On the Creativity of AI Agents

2026-04-14

AI Summary

This study addresses the question of whether AI agents possess genuine creativity, tackling the ambiguity in current definitions and evaluation criteria. It presents the first systematic integration of functionalist and ontological perspectives—focusing respectively on output characteristics and on internal processes alongside socio-individual dimensions. Through theoretical analysis and interdisciplinary reflection, complemented by qualitative assessment of behaviors and outputs from large language model agents, the research finds that AI exhibits rudimentary functionalist creativity but lacks essential elements of ontological creativity. Building on this distinction, the paper clarifies the boundaries of AI’s creative capacities across both dimensions and proposes a balanced pathway for the development of artificial creativity that accounts for both its potential benefits and associated risks.

Technology Category

• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Philosophy and Ethics of AI: Artificial General Intelligence
• Multiagent Systems: Agent/AI Theories and Architectures

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Large language models (LLMs), particularly when integrated into agentic systems, have demonstrated human- and even superhuman-level performance across multiple domains. Whether these systems can truly be considered creative, however, remains a matter of debate, as conclusions heavily depend on the definitions, evaluation methods, and specific use cases employed. In this paper, we analyse creativity along two complementary macro-level perspectives. The first is a functionalist perspective, focusing on the observable characteristics of creative outputs. The second is an ontological perspective, emphasising the underlying processes, as well as the social and personal dimensions involved in creativity. We focus on LLM agents and we argue that they exhibit functionalist creativity, albeit not at its most sophisticated levels, while they continue to lack key aspects of ontological creativity. Finally, we discuss whether it is desirable for agentic systems to attain both forms of creativity, evaluating potential benefits and risks, and proposing pathways toward artificial creativity that can enhance human society.

Problem

• creativity
• large language models
• AI agents
• functionalist creativity
• ontological creativity

Innovation

• artificial creativity
• LLM agents
• functionalist perspective
• ontological perspective
• agentic systems