Transferability is the ability to move AI knowledge, prompts, decision rules, and control logic from one model or platform to another without losing function. In cyber security, this matters because the useful part of an AI system is often not just the data, but the instructions and guardrails that shape its behavior.
If transferability is weak, a model migration can silently change policy enforcement, thresholds, or response style, creating gaps that attackers can exploit or causing defenses to fail. Security teams improve transferability by versioning prompts and policies, separating system instructions from user input, testing behavior after platform changes, and keeping rollback copies. Good transferability helps preserve control, auditability, and consistency when vendors, models, or deployment stacks change.