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市場調查報告書
商品編碼
2118099

自動化領域的生成式人工智慧：市場佔有率分析、行業趨勢和統計數據、成長預測（2026-2031 年）

Generative AI In Automation - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026 - 2031)
出版日期: | 出版商: Mordor Intelligence | 英文 134 Pages | 商品交期: 2-3個工作天內

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簡介目錄

根據 Mordor Intelligence 預測，自動化領域的生成式人工智慧市場規模將從 2025 年的 98.4 億美元和 2026 年的 124.3 億美元成長到 2031 年的 432.9 億美元，2026 年至 2031 年的年複合成長率（CAGR）為 28.35%。

自動化市場中的生成式人工智慧-IMG1

本報告按解決方案類型（生成式人工智慧平台、自動化輔助駕駛、服務及其他）、部署方式（雲端、本地部署、混合部署）、應用領域（基於生成式人工智慧平台、自動化輔助駕駛、服務及其他）、編配方式（雲端、本地部署、混合部署）、應用領域（基於生成式人工智慧的機器人流程自動化、流程最佳化和工作流程編排、對話式和自然語言自動化及其他）、最終用戶（銀行業、金融服務和保險、製造業、IT和電信市場預測以美元計價。

自動化生成式人工智慧市場的趨勢與洞察

從基於規則的自動化到生成式副駕駛的快速轉變。

隨著企業以能夠利用情境資訊的「副駕駛」取代靜態邏輯引擎，自動化領域的生成式人工智慧市場正蓬勃發展。傳統的自動化系統通常需要專家編寫腳本、測試和維護每個流程路徑。根據麻省理工學院史隆管理評論報道，企業採用基於代理的人工智慧的比例在兩年內達到了35%，而傳統人工智慧的採用率在八年內則達到了72%。這種採用模式凸顯了對能夠簡化流程設計並緩解專家瓶頸的工具的需求。 2026年5月，UiPath發布了“UiPath for Coding Agents”，使企業負責人能夠透過自然語言互動來產生、測試、部署和管治自動化流程。這種轉變縮短了新流程的運作時間，並允許更多員工參與自動化流程的創建。

對流程效率和工作流程編配的需求日益成長

企業越來越需要自動化系統來協調跨多個業務系統的代理商、機器人和員工。雖然獨立的機器人可以完成日常任務，但它們無法在更廣泛的工作流程中管理交接、異常處理或批准。 2026 年 4 月，Salesforce 發布了 Agentforce Operations，用於採購、合規和核准工作流程中的後勤部門流程代理。據該公司稱，早期採用者實現了周期時間縮短 50-70%，手動資料輸入導致的錯誤減少了 80%。這些結果解釋了為什麼買家尋求的是編配層，而不是為每個任務添加單獨的自動化產品。因此，在用於自動化的生成式人工智慧市場，對能夠在跨業務應用程式運行並保持流程可見度和人工審核的平台的需求日益成長。

整合傳統OT、IT和邊緣系統的複雜性。

傳統營運技術 (OT) 通常使用比目前 API 設計更老舊的工業通訊協定。這使得它們更難與生產環境中的新型生成式 AI 工具整合。 UiPath 的一項調查發現，在年收入超過 10 億美元的企業中，約 600 位高階主管和 IT 從業人員中有 52% 的人經營混合流程環境，其中靜態流程和動態流程在互不連接的系統中共存。企業可能需要中間件、協定轉換工具和自訂連接器來連接這些環境。這些額外的要素會導致專案成本增加、工期延誤以及營運風險加劇。擁有龐大 ERP 和營運技術 (OT) 堆疊的買家往往更傾向於選擇提供預先建置連接器和更全面部署支援的成熟供應商。

