The nature of agency: designing agentic systems using a biomimetic lens

Purpose This paper aims to explore how biomimetic principles can inform governance models for agentic artificial intelligence (AI) systems, autonomous, adaptive entities that challenge traditional oversight frameworks. It argues that nature-inspired governance offers a dynamic alternative to static, compliance-based models. Design/methodology/approach This study adopts a conceptual viewpoint approach. It synthesizes literature on AI governance, systems theory and biomimicry, applying thematic analysis to existing frameworks and mapping identified gaps to five natural principles: symmetry, fractals, cymatic feedback, self-organization and phase transitions. Findings Current governance frameworks lack mechanisms for managing emergent behaviors and distributed agency in agentic AI. The proposed biomimetic lens offers a conceptual scaffold for adaptative, decentralized governance aligned with ethical norms. Research limitations/implications No empirical validation is provided; future research should use simulation or design science to test biomimetic governance in real-world contexts. Practical implications This paper offers actionable guidance for policymakers and system designers to adaptive, resilient governance mechanisms into agentic AI architectures. Originality/value Introduces “Biomimic AI” as a novel paradigm for governing agentic systems, extending systems theory and responsible AI discourse through nature-inspired design logic.