Research project AI-Enhanced Enterprise Business Processes Analysis
In collaboration with SAP, this project investigates how AI and object-centric process mining can support enterprise business processes analysis and management. The results are of importance for all organizations looking to improve their efficiency and decision-making.
Modern enterprises generate vast amounts of digital event data. These data come from invoices and payments in finance, purchase orders and deliveries in supply chains, employee onboarding in HR, customer service requests in CRM, and even system access logs in IT operations, just to name a few. Yet traditional methods struggle to capture the complexity of interconnected business processes.
This project is carried out in close collaboration with SAP, one of the world’s leading providers of enterprise systems. We explore how object-centric process mining (OCPM), supported by enterprise AI, can provide more accurate and actionable insights into business workflows. By leveraging SAP’s global expertise and platforms, we will design and test methods for aggregating and analyzing event data to detect inefficiencies, uncover hidden patterns, and support predictive decision-making.
The project is supported by the Business Process Design and Intelligence course at the Department of Computer and Systems Sciences (DSV), which prepares students with essential skills in process modeling, analysis and AI-enabled business transformation. In addition, the project brings opportunities for researchers and PhD students to visit SAP and contribute to this impactful project.
SAP provides resources and opportunities in the form of master thesis positions, PhD student visits, and research collaboration activities. This ensures strong integration between academia and industry, enabling students and researchers to engage directly with real-world enterprise systems and challenges.
Please note: Interested students and collaborators should contact Amin Jalali, rather than contacting SAP colleagues directly. All requests will be coordinated through Stockholm University.
Project description
This project investigates how object-centric process mining (OCPM), combined with enterprise AI, can provide deeper insights into complex business processes. Unlike traditional methods, OCPM focuses on business objects and their interactions, offering a richer view of enterprise workflows.
In close collaboration with SAP, the project develops methods for analyzing large-scale event data to support predictive analysis, compliance monitoring, and process optimization. SAP also contributes by offering master thesis positions, PhD student visits, and collaboration opportunities with PhD students interested in enterprise AI, ensuring strong ties between academia and industry.
The project is closely linked to the Business Process Design and Intelligence (BPDI) course at DSV, which equips students with the skills required to apply process mining and AI in practice. This integration strengthens both research and education, preparing students to meet the demands of digital transformation.
Looking ahead, the project will also expand into exploring advanced topics such as agentic AI to further support and transform Business Process Management (BPM), enabling more adaptive and autonomous enterprise processes.
Project members
Project managers
Amin Jalali
Senior Lecturer, Associate Professor
Members
Majid Rafiei
Shahrzad Khayatbashi
Jiayuan Chen