Mining and resources
AI findability benchmark: mining and resources
A multi-company study of how mining and resource issuers perform when AI systems and search engines are asked to find, understand and compare them.
Scope
What was measured
- Mining and resource issuers, weighted toward British Columbia listings
- Scored with the Kumu Brand & Signal Benchmark
- Public evidence only — websites, structured data, third-party sources and live AI responses
Questions
What the study asks
- Whether AI systems can retrieve and correctly categorize each issuer
- Whether project, asset and jurisdiction information is machine-readable
- Whether investor-facing claims meet a verifiable Evidence Standard
- Whether the technical foundation supports retrieval at all
Why it matters
What we found in mining and resources
Resource issuers compete for attention from investors and analysts who increasingly begin with an AI query rather than a search results page. If a model cannot retrieve your project data or cannot verify your claims, it defaults to whatever third-party summary is easiest to find — often outdated.
The pattern across the study is consistent: substance exists in filings and technical reports, but is not transmitted in a form machines can read. That is a Signal Gap, and it is fixable without changing the underlying business.
Next step
See where you sit
The same instrument can be run on your brand and your competitive set. Phase 1 is $500, with first findings in 3–5 days.
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