細分市場分析

到了2025年，生成式人工智慧平台在自動化領域佔據31.84%的市場。企業利用超大規模資料中心業者和獨立供應商提供的編配層API作為其自動化程序的通用基礎。這項早期優勢反映了模型API已整合到企業技術堆疊中的價值。隨著平台日益複雜，服務成為第二大類別，對部署、客製化和託管自動化的需求也隨之增加。對於那些希望以最小營運影響擴展熟悉的流程產品的買家而言，自動化輔助工具仍然發揮著至關重要的作用。其他解決方案類型，包括流程挖掘和發現工具，則有助於在部署前進行前期工作，以確定合適的流程。

預計到2031年，人工智慧代理和基於代理的自動化平台將以31.08%的複合年成長率成長。此細分市場自動化規模的擴張主要源自於從輔助工具轉變為能夠跨應用執行多階段任務的系統。輔助工具通常提供操作建議，而代理則可以在既定的控制下完成操作。 2026年5月，IBM發布了新一代watsonx Orchestrate，它是一種“基於代理的控制平面”，支援在一致的策略應用下部署來自不同來源的代理。這種設計滿足了對來自多個技術供應商的代理商管治的需求。隨著企業在更多業務流程中部署代理，對管治、監控和互通性的需求預計將會增加。具備策略控制和整合能力的供應商能夠很好地滿足這些需求。因此，自動化領域的生成式人工智慧市場正朝向兼顧自主工作和課責管理的平台轉型。

到2025年，雲端部署將佔據自動化領域生成式人工智慧市場的75.42%。透過利用超大規模資料中心業者，企業無需承擔本地基礎設施的資本成本，即可獲得先進的模型、強大的運算能力和頻繁的產品更新。雲端服務也縮短了啟動試點營運和新增用戶所需的時間。雖然本地部署市場佔有率仍然較小，但對於那些無法將工作流程資料遷移到受控環境之外的組織而言，它仍然至關重要。政府機構和受監管企業通常需要對資料儲存位置和系統存取進行更嚴格的控制。即使雲端服務仍然是主要的交付模式，這些需求仍然維持了本地部署的重要性。

預計2026年至2031年間，混合部署的複合年成長率將達到29.76%。各組織機構正在採用混合設計，利用公共端點進行通用推理，同時將敏感的訓練資料和微調工作保存在受控環境中。這種架構並非意味著全面放棄雲端服務；相反，它使企業能夠根據資料敏感度和營運需求來分離工作負載。 2026年5月，UiPath更新了其自動化套件，以在AWS、Azure和OpenShift環境中提供基於本地代理的AI功能。該產品面向無法透過外部雲端API傳輸工作流程資料的公共部門和受監管用戶。亞太和中東地區的買家可能會更加重視混合部署和本地部署，因為這些地區的資料主權政策更為嚴格。預計自動化領域的生成式AI市場將繼續廣泛利用雲端基礎設施，而混合系統將滿足安全性和合規性需求。

區域分析

預計到2025年，北美將佔據自動化領域生成式人工智慧市場的40.52%。這主要得益於該地區超大規模運算基礎設施、企業軟體供應商以及銀行、金融和保險（BFSI）和科技業的早期採用者的集中。美國仍然是該地區的主要需求中心，因為金融服務、科技和政府機構可以透過成熟的企業平台利用人工智慧自動化。在2026年Build開發者大會上，微軟宣布Windows Agent Framework原生支援桌面人工智慧編配，並擴展了Copilot Studio連接器，從而將自動化領域的生成式人工智慧市場擴展到涵蓋整個企業員工工具領域。加拿大和墨西哥則透過IT現代化和近岸服務（包括注重成本效益的後勤部門自動化）做出貢獻。這些因素將使該地區保持主導地位，同時為基於代理的新功能創造大規模的應用基礎。

