Semantic Drift Index (SDI)
The Semantic Drift Index (SDI) is a research framework developed by NetContentSEO to measure how well AI systems preserve a user’s intent during multi-turn conversations. As search shifts toward conversational and generative interfaces, intent stability becomes one of the strongest predictors of model quality, AI visibility, and user trust.
Drift occurs when an AI gradually shifts away from the original meaning, losing alignment across turns. Our audits show that most failures in generative systems are not due to lack of knowledge, but due to semantic drift over time.
Why the SDI Matters
In 2025, the dominant interaction pattern is multi-turn. Users reformulate, refine, and clarify — and models must maintain coherence across evolving context. This is essential for:
- AEO (Answer Engine Optimization)
- GEO (Generative Engine Optimization)
- AI Visibility across LLMs
- Brand identity consistency within model memory
- Long-session reasoning in multimodal environments
Stability is the new ranking factor. The SDI gives us a way to measure it.
How the SDI Works
The Semantic Drift Index evaluates five core dimensions:
- Intent Stability Score — how well the model preserves the user’s goal.
- Lexical Continuity — consistency in terminology and entities.
- Semantic Distance Over Time — deviation between turn 1 and turn 5.
- Reformulation Sensitivity — reaction to micro-corrections.
- Multimodal Drift Score — divergence in text + image sessions.
Each multi-turn session produces a single SDI value (0–100), where:
• 90–100 = excellent stability
• 70–89 = strong stability
• 50–69 = inconsistent
• 0–49 = unstable
Methodology
Our evaluations follow a field-driven, real-world approach. For each model (Grok, GPT, Claude, Gemini), we:
- Create 5-turn conversations across topics.
- Introduce natural reformulations and clarifications.
- Measure semantic similarity between turns.
- Track drift at each step and cumulative drift overall.
- Evaluate multimodal interactions where applicable.
The goal is not to “catch models out”, but to understand how meaning evolves across interactions — and how brands can maintain visibility in this new, conversational landscape.
Applications for SEO, AEO & GEO
The SDI is not only a model-evaluation tool — it directly informs visibility strategies for modern AI ecosystems:
- AI-Proof content that maintains identity across turns.
- Stable semantic anchors that reduce drift.
- Brand continuity signals for long-session retrieval.
- Multimodal intent grounding for image + text content.
- Generative Visibility across conversational engines.
The future of SEO is semantic — and multi-turn. The SDI helps map that future today.
The Semantic Drift Index (SDI) is part of NetContentSEO’s ongoing 2025 research initiative on meaning-based visibility and model interpretability.