Research > Market Forecast: Process Mining, 2026-2030, Worldwide
27.03.2025
Domain:Application Platforms & Automation
Sub Domain:BPM & Process Automation
Price:$ 3,900
Market Forecast: Process Mining, 2026-2030, Worldwide
Report Description:
QKS Group reveals a Process Mining projected the market is expected to grow at a compound annual growth rate of 22.15% through 2032.
Organizations are using process mining to automate their business processes and drive digital transformation. Process mining uncovers existing processes, models and documents them, and identifies areas for improvement. It promotes transparency and facilitates process automation, enhances operation and employee performance, and simplifies decision-making. AI and machine learning can be incorporated into process mining solutions to optimize complex business processes, detect and remedy issues before implementation, and offer insights for workflow optimization. Process mining is a key technology for achieving hyperautomation and has been integrated with RPA and task mining. Several process mining providers offer integration capabilities with third-party process analysis tools. Overall, AI and machine learning in process mining solutions are assisting organizations in achieving operational excellence.
Key questions this study will answer:
Strategic Market Direction:
With the rise of emerging technologies, including artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) there is an increased demand for process mining solutions. These technologies streamline organization operations by identifying and disseminating various processes. Organizations are strengthening process mining capabilities to allow organizations to visualize the actual process based on different event logs. Organizations are expected to increase the adoption of AI, ML, and RPA to enable them to automatically discover and optimize critical business processes. With the emergence of automated process improvement, process mining will efficiently identify bottlenecks and discover areas of improvement, enabling faster delivery for customers and improving their business experiences. Furthermore, AI-driven process mining will provide organizations with predictive, descriptive, diagnostic, and prescriptive analytics. It will help increase the efficiency and transparency of complex organizational operations with actionable business alerts. Moreover, AI-driven process mining will simulate and optimize processes to help the organization understand dynamic visualization (digital twin) where costs can be saved, and the complexity of the processes can be reduced. While RPA and task mining have benefited many organizations, insufficient analyses are hampering their efficiency to fully automate a process or capture typical user tasks. The integration of task mining, RPA, and process mining enables businesses to bridge these gaps and remain future-ready and adaptable for the highly competitive environment.
Vendors Covered:
ABBYY, Appian, Apromore, BusinessOptix, Celonis, IBM, iGrafx, Inverbis Analytics, QAD, Microsoft, mindzie, mpmX, Pegasystems, Futuroot, process.science, QPR software, SAP Signavio, Software AG, StereoLOGIC, UiPath, workfellow, and UpFlux.
Table of Content:
Chapter 01: Executive Summary
Chapter 02: Market Overview
Chapter 03: Market Forecast Analysis
Chapter 04: Company Profile
Chapter 05: Appendix
List of Figures
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