# Exploring Agentic Artificial Intelligence Systems: Towards a Typological Framework

arXiv: https://arxiv.org/abs/2508.00844 · HTML: https://mlsanity.com/paper/2508.00844/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use.
- Builds on 12 of its 54 references that are in the map.
- First posted on arXiv 7 Jul 2025.

## Placed in

- LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/)

## Builds on (most cited first, 12 of 12)

- [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023)
- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://mlsanity.com/paper/2309.07864/) (2023)
- [Understanding the planning of LLM agents: A survey](https://mlsanity.com/paper/2402.02716/) (2024)
- [Agent AI: Surveying the Horizons of Multimodal Interaction](https://mlsanity.com/paper/2401.03568/) (2024)
- [Exploration in Deep Reinforcement Learning: A Survey](https://mlsanity.com/paper/2205.00824/) (2022)
- [Harms from Increasingly Agentic Algorithmic Systems](https://mlsanity.com/paper/2302.10329/) (2023)
- [Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects](https://mlsanity.com/paper/2401.03428/) (2024)
- [Generative AI](https://mlsanity.com/paper/2309.07930/) (2023)
- [Guidelines for including grey literature and conducting multivocal literature reviews in software engineering](https://mlsanity.com/paper/1707.02553/) (2017)
- [An In-depth Survey of Large Language Model-based Artificial Intelligence Agents](https://mlsanity.com/paper/2309.14365/) (2023)
- [Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends](https://mlsanity.com/paper/2409.14457/) (2024)
- [Balancing Autonomy and Alignment: A Multi-Dimensional Taxonomy for Autonomous LLM-powered Multi-Agent Architectures](https://mlsanity.com/paper/2310.03659/) (2023)

## Built on by (most cited first, 3 of 3)

- [Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions](https://mlsanity.com/paper/2510.25445/) (2025)
- [Generative AI and Digital Ecosystem Resilience: A Proactive Lifecycle-Based Survey](https://mlsanity.com/paper/2606.00136/) (2026)
- [Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents](https://mlsanity.com/paper/2610.17126/) (2026)

## Abstract (arXiv)

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.