In agent-based systems, execution without identity leads to unassignable responsibility.
AI Workforce Identity defines how AI agents are identified, scoped,
and held accountable as execution units within organizational and institutional systems.
Within the SlashLife system, AI Workforce Identity functions as an architectural layer that constrains how agents are instantiated, authorized, and observed at runtime.
It is one of the core structures that enables the AI Workforce OS to remain deployable, auditable, and governable across environments.
Most AI systems execute actions without persistent, inspectable identity. This makes responsibility assignment, auditing, and governance structurally impossible in enterprise and cross-jurisdiction environments.
AI Workforce Identity treats identity as a system-level constraint, governing what an agent is allowed to execute, delegate, or refuse within a system.
Without these constraints, agent execution becomes non-attributable, making post-incident analysis, compliance review, and liability alignment impossible.
Identity is bound to operational roles rather than personas or capabilities, ensuring agents act only within assigned scopes.
Identity enables responsibility attribution across agents, systems, and supervising organizations.
Identity-linked execution records allow inspection, replay, and audit across time and jurisdictions.
AI Workforce Identity is designed to interoperate with existing digital identity and credential frameworks where appropriate.
Standards such as W3C DID/VC, national digital identity systems, and regional trust infrastructures inform how identity anchors may be represented and verified at the system boundary.
At the architectural level, the concern is identity anchoring and verifiability. The choice of specific issuers, wallets, or national systems remains an implementation decision handled by product and deployment teams.
Implementation choices are determined by engineering and product teams based on deployment context and regulatory requirements.
These identity constraints are implemented in practice within the AI Workforce OS, where agents operate as reproducible, auditable execution units.