Agentic AI Readiness: A Process-Oriented Assessment Framework

Are organizations ready for agentic artificial intelligence (AI)? Based on the limited success of AI projects in practice, this paper proposes an approach that recognizes the new potential of agentic AI for automating business processes and posits that business benefits are created at the level of business processes. It presents a framework for evaluating organizational readiness for agentic AI systems that emphasizes their potential of agentic AI systems for business process management. The framework provides a dual assessment: first, it determines the potential readiness across five perspectives (activities, decisions, data operations, control flow, and resource management). Second, it measures process debt, which refers to the gaps between documented and actual practices. Validated through a case study involving 40+ stakeholders and nine processes at a German university, the framework reveals distinct readiness patterns and actionable transformation insights. This enables evidence-based decision-making regarding AI investments and systematic capability building for agentic AI implementation in existing organizational settings.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Business Process Modeling and Analysis
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article
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article

Agentic AI Readiness: A Process-Oriented Assessment Framework

Alfréd Zimmermann, Rainer Alt, Rainer Schmidt
ScholarSpace (University of Hawaii at Manoa)
Business Process Modeling and Analysis
article

Agentic AI Readiness: A Process-Oriented Assessment Framework

Alfréd Zimmermann, Rainer Alt, Rainer Schmidt
article en

Abstract

Are organizations ready for agentic artificial intelligence (AI)? Based on the limited success of AI projects in practice, this paper proposes an approach that recognizes the new potential of agentic AI for automating business processes and posits that business benefits are created at the level of business processes. It presents a framework for evaluating organizational readiness for agentic AI systems that emphasizes their potential of agentic AI systems for business process management. The framework provides a dual assessment: first, it determines the potential readiness across five perspectives (activities, decisions, data operations, control flow, and resource management). Second, it measures process debt, which refers to the gaps between documented and actual practices. Validated through a case study involving 40+ stakeholders and nine processes at a German university, the framework reveals distinct readiness patterns and actionable transformation insights. This enables evidence-based decision-making regarding AI investments and systematic capability building for agentic AI implementation in existing organizational settings.

ScholarSpace (University of Hawaii at Manoa)
Openalex Percentile: Top 25%
Business Process Modeling and Analysis
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Agentic AI Readiness: A Process-Oriented Assessment Framework — Alfréd Zimmermann, Rainer Alt, et al. · ScholarSpace (University of Hawaii at Manoa) (2025) | TGRS Research Map | TGRS