---
id: "claim-inclusion-is-bottleneck"
type: "claim"
source_timestamps: ["§ AI Recommends What It Can Interpret", "§ Inclusion—Not Sentiment—Is the Real Competitive Bottleneck"]
tags: ["research-finding", "strategy"]
related: ["concept-ai-recommendation-chain", "contrarian-sentiment-optimization", "concept-ai-recall-share"]
confidence: "high"
testable: true
sources: ["geo"]
sourceVaultSlug: "hbr-seg-geo"
originDay: 3
articleStem: "hbr-new-25-get-ai-to-surface-your-brand"
sourceUrl: "https://hbr.org/2026/06/how-to-get-ai-to-surface-your-brand"
sourceTitle: "How to Get AI to Surface Your Brand"
---
# Inclusion, not sentiment, is the real competitive bottleneck in AI

The study found that **78.7% of brand mentions in AI outputs carry positive sentiment**, a pattern consistent across ChatGPT, Claude, and Gemini.

Because AI systems first determine which brands qualify as *factual solutions* to a user's problem and *only then* express a view, the resulting tone is almost always favorable once a brand is selected. Therefore, the authors claim marketers should stop asking "how do we make AI say nice things about us?" and instead focus entirely on "how do we make our brand **includable** in AI responses?" Competition is decided upstream during the retrieval phase (see [[concept-ai-recommendation-chain|AI Recommendation Chain]]), not during sentiment generation. This is the direct basis of the contrarian argument that [[contrarian-sentiment-optimization|sentiment optimization is a distraction]], and it reframes success as [[concept-ai-recall-share|AI recall share]].

**Confidence:** high · **Testable:** yes.

> Enrichment note: The exact 78.7% is study-specific, but the argument is strongly supported. LLMs exhibit a documented positivity/politeness bias, and IR + generation pipelines structurally decide *which* entities to mention before *how* to talk about them — so retrieval is the primary gate. Counter-nuance: in high-stakes regulated categories (healthcare, finance, B2B), rare negative or hallucinated mentions can be disproportionately important, so sentiment/accuracy monitoring still matters there.


## Related across articles
- [[contrarian-sentiment-optimization]]
- [[claim-ai-visibility-fragmented]]
- [[concept-ai-recall-share]]