AI Disaster Recovery Planning Is Years Behind AI Adoption
InformationWeek, Tuesday, June 23rd, 2026
Enterprises' disaster recovery plans lag years behind their AI deployments, leaving models and agents exposed.
Experts warn that most organizations' disaster recovery plans are years behind their AI adoption, per Quest Software CIO Greg Sarich.
Traditional DR backed up applications and databases, but enterprises must now protect AI models, prompts, and agents and verify their integrity after restoration.
Risks include compromised training data, poisoned models, manipulated prompts, and agents operating across interconnected systems.
Restored AI may appear functional yet return wrong, incomplete, or manipulated answers, as Deloitte's Mehdi Houdaigui notes.
Recommended steps include cataloging AI assets, prioritizing by criticality, mapping dependencies, defining recovery objectives, and regular testing, as 42% of surveyed pros report AI incidents.