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市場調查報告書
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1859718

人工智慧驅動的流程自動化市場預測至2032年：按組件、部署模式、組織規模、應用、最終用戶和地區分類的全球分析

AI-Driven Process Automation Market Forecasts to 2032 - Global Analysis By Component (Automation Platforms and Professional Services), Deployment Model, Organization Size, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球人工智慧驅動的流程自動化市場預計到 2025 年將達到 154.2 億美元，預計到 2032 年將達到 441.1 億美元，預測期內複合年成長率為 16.2%。

人工智慧驅動的流程自動化正在革新企業營運，它將人工智慧功能與傳統自動化解決方案相結合，幫助企業最佳化日常任務、降低成本並提高生產力。這些系統利用機器學習、自然語言處理和預測分析等工具，能夠分析資料、識別趨勢並自主調整工作流程。這種方法提高了流程的速度、準確性和可靠性，同時讓員工專注於策略性任務。金融、製造、醫療保健和物流等行業正擴大採用人工智慧驅動的自動化技術，以提升競爭力、簡化營運並推動組織內部的創新。

據美國總務管理局 (GSA) 稱，聯邦機構已部署了 200 多個機器人流程自動化 (RPA) 應用案例，每年節省超過 100 萬工時。這些 RPA 系統通常整合人工智慧，用於智慧文檔分類和決策。

決策能力和準確性提升

透過整合機器學習、預測分析和進階數據分析，人工智慧驅動的流程自動化能夠提升組織的決策能力。這些技術可以快速處理大量資料集，識別模式，並提供可操作的洞察，從而支持明智及時的決策。最大限度地減少人為錯誤可以提高營運的準確性和可靠性。企業可以預測問題、最佳化工作流程並採取有效的預防措施。醫療保健、金融和物流等行業可以從精準的數據驅動型策略中獲益匪淺。自動化與智慧決策的結合是推動全球採用人工智慧驅動的流程自動化的關鍵因素，因為各組織都在尋求穩定的績效、降低風險並最佳化業務成果。

高昂的實施成本

實施人工智慧驅動的流程自動化需要在技術、基礎設施和軟體方面進行大量投資，這可能成為推廣應用的一大障礙，尤其對於中小企業而言。不僅初始成本高昂，持續的維護、更新和員工培訓也會造成沉重的財務負擔。大型企業通常能夠承擔這些成本，但中小企業可能難以證明此類投資的合理性。高成本壁壘會影響決策流程，並減緩人工智慧自動化的廣泛應用。因此，儘管人工智慧驅動的流程自動化具有許多商業優勢，但高昂的實施成本仍是各行業企業採用該技術時面臨的一大障礙。

拓展產業解決方案

人工智慧驅動的流程自動化有望為醫療保健、金融、製造和物流等產業催生出產業專用的解決方案。這些客製化解決方案能夠應對產業特有的挑戰，簡化關鍵工作流程，確保合規性，並提升決策水準。透過提供專業的AI自動化服務，供應商可以滿足市場對目標明確、高價值解決方案日益成長的需求。產業專屬的解決方案不僅能提升營運效率，還能幫助企業有效達成其策略目標。在各行業提供客製化的AI驅動流程自動化解決方案，蘊藏著龐大的市場成長機會，能夠推動技術應用，改善客戶體驗，並增強全球競爭力。

員工對變革的抵制

由於擔心失業、工作流程改變以及需要學習新技能，採用人工智慧驅動的流程自動化可能會遇到員工的抵觸情緒。這種抵觸會減緩流程自動化的普及速度，降低效率，並限制自動化的效能。企業應專注於變革管理策略、員工培訓和舉措，以促進員工接受並順利過渡。忽視員工的擔憂會導致士氣低落、效率低下以及人工智慧系統利用率不足。因此，員工的抵觸情緒構成重大威脅，會阻礙流程自動化的普及，並降低其在各行各業的整體效益。

新冠疫情的影響：

新冠疫情對人工智慧驅動的流程自動化市場產生了重大影響，加速了數位化和自動化技術的應用。遠端辦公、業務中斷和保持社交距離等措施迫使企業採用人工智慧驅動的解決方案，以確保業務連續性、簡化流程並減少對人工操作的依賴。醫療保健、物流、金融和電子商務等行業已利用自動化來有效管理日益成長的工作量。此次危機凸顯了營運韌性、擴充性和敏捷性的重要性，促使企業對人工智慧系統進行長期投資。因此，疫情成為了成長的催化劑，凸顯了人工智慧驅動的流程自動化的策略價值，並推動了其在各行業的廣泛應用。