預計亞太地區在2026年至2031年間將以30.83%的複合年成長率成長，政府主導的工業人工智慧計畫、不斷擴展的數位基礎設施以及不同程度的自動化成熟度將共同塑造市場需求。中國的「人工智慧+製造」行動計畫旨在2027年開發1000個先進的工業人工智慧代理，為自動化領域的生成式人工智慧市場帶來政策主導的製造業需求。日本正在將生成式人工智慧應用於品管、預測性維護和供應鏈協調，而印度則將不斷成長的用戶群體與部署和交付自動化解決方案的技術服務產業相結合。各國在部署能力、資料法規和產業結構的差異將決定各國從關注到大規模應用的速度。因此，儘管亞太地區的成長環境比北美更為複雜多樣，但在工業和企業應用方面均展現出穩健的前景。

歐洲仍然是至關重要的地區，德國、英國和法國在製造業、金融服務業和公共部門領域引領人工智慧的應用。然而，人工智慧的高風險需求可能會導致更長的開發週期，並增加對管治自動化的需求。中東市場，特別是沙烏地阿拉伯和阿拉伯聯合大公國，正透過國家主導的人工智慧計畫、智慧政府計畫和產業多元化不斷擴張，為生成式人工智慧在自動化領域的應用創造了新的環境。非洲仍處於起步階段，南非和埃及在金融服務和電信領域的應用是推動發展的動力，但基礎設施的差異和準備不足限制了其更廣泛的應用。在以巴西和阿根廷為首的南美洲，銀行、金融和保險（BFSI）以及電子商務自動化領域的需求日益成長，但高效能運算資源的匱乏和法規結構的尚不完善可能會減緩其應用速度，使其不及其他新興地區。

其他好處

  • Excel格式的市場預測（ME）表
  • 3個月的分析師支持

目錄

第1章：引言

  • 研究假設和市場定義
  • 調查範圍

第2章：調查方法

第3章執行摘要

第4章 市場狀況

  • 市場概覽
  • 市場促進因素
    • 從基於規則的自動化到生成式副駕駛的快速轉變。
    • 對流程效率和工作流程編配的需求日益成長
    • 生成式人工智慧在自動化開發、故障排除和維護支援的應用日益廣泛。
    • 擴大智慧RPA在後勤部門和現場工作流程的應用。
    • 企業對人工智慧驅動的流程發現和自動化開發的需求日益成長。
    • 在受監管的自動化應用案例中，需要「人機互動」的可審計性。
  • 市場限制因素
    • 整合傳統OT、IT和邊緣系統的複雜性。
    • 營運環境中的資料隱私、智慧財產權外洩和幻覺風險
    • 中小型工廠的投資報酬率前景仍不明朗。
    • 運算能力、延遲、可擴展性和模型部署限制
  • 價值和供應鏈分析
  • 監理情勢
  • 技術展望
  • 波特五力分析

第5章 市場規模與成長預測

  • 按解決方案類型
    • 下一代的AI平台
    • 自動化副駕駛
    • 人工智慧代理和基於代理的自動化平台
    • 服務
    • 其他解決方案類型
  • 不同的發展
    • 雲
    • 現場
    • 混合
  • 透過使用
    • 利用生成式人工智慧的機器人流程自動化
    • 流程最佳化與工作流程編配
    • 基於對話和自然語言的自動化
    • 其他
  • 最終用戶
    • BFSI
    • 製造業
    • 資訊科技/通訊
    • 醫療保健和生命科學
    • 零售與電子商務
    • 政府/公共部門
    • 能源與公共產業
    • 運輸/物流
    • 媒體與娛樂
    • 其他
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
      • 墨西哥
    • 南美洲
      • 巴西
      • 阿根廷
      • 其他南美國家
    • 歐洲
      • 德國
      • 英國
      • 法國
      • 義大利
      • 西班牙
      • 俄羅斯
      • 其他歐洲國家
    • 亞太地區
      • 中國
      • 日本
      • 印度
      • 韓國
      • 澳洲
      • 其他亞太國家
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 土耳其
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 其他非洲地區

