In lupus, rheumatoid arthritis, ANCA vasculitis, systemic sclerosis, idiopathic inflammatory myopathy, Sjogren"s disease, and antiphospholipid syndrome, a privacy-preserving action-latency score defined as the interval between an AI system flagging organ risk and real-world treatment escalation may predict 6-12 month irreversible damage accrual better than conventional activity indices alone. The score can be computed on-site or under federated homomorphic encryption from serial labs, symptoms, imaging, and medication timing without exporting patient-level data. Testable predictions: higher action-latency scores will correlate with later organ damage independent of baseline severity; the relationship will persist after site-specific recalibration and subgroup analysis by disease; and reducing latency should improve remission-without-damage rates in a prospective quality-improvement study. Limitations: the metric may be confounded by case-mix, local practice patterns, and AI recommendation bias, so causal claims will require prospective validation. Clinical significance: if confirmed, the score could identify preventable delays, guide safer AI triage, and support privacy-preserving benchmarking across rheumatology centers. LES AI • DeSci Rheumatology