預計在預測期內，現場消費市場將是最大的細分市場。

預計在預測期內，本地部署方案將佔據最大的市場佔有率，因為企業優先考慮自動化平台的控制、安全性和客製化。處理敏感資訊和關鍵業務的公司通常選擇本地部署解決方案，以維護資料隱私、遵守法規並與現有IT基礎設施無縫整合。在企業內部管理 AI主導的工作流程可以減少對外部供應商的依賴，並確保流程監管。需要客製化解決方案來應對獨特工作流程或行業特定需求的公司更傾向於本地部署。總而言之，該細分市場的主導地位是由對強大控制、增強安全性和靈活自動化解決方案的需求所驅動的，使其成為全球企業的首選。

預計醫療保健和生命科學領域在預測期內將實現最高的複合年成長率。

在提升營運效率、改善患者照護和加強監管合規性的迫切需求驅動下，醫療保健和生命科學產業預計將在預測期內實現最高成長率。人工智慧自動化使醫療服務提供者能夠簡化行政工作流程、處理大規模資料集並提高診斷和治療的準確性。生命科學公司正在利用人工智慧加速藥物研發、最佳化臨床試驗並改善研究成果。對數位轉型、成本最佳化和醫療服務改進的投資不斷增加，正在加速人工智慧技術的應用。因此，醫療保健和生命科學產業引領著人工智慧驅動的流程自動化成長，並正在成為全球成長最快的產業。

比最大的地區

在預測期內，北美預計將佔據最大的市場佔有率，這主要得益於其先進的數位基礎設施、人工智慧解決方案的快速普及以及在創新和研發方面的大量投入。醫療保健、金融、製造和IT等各行各業的組織都在利用人工智慧自動化來簡化營運、降低成本並實現更智慧的決策。政府的支持性政策、穩定的監管環境以及高素質的勞動力進一步鞏固了該地區的市場地位。該地區的技術成熟度、早期採用趨勢以及對創新的重視共同強化了其優勢，使北美成為最有可能推動全球各行業和業務職能部門人工智慧驅動流程自動化成長的地區。

複合年成長率最高的地區：

由於數位化加快、人工智慧技術應用日益普及以及自動化投資不斷成長，亞太地區預計將在預測期內實現最高的複合年成長率。中國、印度、日本和韓國等主要國家在製造業、醫療保健、物流和銀行、物流及保險（BFSI）等產業採用人工智慧自動化技術，最佳化營運、降低成本並提高生產力。政府政策、技術創新和不斷壯大的技能型勞動力也進一步推動了該地區的成長。隨著企業專注於效率提升、創新和流程改進，亞太地區可望加速擴張，成為全球人工智慧驅動的流程自動化市場中複合年成長率最高的地區。

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    • 基於產品系列、地域覆蓋和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 原始研究資料
    • 二手研究資料
    • 先決條件

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球人工智慧驅動流程自動化市場（按組件分類）

  • 自動化平台
  • 專業服務

6. 全球人工智慧驅動流程自動化市場（依部署模式分類）

  • 本地部署
  • 雲
  • 混合

7. 全球人工智慧驅動流程自動化市場（依組織規模分類）

  • 主要企業
  • 小型企業

8. 全球人工智慧驅動的流程自動化市場（按應用領域分類）

  • 金融自動化
  • 人力資源流程自動化
  • 客戶互動自動化
  • IT工作流程自動化
  • 採購和庫存自動化
  • 自動化管治與合規

9. 全球人工智慧驅動的流程自動化市場（依最終用戶分類）

  • 銀行、金融服務和保險（BFSI）
  • 製造/物流
  • 醫療保健和生命科學
  • 零售與電子商務
  • 通訊/IT
  • 能源與公共產業
  • 政府/公共部門
  • 媒體與娛樂

第10章：全球人工智慧驅動的流程自動化市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與併購
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第12章 企業概況

  • UiPath
  • Automation Anywhere
  • Blue Prism（SS&C Blue Prism）
  • AutomationEdge
  • AiFA Labs
  • Bizagi
  • Kofax
  • Laiye
  • Voypost
  • Automation House
  • AntWorks
  • Pega
  • SAP
  • Appian
  • IBM
  • DataRobot
Product Code: SMRC31942

