What it means
AI change management is the operating work required to introduce, explain, govern, and adjust AI-enabled workflows after purchase. It includes stakeholder alignment, training, policy updates, communication, reviewer guidance, escalation paths, feedback loops, adoption metrics, and controls for changing or disabling AI features over time.
Why buyers should care
AI tools often change how recruiters, HR teams, managers, candidates, or employees experience a workflow. Even when the feature is technically sound, adoption can fail if users do not trust outputs, understand review expectations, or know how to handle exceptions. Change management is especially important when AI touches hiring, employee communication, analytics, or recommendations.
Evaluation checks
Buyers should ask how the vendor supports rollout planning, training, admin controls, permissions, communication templates, and post-launch monitoring. Review how teams collect user feedback, report AI errors, update workflows, and pause features when needed. Strong change management should make adoption measurable and reversible, rather than assuming users will accept AI features because they are available.
This glossary entry is buyer-oriented guidance, not legal, compliance, or financial advice.