洞察来改善决策。随着越来越多的企业采用自动化，对可扩展和自适应技术的需求持续激增。市场受益于各种认知技术的整合，使企业能够重新思考其工作流程，进而提高敏捷性、创新性和绩效。各产业越来越多地部署IPA工具，凸显了一个更广泛的趋势：自动化不再只是被视为一种成本削减机制，而是成为竞争优势和数位韧性的关键推动因素。

智慧过程自动化市场 - IMG1

IPA 的主要成长动力之一是支援即时资料处理、模式识别和持续学习的人工智慧元件的整合。凭藉人工智慧功能，IPA 平台可以适应不断变化的业务需求、分析非结构化资料并做出预测性决策。企业正在转向这些工具来提高透明度、减少人为错误并简化大批量操作。云端解决方案和低程式码/无程式码开发平台的日益普及也推动了自动化的发展，使 IPA 更易于在不同业务环境中存取和实施。这些创新正在帮助企业打破孤岛，应对与遗留系统和碎片化资料环境相关的挑战。因此，智慧自动化正日益嵌入到​​核心业务功能中，支援从合规性监控到客户参与的所有方面，同时透过减少纸张使用和能源消耗为永续发展做出贡献。

市场范围
起始年份 2024
预测年份 2025-2034
起始值 152亿美元
预测值 488亿美元
复合年增长率 14.3%

就组件而言，IPA 市场细分为解决方案和服务。解决方案部分在 2024 年占据约 67% 的主导份额，预计在整个预测期内将以超过 15% 的复合年增长率增长。这些平台因其在高级功能和易于部署之间的平衡而吸引了许多行业。透过整合人工智慧、机器学习和机器人流程自动化，IPA 解决方案可以有效率地实现后台和前端工作流程的自动化。它们能够增强合规性、跨职能扩展并减少对手动流程的依赖，使其成为寻求稳定、智慧自动化系统的企业的首选。从文件处理到客户互动管理，这些解决方案可以减少错误、提高资料准确性并支援持续的流程改进。

依部署方式，市场可分为云端部署和本地部署两种模式。云端IPA在2024年占据了62%的市场份额，预计2025年至2034年的复合年增长率将超过14.9%。这些平台拥有许多关键优势，例如更快的实施速度、更强大的整合能力以及远端存取能力，使其成为正在进行数位转型的企业的理想之选。其集中式基础架构以及与SaaS应用程式的兼容性，使企业能够跨部门和地区无缝地实现流程自动化。越来越多的小型和大型组织选择云端部署，以加快合规性、入职培训和交易处理等领域的自动化进程。

按技术划分，市场细分为机器学习 (ML)、自然语言处理 (NLP)、机器人流程自动化 (RPA)、电脑视觉、虚拟代理等。机器学习引领该领域，因为它在提升自动化平台的适应性和智慧性方面发挥了变革性作用。机器学习使系统能够从资料中学习、检测趋势并在无需手动编程的情况下做出决策。它广泛应用于需要预测性洞察和管理复杂或非结构化资料集能力的应用程式。对机器学习的日益依赖凸显了其在推动IPA从基于规则的静态系统向支援战略业务目标的动态、支持学习的解决方案演变方面的重要性。

从地区来看，美国在2024年占据北美市场主导地位，占据该地区约84.4%的收入，创造了近48亿美元的市场规模。美国在数位创新方面的领导地位，加上企业对人工智慧技术的大力采用，使其继续处于智慧自动化领域的前沿。美国市场受益于成熟的IT基础设施、对自动化技术的大量投资以及主要软体供应商的高度集中。随着数位转型成为各行各业的首要任务，预计在整个预测期内，对敏捷、智慧且可扩展的自动化平台的需求将保持强劲。

