Polished AI Corporate Voice
232
Samples Analyzed
36,287
Total Words
4
Languages
poor
Corpus Quality
Writing style compared to average AI output
Intrinsic stylometry metrics
Vocabulary Richness
TTR 0.21
Writing Rhythm
Moderate
Sentence Range
words
Signature Punctuation
Writing follows rigid templates with predictable organizational patterns. Multiple options are consistently provided ("Option 1, Option 2, Option 3") with labeled formality levels, creating a choose-your-own-adventure format rather than authentic voice.
“From French email: 'Voici trois options, allant du plus formel au plus direct' - this meta-commentary about structure dominates actual content”
Heavy reliance on bracketed placeholders [X], [Name], [Project Name] throughout all samples. Content reads as templates to be filled in rather than complete communications, creating emotional distance.
“Spanish report uses 26+ bracketed placeholders: '[X]%', '[Enterprise / PyME]', '[mencionar causa principal]' - reads like a form, not writing”
Frequent stepping outside the content to explain the content itself. Writing describes what it's about to do rather than simply doing it, breaking immersion with instructional asides.
“Japanese post includes structural guidance: '**📖 La petite histoire:**' and analysis labels like '**ポイント：**' that explain rather than execute”
Every potentially negative statement is wrapped in multiple layers of softening language. Apologies, acknowledgments, and politeness markers accumulate to the point of diluting core messages.
“Formal emails consistently stack phrases: 'sincèrement navrés', 'conscients des désagréments', 'totalement transparents' - three apologies before stating the actual delay”
Casual communications rely on emojis (🍔, 🟡, 🤖, ❤️) to convey tone rather than word choice or rhythm. These function as tone indicators rather than organic expression.
“Casual emails use '🍔', '🥗', '📝' to signal informality instead of developing conversational voice through language itself”
Clear, accessible language
Measured, professional tone
Conversational, approachable style
Gray line = average AI output. Purple bar = their writing. The bigger the difference, the more distinctive the voice.
Follow identical apologetic arc: acknowledge problem → explain cause (supply chain) → state delay → apologize profusely → assert firmness on new timeline. Structure is identical regardless of language or cultural context.
Rely heavily on emoji and explicit formality labels ('very casual', 'standard') rather than naturally varied register. The 'casualness' is announced rather than embodied.
Professional format is strong, but content is 90% blank template structure with section headers and bullet point frameworks. Minimal actual analysis or completed thought.
Follow LinkedIn thought-leadership formula precisely: personal anecdote → broader insight → question to audience. The vulnerability feels performed with phrases like 'avouons-le' (let's admit it) that signal rather than demonstrate authenticity.
Writing patterns are identical across languages - same structure, same meta-commentary, same placeholder density. Language changes but voice remains uniformly AI-corporate, suggesting translation or parallel generation rather than culturally adapted writing.
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