Physical AI Safety Maturity Model (PAS-MM): A Five-Level Framework for Industry Readiness

Physical AI deployments — humanoid robots, autonomous mobile robots, surgical systems, autonomous vehicles — are scaling faster than the safety vocabulary used to describe them. Safety claims across organizations are not comparable. Adjacent fields solved this problem with maturity models: CMMI for software process, AI Safety Levels (ASL) for AI safety posture, ISO/IEC 33001 for process assessment, PCI DSS for payment-industry security. Physical AI lacks an equivalent. This paper proposes the Physical AI Safety Maturity Model (PAS-MM), a five-level classification system: Ad-hoc, Documented, Compliant, Certified, and Defense-in-depth. Levels are anchored to recognized functional-safety standards (IEC 61508 SIL, ISO 13849 PL) and to the Physical AI Safety Stack introduced in a forthcoming companion paper. PAS-MM includes a 30-question self-assessment instrument across six categories: hazard analysis, software safety, hardware safety, certification posture, operational monitoring, and incident response. A 0–90 score maps to a PAS Level via a defined rubric. Application to approximately 30 publicly-known Physical AI organizations, using public information only, shows clustering at PAS 1–2, a small population at PAS 3–4, and no organization at PAS 5. The paper concludes with adoption guidance for analysts, regulators, insurers, customers, and Physical AI organizations.