According to Stratistics MRC, the Global AI-Driven Process Automation Market is accounted for $15.42 billion in 2025 and is expected to reach $44.11 billion by 2032 growing at a CAGR of 16.2% during the forecast period. AI-driven process automation is revolutionizing business operations by combining AI capabilities with conventional automation solutions. It helps companies optimize routine tasks, lower costs, and boost productivity. Using tools like machine learning, natural language processing, and predictive analytics, these systems can analyze data, recognize trends, and adjust workflows autonomously. This approach enhances process speed, precision, and reliability while freeing employees to engage in strategic tasks. Sectors including finance, manufacturing, healthcare, and logistics are progressively implementing AI-driven automation to improve competitiveness, streamline operations, and foster innovation across their organizations.

According to the U.S. General Services Administration (GSA), over 200 federal use cases of Robotic Process Automation (RPA) have been deployed across agencies, with reported savings of over 1 million labor hours annually. These RPA systems often integrate AI for intelligent document classification and decision-making source.

Market Dynamics:

Driver:

Enhanced decision-making & accuracy

By integrating machine learning, predictive analytics, and advanced data analysis, AI-driven process automation strengthens organizational decision-making. These technologies can rapidly process vast datasets, detect patterns, and deliver actionable insights for informed, timely decisions. Minimizing human errors ensures higher operational accuracy and reliability. Businesses can forecast issues, optimize workflows, and take proactive actions effectively. Sectors including healthcare, finance, and logistics gain significant advantages through precise and data-informed strategies. The combination of automation and intelligent decision-making is a key factor fueling the global adoption of AI-driven process automation, as organizations seek consistent performance, risk mitigation, and optimized operational outcomes.

Restraint:

High implementation costs

Implementing AI-driven process automation requires substantial investment in technology, infrastructure, and software, which can hinder adoption, especially among small and medium businesses. Beyond the initial expenditure, ongoing maintenance, updates, and employee training add to the financial burden. Large corporations can often manage these costs, but smaller firms may find it challenging to justify such investments. The high cost barrier impacts the decision-making process and slows the widespread integration of AI automation. Consequently, despite the operational benefits, high implementation expenses remain a significant restraint for organizations aiming to adopt AI-driven process automation across industries.

Opportunity:

Expansion in industry-specific solutions

AI-driven process automation creates prospects for crafting industry-specific solutions that cater to sectors like healthcare, finance, manufacturing, and logistics. These tailored solutions address unique industry challenges, streamline critical workflows, ensure compliance, and enhance decision-making. By offering specialized AI automation services, providers can meet the increasing demand for targeted, high-value solutions. Industry-focused adoption not only improves operational efficiency but also helps companies achieve strategic goals effectively. Delivering customized AI-driven process automation solutions across diverse sectors presents a major opportunity for market growth, driving adoption, improving customer outcomes, and strengthening competitive positioning worldwide.

Threat:

Resistance to change among workforce

Adopting AI-driven process automation may encounter workforce resistance stemming from concerns about job loss, altered workflows, and the requirement to acquire new skills. Such opposition can slow down implementation, decrease efficiency, and limit automation effectiveness. Companies must focus on change management strategies, employee training, and engagement initiatives to foster acceptance and ease transitions. Ignoring employee concerns can lead to reduced morale, inefficiencies, and underutilization of AI systems. Consequently, resistance from employees represents a notable threat, potentially hindering widespread adoption and diminishing the overall benefits of AI-driven process automation across industries.

Covid-19 Impact:

The COVID-19 outbreak had a profound effect on the AI-driven process automation market, accelerating the adoption of digital and automation technologies. Remote work, operational disruptions, and social distancing measures compelled organizations to implement AI-driven solutions to ensure continuity, streamline processes, and reduce manual dependency. Industries such as healthcare, logistics, finance, and e-commerce leveraged automation to manage increased workloads efficiently. The crisis underscored the importance of operational resilience, scalability, and agility, prompting long-term investments in AI-powered systems. Consequently, the pandemic served as a catalyst for growth, emphasizing the strategic value of AI-driven process automation and driving widespread adoption across diverse sectors.

The on-premise segment is expected to be the largest during the forecast period

The on-premise segment is expected to account for the largest market share during the forecast period, as organizations prioritize control, security, and customization of their automation platforms. Businesses handling sensitive information or critical operations often choose on-premise solutions to maintain data privacy, comply with regulations, and integrate smoothly with existing IT infrastructure. Internal management of AI-driven workflows reduces reliance on external providers and ensures process oversight. Companies requiring bespoke solutions for unique workflows or industry-specific needs prefer on-premise deployments. Overall, this segment's leading position is fueled by the demand for robust control, enhanced security, and flexible automation solutions, making it the preferred choice for enterprises worldwide.