第6章 競爭情勢

  • 市場集中度
  • 策略趨勢
  • 市佔率分析
  • 公司簡介
    • Microsoft Corporation
    • Amazon Web Services, Inc.
    • UiPath Inc.
    • International Business Machines Corporation
    • Google DeepMind Technologies Limited
    • Oracle Corporation
    • Salesforce, Inc.
    • Siemens AG
    • Automation Anywhere, Inc.
    • C3.ai, Inc.
    • SAP SE
    • Schneider Electric SE
    • Rockwell Automation, Inc.
    • Honeywell International Inc.
    • GE Vernova Inc.
    • ServiceNow, Inc.
    • Pegasystems Inc.
    • Databricks, Inc.
    • OpenAI, LLC
    • NVIDIA Corporation

第7章 市場機會與未來展望

簡介目錄
Product Code: 100851

According to Mordor Intelligence, the generative AI in automation market size is projected to expand from USD 9.84 billion in 2025 and USD 12.43 billion in 2026 to USD 43.29 billion by 2031, registering a CAGR of 28.35% between 2026 and 2031.

Generative AI In Automation - Market - IMG1

This report is Segmented by Solution (Generative AI Platforms, Automation Copilots, Services, and More), Deployment (Cloud, On-Premises, and Hybrid), Application (Gen AI RPA, Process Optimization, Conversational, Other Applications), End User (BFSI, Manufacturing, IT and Telecom, Healthcare, Retail, Government, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Generative AI In Automation Market Trends and Insights

Rapid Shift From Rule-Based Automation to Generative Copilots

The generative AI in automation market is benefiting as enterprises replace rigid logic engines with copilots that can work with contextual information. Older automation systems often required specialists to script, test, and maintain each process path. Agentic AI reached 35% enterprise adoption within 2 years, while traditional AI reached 72% over 8 years, according to MIT Sloan Management Review. This adoption pattern supports demand for tools that simplify process design and reduce specialist bottlenecks. UiPath released UiPath for Coding Agents in May 2026, enabling enterprise coding agents to generate, test, deploy, and govern automations through natural-language conversation. The change can shorten the time required to place new processes into operation and make automation creation accessible to a wider group of employees.

Rising Demand for Process Efficiency and Workflow Orchestration

Organizations increasingly need automation that coordinates agents, bots, and employees across several business systems. Isolated bots can complete routine tasks, but they do not manage the handoffs, exceptions, and approvals within broader workflows. Salesforce launched Agentforce Operations in April 2026 for back-office process agents used across procurement, compliance, and approval workflows. The company reported that early adopters reduced cycle times by 50-70% and manual data-entry errors by 80%. These results explain why buyers are looking for orchestration layers rather than adding separate automation products for each task. The generative AI in automation market, therefore, favors platforms that can work across business applications while retaining process visibility and human review.

Integration Complexity Across Legacy OT, IT, and Edge Systems

Legacy operational technology often uses industrial communication protocols that predate current API designs. This makes it more difficult to connect to newer generative AI tools in production environments. UiPath found that 52% of nearly 600 C-suite and IT practitioners at organizations with more than USD 1 billion in revenue operated hybrid process environments that mixed static and dynamic processes across disconnected systems. Organizations may need middleware, protocol translators, and custom connectors to bridge these environments. These additions can raise project costs, increase latency, and introduce additional operational risks. Buyers with extensive ERP and operational technology stacks may favor established providers with pre-built connectors and deeper implementation support.

Other drivers and restraints analyzed in the detailed report include:

  1. Generative AI for Automation Development, Troubleshooting, and Maintenance
  2. Intelligent RPA Across Back-Office and Shop-Floor Workflows
  3. Data Privacy, IP Leakage, and Hallucination Risk in Operational Environments

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Generative AI Platforms held 31.84% of the generative AI in automation market share in 2025. Enterprises used orchestration-layer APIs from hyperscalers and independent software vendors as a common foundation for automation programs. Their early position reflects the value of having model APIs already embedded in enterprise stacks. Services formed the next large category because implementation, customization, and managed automation needs rise with platform complexity. Automation Copilots also retained an important role for buyers who wanted to extend familiar workflow products with limited disruption. Other solution types, including process mining and discovery tools, supported upstream work to identify suitable processes before deployment.

