arXiv:2606.15291v1 Announce Type: new Abstract: Agentic AI opens new opportunities for automating Business Process (BP), enabling autonomous decision-making and dynamic adaptation. However, realising this potential requires BP entities and their interactions to be defined with formal precision. This paper presents a formal framework for Agentic BP analysis through the AGO methodology. AGO captures the modelling perspective in terms of who is acting (Agents), why it is carried out (Goals), and what the relevant entities are (Objects). Grounded in set theory and mathematical logic, we formally d
The rapid advancement in AI capabilities necessitates formal frameworks to ensure reliable, auditable, and effective deployment of agentic systems in complex business environments.
This paper provides a foundational formal framework (AGO methodology) essential for designing and implementing robust Agentic AI in business processes, addressing the crucial need for precision, automation, and dynamic adaptation.
The introduction of a formal methodology for Agentic BP analysis moves beyond ad-hoc implementations towards systematic, verifiable, and scalable agent deployment in business operations.
- · AI platform developers
- · Enterprise software vendors
- · Consulting firms specializing in process automation
- · Organisations with complex business processes
- · Businesses relying on manual process analysis
- · Legacy BP automation providers without AI integration
- · Consultants focused solely on traditional BP re-engineering
Increased precision and reliability in the design and deployment of AI agents for business process automation.
Accelerated adoption of agentic AI within enterprises, leading to significant shifts in workflow management and operational efficiency.
Emergence of new regulatory or audit standards specifically for formally defined agentic business processes, ensuring accountability and compliance.
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