# LLM positioning lag misleads users about updated brands

Digest AI · Marketing & Small Business · published 2026-09-29T14:50:00Z

Canonical: https://digestai.news/story/llm-positioning-lag-misleads-users-about-updated-brands

## Summary

The **LLM positioning lag** occurs when a company’s branding or service offerings change, but generative AI models still reflect outdated information. This gap can mislead potential customers, as **58% of consumers now use LLMs for product and service recommendations**, up from 25% in 2023, per Capgemini data. Models default to training data unless prompted to search the web, leaving users with incorrect impressions—such as assuming a consultant still specializes in an old niche or that a meal delivery service requires subscriptions when it no longer does.

The issue stems from three factors: outdated training data, conflicting online sources, and the dominance of long-standing narratives. Even well-funded efforts—like **Contentsquare’s acquisition of Hotjar** (announced via press releases, blog posts, and support docs) or **Duolingo’s expansion into math and chess** (highlighted in app updates and press releases)—fail to update AI responses quickly. For example, **ChatGPT still lists Hotjar as an independent tool** despite its merger in 2025, and **Duolingo’s AI descriptions remain limited to language learning**, ignoring its newer offerings. Small businesses and consultants face similar challenges, as **Peep Laja’s shift from conversion rate optimization (CRO) to business strategy** (documented on LinkedIn and his newsletter) still surfaces his CRO expertise in AI-generated advice.

Semrush’s **Perception report** helps brands audit AI perceptions by analyzing responses to branded and non-branded queries. To fix the lag, companies must coordinate PR, content updates, and backlink audits—publishing clear press releases, revising outdated web content, and ensuring consistent messaging across directories like Google Business Profile and LinkedIn. Structuring pages for LLM extraction (e.g., using clear headings and dated shifts) and monitoring AI responses regularly can mitigate the problem.

## Key points

- 58% of consumers now use LLMs for product/service recommendations, up from 25% in 2023, per Capgemini
- Outdated training data, conflicting online sources, and long-standing narratives cause AI to misrepresent updated brands
- Semrush’s tools help audit AI perceptions and track fixes via PR, content updates, and backlink audits

## Why it matters

Brands risk losing sales and credibility if LLMs misrepresent their updated offerings. With 58% of users relying on AI for decisions, even minor positioning gaps can alienate prospects or miss opportunities.

## Sources

1. [The LLM positioning lag: What it is and how to avoid it](https://semrush.com/blog/llm-positioning-lag) (Semrush Blog, 2026-09-29)

## Cite

Digest AI, "LLM positioning lag misleads users about updated brands", 29 September 2026, https://digestai.news/story/llm-positioning-lag-misleads-users-about-updated-brands

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