Source Context & Analysis
The first quantified vocabulary for what goes wrong inside the enterprise when agents proliferate without governance.
AAGMM is corpus-relevant for two reasons. First, the agent-sprawl taxonomy (functional duplication, shadow agents, orphaned agents, permission creep, unmonitored delegation chains) is original vocabulary that maps cleanly onto observed enterprise pathologies — every operator dealing with hundreds of internal agents recognises these patterns. Second, the maturity model itself is the first to claim quantifiable validation (94.3% lower sprawl, 96.4% fewer incidents at L4–5) across 750 simulation runs — a level of evidence rare in Category D. Coded definition_type 'prescriptive' because the paper specifies what enterprises must do, not what they currently do. Coded actor_model 'hybrid' because the maturity model spans pre-deployment governance (human-decided) and runtime behaviour (autonomous-or-supervised). The work is single-author and unrefereed; corpus placement reflects the originality of the taxonomy, not endorsement of the empirical claims.
Tags
Category D: Analytical and Regulatory
They analyze what Categories A through C will do to markets, workers, and systemic stability.