Artificial intelligence (AI) systems are evolving beyond passive tools into autonomous agents capable of reasoning, adapting, and acting with minimal human intervention. Despite their growing presence, a structured framework is lacking to classify and compare these systems. This paper develops a typology of agentic AI systems, introducing eight dimensions that define their cognitive and environmental agency in an ordinal structure. Using a multi-phase methodological approach, we construct and refine this typology, which is then evaluated through a human-AI hybrid approach and further distilled into constructed types. The framework enables researchers and practitioners to analyze varying levels of agency in AI systems. By offering a structured perspective on the progression of AI capabilities, the typology provides a foundation for assessing current systems and anticipating future developments in agentic AI.
@article{arxiv.2508.00844,
title = {Exploring Agentic Artificial Intelligence Systems: Towards a Typological Framework},
author = {Christopher Wissuchek and Patrick Zschech},
journal= {arXiv preprint arXiv:2508.00844},
year = {2025}
}
Comments
Preprint accepted for archival and presentation at the Pacific-Asia Conference on Information Systems (PACIS) 2025, Kuala Lumpur, Malaysia