Agentic AI Security in Industry 5.0: Emerging Threats, Forensic Readiness, and Trustworthy Human–Agent Collaboration

Abstract

Industry 5.0 places autonomous agents inside its human–agent collaborative loop, resting its human-centricity pillar on an assumption of trustworthy collaboration that has not been examined critically. Agentic artificial intelligence has moved from research demonstration to industrial deployment within months, introducing a threat class this setting has not yet addressed. This article bridges three literatures developed in isolation, Industry 5.0 cybersecurity, agentic AI security, and Industry 5.0’s own foundational scholarship, proposing a six-category threat taxonomy and a paired forensic readiness framework, formalised as a five-level maturity model and grounded in real 2024–2026 incidents rather than hypothetical scenarios. Both contributions are evaluated through two complementary methods. An exploratory elicitation exercise, modelled on Delphi methodology and using six independent large language models as blind panellists across two rounds, converges on a specific structural critique that is incorporated into the taxonomy’s final design. A retrospective coding exercise then applies that taxonomy to fourteen publicly documented incidents, finding that half require multi-category classification and that two categories remain unexercised in the current public record, evidence that physically embodied industrial deployment has outpaced the documented incident base rather than a gap in the taxonomy itself. This urgency is reinforced by emerging EU and UK regulation imposing 24- and 72-h incident reporting obligations that, on current evidence, most industrial organisations are not positioned to meet. The article closes with a research agenda addressing liability, evidentiary standards, and the readiness-sustainability trade-off.