AI Agents and Agentic Automation Platforms are projected to expand at a CAGR of 31.08% through 2031. The segment's generative AI in automation market size is supported by the move from assistive tools to systems that can perform multi-step work across applications. Copilots generally recommend actions, while agents can complete actions under defined controls. IBM presented the next generation of watsonx Orchestrate in May 2026 as an agentic control plane that can deploy agents from different sources with consistent policy enforcement. This design addresses the need to govern agents that come from several technology suppliers. Demand for governance, monitoring, and interoperability should rise as enterprises place agents in more business processes. Providers with policy controls and integration capabilities are better positioned to serve this requirement. The generative AI in automation market is therefore shifting toward platforms that balance autonomous work with accountable management.

Cloud deployment commanded 75.42% of the generative AI in automation market share in 2025. Enterprises used hyperscaler infrastructure to access advanced models, elastic compute capacity, and frequent product updates without incurring capital costs for local infrastructure. Cloud services also reduced the time needed to begin a pilot or add new users. The on-premises segment was smaller, but it remained important for organizations that could not move workflow data outside controlled environments. Government agencies and regulated businesses often require stronger control over data location and system access. These needs kept on-premises deployment relevant even as cloud services remained the main delivery model.

Hybrid deployment is projected to grow at a CAGR of 29.76% from 2026 to 2031. Organizations are using hybrid designs to keep sensitive training data and fine-tuning work in controlled environments while using public endpoints for general inference. This structure does not represent a broad withdrawal from cloud services. Instead, it allows firms to separate workloads according to data sensitivity and operational requirements. UiPath updated Automation Suite in May 2026 to provide on-premises agentic AI capabilities across AWS, Azure, and OpenShift environments. The product targets public-sector and regulated users that cannot route workflow data through external cloud APIs. Asia-Pacific and Middle East buyers may place more weight on hybrid and on-premises deployments where data-sovereignty policies are more directive. The generative AI in automation market will continue to use cloud infrastructure widely, while hybrid systems address security and compliance needs.

Complete Report Scope:

  • By Solution Type
    • Generative AI Platforms
    • Automation Copilots
    • AI Agents and Agentic Automation Platforms
    • Services
    • Other Solution Types
  • By Deployment
    • Cloud
    • On-premises
    • Hybrid
  • By Application
    • Generative AI-Enabled Robotic Process Automation
    • Process Optimization and Workflow Orchestration
    • Conversational and Natural-Language Automation
    • Other Applications
  • By End User
    • BFSI
    • Manufacturing
    • IT and Telecommunications
    • Healthcare and Life Sciences
    • Retail and E-commerce
    • Government and Public Sector
    • Energy and Utilities
    • Transportation and Logistics
    • Media and Entertainment
    • Other End users
  • By Geography
    • North America
      • United States
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Rest of South America
    • Europe
      • Germany
      • United Kingdom
      • France
      • Italy
      • Spain
      • Russia
      • Rest of Europe
    • Asia-Pacific
      • China
      • Japan
      • India
      • South Korea
      • Australia
      • Rest of Asia-Pacific
    • Middle East
      • Saudi Arabia
      • United Arab Emirates
      • Turkey
      • Rest of Middle East
    • Africa
      • South Africa
      • Egypt
      • Rest of Africa

Geography Analysis

North America held 40.52% of the generative AI in automation market share in 2025, supported by its concentration of hyperscale computing infrastructure, enterprise software suppliers, and early adopters in BFSI and technology. The United States remains the region's main demand center because financial services, technology, and government organizations can use AI automation through established enterprise platforms. Microsoft announced native Windows Agent Framework support for desktop AI orchestration and expanded Copilot Studio connectors during Build 2026, which broadens the generative AI in automation market across enterprise worker tools. Canada and Mexico contribute through IT modernization and nearshore service delivery, including cost-sensitive back-office automation. These conditions preserve the region's leading position while creating a large installed base for newer agentic capabilities.

