Exploring Agentic Artificial Intelligence Systems: Towards a Typological Framework

TL;DR

This paper introduces a structured typology of agentic AI systems, defining eight dimensions of agency to classify and compare autonomous AI, aiding research and development in understanding AI progression.

Contribution

It develops a novel eight-dimensional typology of agentic AI systems, providing a structured framework for classification and analysis of AI agency levels.

Findings

The typology effectively categorizes AI systems based on agency dimensions.

The framework facilitates comparison and assessment of AI capabilities.

It supports future research in developing and evaluating autonomous AI systems.

Abstract

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.