The healthcare & life sciences segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare & life sciences segment is predicted to witness the highest growth rate, driven by the need to enhance operational efficiency, patient care, and compliance with regulations. AI automation enables healthcare providers to simplify administrative workflows, process large datasets, and increase accuracy in diagnostics and treatments. Life sciences firms use AI to speed up drug discovery, optimize clinical trials, and boost research outcomes. Rising investments in digital transformation, cost optimization, and improved healthcare delivery are accelerating adoption. As a result, the Healthcare & Life Sciences segment leads in growth rate, emerging as the most rapidly expanding sector for AI-driven process automation worldwide.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, fueled by advanced digital infrastructure, rapid adoption of AI solutions, and substantial investments in innovation and R&D. Organizations across sectors like healthcare, finance, manufacturing, and IT leverage AI automation to streamline operations, cut costs, and enable smarter decision-making. Supportive government policies, regulatory stability, and a skilled workforce further strengthen the region's market position. The region's technological maturity, early adoption tendencies, and focus on innovation collectively reinforce its dominance, making North America the foremost contributor to global growth in AI-driven process automation across industries and business functions.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid digitalization, increased adoption of AI technologies, and rising investments in automation. Key economies such as China, India, Japan, and South Korea are implementing AI automation to optimize operations, cut costs, and boost productivity in sectors including manufacturing, healthcare, logistics, and BFSI. The region's growth is further supported by government policies, technological innovations, and a growing skilled workforce. With companies focusing on efficiency, innovation, and process improvement, Asia-Pacific is poised for accelerated expansion, establishing itself as the region with the highest CAGR in the global AI-driven process automation market.

Key players in the market

Some of the key players in AI-Driven Process Automation Market include UiPath, Automation Anywhere, Blue Prism (SS&C Blue Prism), AutomationEdge, AiFA Labs, Bizagi, Kofax, Laiye, Voypost, Automation House, AntWorks, Pega, SAP, Appian, IBM and DataRobot.

Key Developments:

In October 2025, IBM announced that it has signed a definitive agreement to acquire Cognitus, a leading SAP S/4HANA services provider, with industry-specific, AI-powered solutions. Cognitus will bring mission-critical SAP skills, including in RISE and GROW with SAP, as well as an extensive portfolio of software assets. This combination of services, software and industry expertise, aligns with IBM's asset-based approach to digital transformation, driving increased productivity and operational efficiency for clients around the world.

In August 2025, SAP and SmartRecruiters announced that SAP has entered into an agreement to acquire SmartRecruiters, a leading talent acquisition (TA) software provider. SmartRecruiters' deep expertise in high-volume recruiting, recruitment automation and AI-enabled candidate experience and engagement are considered an ideal addition to the SAP SuccessFactors human capital management (HCM) suite.

In March 2025, UiPath announced that it has negotiated a new global consulting agreement with a major Electronic Medical Records (EMR) platform to accelerate professional services programs for customers in 16 new countries. With the agreement, UiPath significantly expands its professional services capabilities for healthcare organizations and makes customer and partner access to this EMR platform faster and more seamless.

Components Covered:

  • Automation Platforms
  • Professional Services

Deployment Models Covered:

  • On-Premise
  • Cloud
  • Hybrid

Organization Sizes Covered:

  • Large Enterprises
  • Small & Medium Enterprises (SMEs)

Applications Covered:

  • Finance Automation
  • HR Process Automation
  • Customer Interaction Automation
  • IT Workflow Automation
  • Procurement & Inventory Automation
  • Governance & Compliance Automation

End Users Covered:

  • Banking, Financial Services & Insurance (BFSI)
  • Manufacturing & Logistics
  • Healthcare & Life Sciences
  • Retail & E-Commerce
  • Telecom & IT
  • Energy & Utilities
  • Government & Public Sector
  • Media & Entertainment

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI-Driven Process Automation Market, By Component

