Meet Your New Client: Writing Reports for AI -- Benchmarking Information Loss in Market Research Deliverables

As organizations adopt retrieval-augmented generation (RAG) for their knowledge management systems (KMS), traditional market research deliverables face new functional demands. While PDF reports and slides have long served human readers, they are now also "read" by AI systems to answer user questions. To future-proof reports being delivered today, this study evaluates information loss during their ingestion into RAG systems. It compares how well PDF and PowerPoint (PPTX) documents converted to Markdown can be used by an LLM to answer factual questions in an end-to-end benchmark. Findings show that while text is reliably extracted, significant information is lost from complex objects like charts and diagrams. This suggests a need for specialized, AI-native deliverables to ensure research insights are not lost in translation.

Publication Details

Journal
ArXiv.org
Published
2025-08-17
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Meet Your New Client: Writing Reports for AI -- Benchmarking Information Loss in Market Research Deliverables

ArXiv.org
Geochemistry and Geologic Mapping
article

Meet Your New Client: Writing Reports for AI -- Benchmarking Information Loss in Market Research Deliverables

article en

Abstract

As organizations adopt retrieval-augmented generation (RAG) for their knowledge management systems (KMS), traditional market research deliverables face new functional demands. While PDF reports and slides have long served human readers, they are now also "read" by AI systems to answer user questions. To future-proof reports being delivered today, this study evaluates information loss during their ingestion into RAG systems. It compares how well PDF and PowerPoint (PPTX) documents converted to Markdown can be used by an LLM to answer factual questions in an end-to-end benchmark. Findings show that while text is reliably extracted, significant information is lost from complex objects like charts and diagrams. This suggests a need for specialized, AI-native deliverables to ensure research insights are not lost in translation.

ArXiv.org
Openalex Percentile: Top 65%
Geochemistry and Geologic Mapping
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Meet Your New Client: Writing Reports for AI -- Benchmarking Information Loss in Market Research Deliverables · ArXiv.org (2025) | TGRS Research Map | TGRS