目录

第一章：方法论与范围

第二章：执行摘要

第三章：行业洞察

  • 产业生态系统分析
  • 供应商格局
    • 技术提供者
    • 系统整合商
    • 云端和基础设施供应商
    • 最终用途
  • 川普政府关税的影响
    • 贸易影响
      • 贸易量中断
      • 报復措施
    • 对产业的影响
      • 供应方影响（原料）
        • 主要材料价格波动
        • 供应链重组
        • 生产成本影响
      • 需求面影响（客户成本）
        • 价格传导至终端市场
        • 市占率动态
        • 消费者反应模式
    • 受影响的主要公司
    • 策略产业反应
      • 供应链重组
      • 定价和产品策略
      • 政策参与
    • 展望与未来考虑
  • 利润率分析
  • 技术与创新格局
  • 专利分析
  • 用例
  • 重要新闻和倡议
  • 监管格局
  • 衝击力
    • 成长动力
      • 快速数位转型
      • 人工智慧和机器学习在业务流程中的集成
      • 机器人流程自动化（RPA）的采用日益增多
      • 云端采用和 SaaS 扩展
    • 产业陷阱与挑战
      • 实施成本高
      • 资料隐私和安全问题
  • 成长潜力分析
  • 波特的分析
  • PESTEL分析

第四章：竞争格局

  • 介绍
  • 公司市占率分析
  • 竞争定位矩阵
  • 战略展望矩阵

第五章：市场估计与预测：按组件，2021 - 2034 年

  • 主要趋势
  • 解决方案
  • 服务
    • 专业服务
    • 託管服务

第六章：市场估计与预测：依部署模型，2021 - 2034 年

  • 主要趋势
  • 基于云端
  • 本地

第七章：市场估计与预测：依技术分类，2021 - 2034 年

  • 主要趋势
  • 机器学习（ML）
  • 自然语言处理（NLP）
  • 机器人流程自动化（RPA）
  • 电脑视觉
  • 虚拟代理
  • 其他的

第八章：市场估计与预测：依组织规模，2021 - 2034 年

  • 主要趋势
  • 大型企业
  • 中小企业

第九章：市场估计与预测：按应用，2021 - 2034

  • 主要趋势
  • 业务流程自动化
  • IT营运
  • 应用程式管理
  • 内容管理
  • 安全管理
  • 其他的

第十章：市场估计与预测：依最终用途，2021 - 2034 年

  • 主要趋势
  • 金融服务业
  • 卫生保健
  • 零售
  • IT和电信
  • 传播、媒体与教育
  • 製造业
  • 物流、能源和公用事业
  • 其他的

第 11 章：市场估计与预测：按地区，2021 年至 2034 年

  • 主要趋势
  • 北美洲
    • 我们
    • 加拿大
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 义大利
    • 西班牙
    • 俄罗斯
    • 北欧人
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 韩国
    • 澳新银行
    • 东南亚
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • MEA
    • 阿联酋
    • 沙乌地阿拉伯
    • 南非

第十二章：公司简介

  • AntWorks
  • Appian
  • Automation Anywhere
  • Blue Prism
  • Cognizant Technology Solutions
  • HCLTech
  • HelpSystems
  • IBM
  • Infosys
  • Kofax
  • Microsoft
  • NICE
  • Oracle Corporation
  • Pegasystems
  • Salesforce
  • SAP SE
  • Tata Consultancy Services (TCS)
  • UiPath
  • Wipro
  • WorkFusion
简介目录
Product Code: 13903

The Global Intelligent Process Automation (IPA) Market was valued at USD 15.2 billion in 2024 and is estimated to grow at a CAGR of 14.3% to reach USD 48.8 billion by 2034. This rapid growth is largely fueled by the increasing adoption of digital transformation across industries and the rising need for advanced technologies like artificial intelligence and machine learning to optimize business operations. Companies are under pressure to enhance operational efficiency, cut costs, and deliver better customer experiences-all of which are accelerating the shift toward intelligent automation. IPA solutions are enabling organizations to eliminate manual, repetitive tasks and improve decision-making through data-driven insights. As more businesses embrace automation, the demand for scalable and adaptive technologies continues to surge. The market is benefiting from the convergence of various cognitive technologies, allowing businesses to rethink their workflows for greater agility, innovation, and performance. Increasing deployment of IPA tools across sectors highlights a broader trend where automation is no longer viewed solely as a cost-cutting mechanism but as a key enabler of competitive advantage and digital resilience.

