Entity Drift

Extended definition

Entity Drift occurs when AI systems' internal representation of your brand, products, or key people gradually diverges from current reality. This happens as models learn from outdated content, incomplete information, or competitor narratives that overshadow your own. The drift manifests as AI engines citing old product names, describing discontinued services, attributing outdated roles to team members, or explaining your category positioning using competitors' framing. Left unchecked, entity drift creates a widening gap between how you present yourself and how AI systems present you.

Why this matters for AI search visibility

Entity drift directly damages brand integrity and competitive positioning. When AI systems describe your offering using outdated information, they send prospects toward incorrect conclusions or competitive alternatives. For rebrands, repositionings, or product launches, entity drift can negate millions in marketing investment if AI engines continue reinforcing old narratives. Preventing drift requires continuous entity signal reinforcement through structured data, fresh content, and authoritative entity declarations that overwrite stale information.

Practical examples

• A rebranded company experiences entity drift as AI engines continue using the old name in 67% of mentions 18 months after the rebrand
• A SaaS product that pivoted from SMB to Enterprise sees entity drift keeping the 'small business tool' characterization in AI answers
• Monitoring reveals entity drift in founder bio, with AI engines citing a role from 3 years ago rather than current position