  • 5.1 Introduction
  • 5.2 Automation Platforms
  • 5.3 Professional Services

6 Global AI-Driven Process Automation Market, By Deployment Model

  • 6.1 Introduction
  • 6.2 On-Premise
  • 6.3 Cloud
  • 6.4 Hybrid

7 Global AI-Driven Process Automation Market, By Organization Size

  • 7.1 Introduction
  • 7.2 Large Enterprises
  • 7.3 Small & Medium Enterprises (SMEs)

8 Global AI-Driven Process Automation Market, By Application

  • 8.1 Introduction
  • 8.2 Finance Automation
  • 8.3 HR Process Automation
  • 8.4 Customer Interaction Automation
  • 8.5 IT Workflow Automation
  • 8.6 Procurement & Inventory Automation
  • 8.7 Governance & Compliance Automation

9 Global AI-Driven Process Automation Market, By End User

  • 9.1 Introduction
  • 9.2 Banking, Financial Services & Insurance (BFSI)
  • 9.3 Manufacturing & Logistics
  • 9.4 Healthcare & Life Sciences
  • 9.5 Retail & E-Commerce
  • 9.6 Telecom & IT
  • 9.7 Energy & Utilities
  • 9.8 Government & Public Sector
  • 9.9 Media & Entertainment

10 Global AI-Driven Process Automation Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 UiPath
  • 12.2 Automation Anywhere
  • 12.3 Blue Prism (SS&C Blue Prism)
  • 12.4 AutomationEdge
  • 12.5 AiFA Labs
  • 12.6 Bizagi
  • 12.7 Kofax
  • 12.8 Laiye
  • 12.9 Voypost
  • 12.10 Automation House
  • 12.11 AntWorks
  • 12.12 Pega
  • 12.13 SAP
  • 12.14 Appian
  • 12.15 IBM
  • 12.16 DataRobot

List of Tables

  • Table 1 Global AI-Driven Process Automation Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI-Driven Process Automation Market Outlook, By Component (2024-2032) ($MN)
  • Table 3 Global AI-Driven Process Automation Market Outlook, By Automation Platforms (2024-2032) ($MN)
  • Table 4 Global AI-Driven Process Automation Market Outlook, By Professional Services (2024-2032) ($MN)
  • Table 5 Global AI-Driven Process Automation Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 6 Global AI-Driven Process Automation Market Outlook, By On-Premise (2024-2032) ($MN)
  • Table 7 Global AI-Driven Process Automation Market Outlook, By Cloud (2024-2032) ($MN)
  • Table 8 Global AI-Driven Process Automation Market Outlook, By Hybrid (2024-2032) ($MN)
  • Table 9 Global AI-Driven Process Automation Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 10 Global AI-Driven Process Automation Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 11 Global AI-Driven Process Automation Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 12 Global AI-Driven Process Automation Market Outlook, By Application (2024-2032) ($MN)
  • Table 13 Global AI-Driven Process Automation Market Outlook, By Finance Automation (2024-2032) ($MN)
  • Table 14 Global AI-Driven Process Automation Market Outlook, By HR Process Automation (2024-2032) ($MN)
  • Table 15 Global AI-Driven Process Automation Market Outlook, By Customer Interaction Automation (2024-2032) ($MN)
  • Table 16 Global AI-Driven Process Automation Market Outlook, By IT Workflow Automation (2024-2032) ($MN)
  • Table 17 Global AI-Driven Process Automation Market Outlook, By Procurement & Inventory Automation (2024-2032) ($MN)
  • Table 18 Global AI-Driven Process Automation Market Outlook, By Governance & Compliance Automation (2024-2032) ($MN)
  • Table 19 Global AI-Driven Process Automation Market Outlook, By End User (2024-2032) ($MN)
  • Table 20 Global AI-Driven Process Automation Market Outlook, By Banking, Financial Services & Insurance (BFSI) (2024-2032) ($MN)
  • Table 21 Global AI-Driven Process Automation Market Outlook, By Manufacturing & Logistics (2024-2032) ($MN)
  • Table 22 Global AI-Driven Process Automation Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 23 Global AI-Driven Process Automation Market Outlook, By Retail & E-Commerce (2024-2032) ($MN)
  • Table 24 Global AI-Driven Process Automation Market Outlook, By Telecom & IT (2024-2032) ($MN)
  • Table 25 Global AI-Driven Process Automation Market Outlook, By Energy & Utilities (2024-2032) ($MN)
  • Table 26 Global AI-Driven Process Automation Market Outlook, By Government & Public Sector (2024-2032) ($MN)
  • Table 27 Global AI-Driven Process Automation Market Outlook, By Media & Entertainment (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.