Asia-Pacific is projected to grow at a CAGR of 30.83% between 2026 and 2031, with government-led industrial AI plans, growing digital infrastructure, and uneven automation maturity shaping demand. China's AI+Manufacturing action plan directs the development of 1,000 high-level industrial AI agents by 2027 and gives the generative AI in automation market a policy-led source of manufacturing demand. Japan is applying generative AI to quality management, predictive maintenance, and supply-chain coordination, while India combines a growing user base with a technology-services sector that deploys and delivers automation solutions. National differences in implementation capacity, data rules, and industrial structures will determine how quickly individual countries convert interest into scaled use. Asia-Pacific therefore has a wider range of growth conditions than North America, but a strong outlook for both industrial and enterprise applications.

Europe retained a significant regional position, with Germany, the United Kingdom, and France supporting adoption across manufacturing, financial services, and public-sector applications, while high-risk AI requirements can lengthen procurement and increase demand for governance automation. Middle East markets, especially Saudi Arabia and the United Arab Emirates, are expanding through sovereign AI programs, smart-government projects, and industrial diversification, which adds new deployment settings for the generative AI in automation market. Africa remains at an earlier stage, led by financial-services and telecommunications applications in South Africa and Egypt, as infrastructure gaps and readiness constraints limit wider uptake. South America, led by Brazil and Argentina, is seeing demand in BFSI and e-commerce automation, although limited high-performance computing access and developing regulatory frameworks may slow adoption compared with other emerging regions.

  1. Microsoft Corporation
  2. Amazon Web Services, Inc.
  3. UiPath Inc.
  4. International Business Machines Corporation
  5. Google DeepMind Technologies Limited
  6. Oracle Corporation
  7. Salesforce, Inc.
  8. Siemens AG
  9. Automation Anywhere, Inc.
  10. C3.ai, Inc.
  11. SAP SE
  12. Schneider Electric SE
  13. Rockwell Automation, Inc.
  14. Honeywell International Inc.
  15. GE Vernova Inc.
  16. ServiceNow, Inc.
  17. Pegasystems Inc.
  18. Databricks, Inc.
  19. OpenAI, L.L.C.
  20. NVIDIA Corporation

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 Introduction

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 Research Methodology

3 Executive Summary

4 MARKET LANDSCAPE

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Rapid Shift From Rule-Based Automation to Generative Copilots
    • 4.2.2 Rising Demand for Process Efficiency and Workflow Orchestration
    • 4.2.3 Growing Adoption of Generative AI for Automation Development, Troubleshooting, and Maintenance Assistance
    • 4.2.4 Growing Adoption of Intelligent RPA Across Back-Office and Shop-Floor Workflows
    • 4.2.5 Growing Enterprise Demand for AI-Powered Process Discovery and Automation Creation
    • 4.2.6 Need for Human-in-the-Loop Auditability in Regulated Automation Use Cases
  • 4.3 Market Restraints
    • 4.3.1 High Integration Complexity Across Legacy OT, IT, and Edge Systems
    • 4.3.2 Data Privacy, IP Leakage, and Hallucination Risk in Operational Environments
    • 4.3.3 Unclear Return on Investment for Small and Mid-Sized Plants
    • 4.3.4 Compute, Latency, Scalability, and Model Deployment Constraints
  • 4.4 Value and Supply Chain Analysis
  • 4.5 Regulatory Landscape
  • 4.6 Technological Outlook
  • 4.7 Porter's Five Forces Analysis
    • 4.7.1 Bargaining Power of Suppliers
    • 4.7.2 Bargaining Power of Buyers
    • 4.7.3 Threat of New Entrants
    • 4.7.4 Threat of Substitutes
    • 4.7.5 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

