BW Marketing World: How AI Assistants Represent Brands

BW Marketing World reported on 9 December 2025 on Pulp Strategy’s GEO Benchmark Index 2025, a study powered by NeuroRank, of how ChatGPT, Gemini, Claude, and Perplexity recall, rank, and represent brands. The report covers the study’s four sources of evidence, the structural causes of weak AI representation, and the business risks for regulated sectors.

The study drew on four streams of evidence

BW Online Bureau sets out the method in detail: 70 enterprise audits, more than 350 brands, 408,000 prompt simulations, and insights from more than 60 CMOs and business leaders. Anonymized GEO audits examined content inventory, hallucination events, top prompts, competitor positioning, and recommendations. Real-world prompts were run and analyzed for brand presence, sentiment, citation quality, and hallucinations. Interviews with CMOs and business leaders, all anonymized, covered how ready their organizations were for GEO, how content is governed, and where the risks sit.

Selected findings were then checked against independent research and coded into a quantitative codebook to detect patterns at scale. The sectors covered were BFSI, retail, technology, energy, and media.

Four headline findings

BW reported the study’s core findings:

• 68 percent of brands are invisible in AI-generated category lists;

• 52 percent face factual inaccuracies or hallucinated capabilities in AI responses;

• negative sentiment bias affects 90 percent of consumer brands;

• and 88 percent show inconsistent naming and recognition across AI models.

Weak representation traces to format and trust signals

The report places the cause in how brand information is published. Market performance plays little part. Content that machines cannot read, outdated formats such as PDFs and unstructured pages, and weak trust signals in AI knowledge graphs leave the models with an incomplete picture of a brand.

 Regulated sectors carry the widest exposure

BW lists the risks that came out of the audits and interviews:

• brands left out of comparison queries;

• outdated or fabricated capabilities appearing in AI answers;

• ESG credentials misread because of poor data formatting;

• and competitors appearing ahead of category leaders.

In regulated industries the exposure reaches investor perception, compliance, and procurement visibility. The study closed with a 30 to 90 day roadmap on factual accuracy, fewer hallucinations, AI-trusted content surfaces, recognition across models, and machine-legible brand authority.

Current NeuroRank research

This coverage describes a study from 2025. NeuroRank now publishes its research as the AI Visibility Index 2026.

Sharma’s statement in the BW report opened on the stakes for procurement, investors, and consumers.BW Marketing World reported on 9 December 2025 on Pulp Strategy’s GEO Benchmark Index 2025, a study powered by NeuroRank, of how ChatGPT, Gemini, Claude, and Perplexity recall, rank, and represent brands. The report covers the study’s four sources of evidence, the structural causes of weak AI representation, and the business risks for regulated sectors.

The study drew on four streams of evidence

BW Online Bureau sets out the method in detail: 70 enterprise audits, more than 350 brands, 408,000 prompt simulations, and insights from more than 60 CMOs and business leaders. Anonymized GEO audits examined content inventory, hallucination events, top prompts, competitor positioning, and recommendations. Real-world prompts were run and analyzed for brand presence, sentiment, citation quality, and hallucinations. Interviews with CMOs and business leaders, all anonymized, covered how ready their organizations were for GEO, how content is governed, and where the risks sit.

Selected findings were then checked against independent research and coded into a quantitative codebook to detect patterns at scale. The sectors covered were BFSI, retail, technology, energy, and media.

Four headline findings

BW reported the study’s core findings:

• 68 percent of brands are invisible in AI-generated category lists;

• 52 percent face factual inaccuracies or hallucinated capabilities in AI responses;

• negative sentiment bias affects 90 percent of consumer brands;

• and 88 percent show inconsistent naming and recognition across AI models.

Weak representation traces to format and trust signals

The report places the cause in how brand information is published. Market performance plays little part. Content that machines cannot read, outdated formats such as PDFs and unstructured pages, and weak trust signals in AI knowledge graphs leave the models with an incomplete picture of a brand.

 Regulated sectors carry the widest exposure

BW lists the risks that came out of the audits and interviews:

• brands left out of comparison queries;

• outdated or fabricated capabilities appearing in AI answers;

• ESG credentials misread because of poor data formatting;

• and competitors appearing ahead of category leaders.

In regulated industries the exposure reaches investor perception, compliance, and procurement visibility. The study closed with a 30 to 90 day roadmap on factual accuracy, fewer hallucinations, AI-trusted content surfaces, recognition across models, and machine-legible brand authority.

Current NeuroRank research

This coverage describes a study from 2025. NeuroRank now publishes its research as the AI Visibility Index 2026.

Ambika Sharma’s statement in the BW report opened on the stakes for procurement, investors, and consumers.