Intelligent Process Automation Market - IMG1

One of the major growth drivers for IPA is the integration of artificial intelligence components that support real-time data processing, pattern recognition, and continuous learning. With AI capabilities, IPA platforms can adapt to changing business needs, analyze unstructured data, and make predictive decisions. Organizations are turning to these tools to increase transparency, reduce human error, and streamline high-volume operations. The push toward automation is also being bolstered by the growing availability of cloud-based solutions and low-code/no-code development platforms, making IPA more accessible and easier to implement across diverse business environments. These innovations are helping companies break down silos and address challenges associated with legacy systems and fragmented data landscapes. As a result, intelligent automation is becoming increasingly embedded in core business functions, supporting everything from compliance monitoring to customer engagement, all while contributing to sustainability efforts by reducing paper usage and energy consumption.

Market Scope
Start Year2024
Forecast Year2025-2034
Start Value$15.2 Billion
Forecast Value$48.8 Billion
CAGR14.3%

In terms of components, the IPA market is segmented into solutions and services. The solutions segment held a dominant share of approximately 67% in 2024 and is anticipated to grow at a CAGR exceeding 15% throughout the forecast period. These platforms appeal to a wide range of industries due to their balance of advanced features and ease of deployment. By incorporating AI, machine learning, and robotic process automation, IPA solutions can automate both back-office and front-end workflows efficiently. Their ability to enhance compliance, scale across functions, and reduce dependency on manual processes makes them a preferred choice for enterprises seeking stable, intelligent automation systems. From document processing to customer interaction management, these solutions enable error reduction, improve data accuracy, and support continuous process improvement.

Based on deployment, the market is categorized into cloud-based and on-premises models. Cloud-based IPA held the majority share of 62% in 2024 and is projected to expand at a CAGR of over 14.9% from 2025 to 2034. These platforms offer key advantages such as faster implementation, better integration capabilities, and remote accessibility, making them ideal for businesses undergoing digital transformation. Their centralized infrastructure and compatibility with SaaS applications allow companies to automate processes seamlessly across different departments and geographies. Both small and large organizations are increasingly opting for cloud deployment to speed up automation efforts in areas like compliance, onboarding, and transactional processing.

By technology, the market is segmented into machine learning (ML), natural language processing (NLP), robotic process automation (RPA), computer vision, virtual agents, and others. Machine learning leads the segment due to its transformative role in enhancing the adaptability and intelligence of automation platforms. ML allows systems to learn from data, detect trends, and make decisions without manual programming. It is widely used for applications that require predictive insights and the ability to manage complex or unstructured datasets. The growing reliance on machine learning underscores its importance in driving the evolution of IPA from static rule-based systems to dynamic, learning-enabled solutions that support strategic business goals.

Regionally, the United States dominated the North American market in 2024, capturing around 84.4% of the regional revenue and generating close to USD 4.8 billion. The country's leadership in digital innovation, combined with strong enterprise adoption of AI-powered technologies, continues to position it at the forefront of intelligent automation. The U.S. market benefits from a mature IT infrastructure, substantial investment in automation technologies, and a high concentration of major software vendors. With digital transformation being a top priority across industries, the demand for agile, intelligent, and scalable automation platforms is expected to remain strong throughout the forecast period.

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 3600 synopsis, 2021 - 2034

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
  • 3.2 Supplier landscape
    • 3.2.1 Technology providers
    • 3.2.2 System integrators
    • 3.2.3 Cloud and infrastructure providers
    • 3.2.4 End use
  • 3.3 Impact of Trump administration tariffs
    • 3.3.1 Trade impact
      • 3.3.1.1 Trade volume disruptions
      • 3.3.1.2 Retaliatory measures
    • 3.3.2 Impact on industry
      • 3.3.2.1 Supply-side impact (raw materials)
        • 3.3.2.1.1 Price volatility in key materials
        • 3.3.2.1.2 Supply chain restructuring
        • 3.3.2.1.3 Production cost implications
      • 3.3.2.2 Demand-side impact (Cost to customers)
        • 3.3.2.2.1 Price transmission to end markets
        • 3.3.2.2.2 Market share dynamics
        • 3.3.2.2.3 Consumer response patterns
    • 3.3.3 Key companies impacted
    • 3.3.4 Strategic industry responses
      • 3.3.4.1 Supply chain reconfiguration
      • 3.3.4.2 Pricing and product strategies
      • 3.3.4.3 Policy engagement
    • 3.3.5 Outlook & future considerations
  • 3.4 Profit margin analysis
  • 3.5 Technology & innovation landscape
  • 3.6 Patent analysis
  • 3.7 Use cases
  • 3.8 Key news & initiatives
  • 3.9 Regulatory landscape
  • 3.10 Impact forces
    • 3.10.1 Growth drivers
      • 3.10.1.1 Rapid digital transformation
      • 3.10.1.2 Integration of AI and machine learning in business processes
      • 3.10.1.3 Growing adoption of Robotic Process Automation (RPA)
      • 3.10.1.4 Cloud adoption and SaaS expansion
    • 3.10.2 Industry pitfalls & challenges
      • 3.10.2.1 High implementation costs
      • 3.10.2.2 Data privacy and security concerns
  • 3.11 Growth potential analysis
  • 3.12 Porter's analysis
  • 3.13 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 Component, 2021 - 2034 ($Mn)