  • 5.1 By Solution Type
    • 5.1.1 Generative AI Platforms
    • 5.1.2 Automation Copilots
    • 5.1.3 AI Agents and Agentic Automation Platforms
    • 5.1.4 Services
    • 5.1.5 Other Solution Types
  • 5.2 By Deployment
    • 5.2.1 Cloud
    • 5.2.2 On-premises
    • 5.2.3 Hybrid
  • 5.3 By Application
    • 5.3.1 Generative AI-Enabled Robotic Process Automation
    • 5.3.2 Process Optimization and Workflow Orchestration
    • 5.3.3 Conversational and Natural-Language Automation
    • 5.3.4 Other Applications
  • 5.4 By End User
    • 5.4.1 BFSI
    • 5.4.2 Manufacturing
    • 5.4.3 IT and Telecommunications
    • 5.4.4 Healthcare and Life Sciences
    • 5.4.5 Retail and E-commerce
    • 5.4.6 Government and Public Sector
    • 5.4.7 Energy and Utilities
    • 5.4.8 Transportation and Logistics
    • 5.4.9 Media and Entertainment
    • 5.4.10 Other End users
  • 5.5 By Geography
    • 5.5.1 North America
      • 5.5.1.1 United States
      • 5.5.1.2 Canada
      • 5.5.1.3 Mexico
    • 5.5.2 South America
      • 5.5.2.1 Brazil
      • 5.5.2.2 Argentina
      • 5.5.2.3 Rest of South America
    • 5.5.3 Europe
      • 5.5.3.1 Germany
      • 5.5.3.2 United Kingdom
      • 5.5.3.3 France
      • 5.5.3.4 Italy
      • 5.5.3.5 Spain
      • 5.5.3.6 Russia
      • 5.5.3.7 Rest of Europe
    • 5.5.4 Asia-Pacific
      • 5.5.4.1 China
      • 5.5.4.2 Japan
      • 5.5.4.3 India
      • 5.5.4.4 South Korea
      • 5.5.4.5 Australia
      • 5.5.4.6 Rest of Asia-Pacific
    • 5.5.5 Middle East
      • 5.5.5.1 Saudi Arabia
      • 5.5.5.2 United Arab Emirates
      • 5.5.5.3 Turkey
      • 5.5.5.4 Rest of Middle East
    • 5.5.6 Africa
      • 5.5.6.1 South Africa
      • 5.5.6.2 Egypt
      • 5.5.6.3 Rest of Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Market Concentration
  • 6.2 Strategic Moves
  • 6.3 Market Share Analysis
  • 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
    • 6.4.1 Microsoft Corporation
    • 6.4.2 Amazon Web Services, Inc.
    • 6.4.3 UiPath Inc.
    • 6.4.4 International Business Machines Corporation
    • 6.4.5 Google DeepMind Technologies Limited
    • 6.4.6 Oracle Corporation
    • 6.4.7 Salesforce, Inc.
    • 6.4.8 Siemens AG
    • 6.4.9 Automation Anywhere, Inc.
    • 6.4.10 C3.ai, Inc.
    • 6.4.11 SAP SE
    • 6.4.12 Schneider Electric SE
    • 6.4.13 Rockwell Automation, Inc.
    • 6.4.14 Honeywell International Inc.
    • 6.4.15 GE Vernova Inc.
    • 6.4.16 ServiceNow, Inc.
    • 6.4.17 Pegasystems Inc.
    • 6.4.18 Databricks, Inc.
    • 6.4.19 OpenAI, L.L.C.
    • 6.4.20 NVIDIA Corporation

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

  • 7.1 White-space and Unmet-Need Assessment