Automating business processes with AI agents: maintaining control
Integrating generative AI into corporate processes using BPMN 2.0 and DMN for secure AI agent orchestration and maintaining system control.
EXPERT
Marta Polianska
Lead BPM Consultant
Works on practical business-transformation questions, from defining decisions and roles to validating processes, data and team readiness.
Publications
Secure process automation using AI agents: risk mitigation architecture
How to integrate autonomous AI agents into enterprise systems, avoid the risk of Excessive Agency, and maintain full control using BPMN 2.0 orchestration and DMN rules.
Automation antipatterns: chaos, RPA, and AI risks
How to avoid cementing inefficiencies, replace fragile RPA scenarios with reliable API integrations, and safely implement AI into operational workflows using BPMN and DMN standards.
Overview of BPM platforms: process orchestration using BPMN 2.0 and DMN standards
An analysis of architectural approaches to business process automation. Comparing Scriptum, Camunda, Bonita, and UiPath to eliminate shadow processes and enable flexible modeling.
Process modeling standards: BPMN, CMMN, and DMN
Effective enterprise process automation requires separating workflow orchestration, flexible case management, and business rules. Learn how to avoid hardcoded logic and identify shadow routes.
Prioritizing business processes for automation: signals, metrics, and ROI
A guide to prioritizing business processes for automation using process mining, BPMN/DMN standards, and evidence-based ROI calculation to avoid common pitfalls.
Understanding BPM versus RPA and workflow automation
A guide to BPM, RPA, and workflow automation for IT architects. Learn how to combine BPMN, DMN, and Process Mining to avoid technical debt and achieve end-to-end orchestration.
BPM and document management: defining the boundary
Documents store facts, while business processes manage actions. Distinguish between DMS/ECM and BPM to avoid data silos and securely integrate AI agents.
RPA after ERP: A Bridge or a Digital Patch?
RPA is a useful temporary bridge to legacy systems following an ERP deployment. However, automating Excel-based workflows, email approvals, and fragmented responsibilities often accelerates technical debt rather than resolving it.
Recursive AI self-improvement: preparing businesses for new challenges
The concept of recursive AI self-improvement is transforming process automation. We explore how companies can prepare their data and manage risks.
AI and RPA: How data and risks define automation success
Integrating AI into RPA is transforming business processes, but success hinges on data readiness and effective risk management. Prepare your data.
Phased legacy ERP migration for uninterrupted transformation
Phased migration of legacy ERP systems in the public sector helps avoid downtime and ensures process continuity by focusing on automation and data.