  • 5.1 Key trends
  • 5.2 Solution
  • 5.3 Services
    • 5.3.1 Professional services
    • 5.3.2 Managed services

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

  • 6.1 Key trends
  • 6.2 Cloud-based
  • 6.3 On-premises

Chapter 7 Market Estimates & Forecast, By Technology, 2021 - 2034 ($Mn)

  • 7.1 Key trends
  • 7.2 Machine Learning (ML)
  • 7.3 Natural Language Processing (NLP)
  • 7.4 Robotic Process Automation (RPA)
  • 7.5 Computer vision
  • 7.6 Virtual agents
  • 7.7 Others

Chapter 8 Market Estimates & Forecast, By Organization Size, 2021 - 2034 ($Mn)

  • 8.1 Key trends
  • 8.2 Large enterprise
  • 8.3 SME

Chapter 9 Market Estimates & Forecast, By Application, 2021 - 2034 ($Mn)

  • 9.1 Key trends
  • 9.2 Business process automation
  • 9.3 IT operations
  • 9.4 Application management
  • 9.5 Content management
  • 9.6 Security management
  • 9.7 Others

Chapter 10 Market Estimates & Forecast, By End Use, 2021 - 2034 ($Mn)

  • 10.1 Key trends
  • 10.2 BFSI
  • 10.3 Healthcare
  • 10.4 Retail
  • 10.5 IT & telecom
  • 10.6 Communication and media & education
  • 10.7 Manufacturing
  • 10.8 Logistics, energy & utilities
  • 10.9 Others

Chapter 11 Market Estimates & Forecast, By Region, 2021 - 2034 ($Mn)

  • 11.1 Key trends
  • 11.2 North America
    • 11.2.1 U.S.
    • 11.2.2 Canada
  • 11.3 Europe
    • 11.3.1 UK
    • 11.3.2 Germany
    • 11.3.3 France
    • 11.3.4 Italy
    • 11.3.5 Spain
    • 11.3.6 Russia
    • 11.3.7 Nordics
  • 11.4 Asia Pacific
    • 11.4.1 China
    • 11.4.2 India
    • 11.4.3 Japan
    • 11.4.4 South Korea
    • 11.4.5 ANZ
    • 11.4.6 Southeast Asia
  • 11.5 Latin America
    • 11.5.1 Brazil
    • 11.5.2 Mexico
    • 11.5.3 Argentina
  • 11.6 MEA
    • 11.6.1 UAE
    • 11.6.2 Saudi Arabia
    • 11.6.3 South Africa

Chapter 12 Company Profiles

  • 12.1 AntWorks
  • 12.2 Appian
  • 12.3 Automation Anywhere
  • 12.4 Blue Prism
  • 12.5 Cognizant Technology Solutions
  • 12.6 HCLTech
  • 12.7 HelpSystems
  • 12.8 IBM
  • 12.9 Infosys
  • 12.10 Kofax
  • 12.11 Microsoft
  • 12.12 NICE
  • 12.13 Oracle Corporation
  • 12.14 Pegasystems
  • 12.15 Salesforce
  • 12.16 SAP SE
  • 12.17 Tata Consultancy Services (TCS)
  • 12.18 UiPath
  • 12.19 Wipro
  • 12.20 WorkFusion