Designing Unified Identity Frameworks for Humans and AI Agents

Abstract

Contemporary identity management infrastructures emerged from foundational assumptions regarding human-exclusive system participation. Modern computational environments invalidate these premises. Organizational ecosystems now encompass distributed architectures wherein human operators, automated services, integration middleware, and machine learning systems require authentication, authorization, and accountability mechanisms. Legacy identity frameworks, architected for static user registries, demonstrate inadequacy when representing novel actor classifications and their interdependencies. This article investigates architectural substrates, deployment methodologies, and governance structures requisite for constructing identity systems accommodating both human participants and autonomous computational agents, while examining real-world failure modes and practical implementation challenges.