Marketing

When AI Makes Marketing 'Soulless': Balancing Automation with Authenticity

10 December 2025
10 min
Ben Gale
When AI Makes Marketing 'Soulless': Balancing Automation with Authenticity

The Homogenisation Problem

Something strange is happening to marketing content. As more businesses adopt AI for content creation, a sameness is emerging. The same sentence structures. The same overused phrases. The same predictable approaches.

AI-generated marketing is increasingly recognisable—and not in a good way. It's grammatically correct, comprehensive, and completely forgettable.

Rising
AI-generated marketing content
Declining
Distinctive brand voices
Risk
Blending into the noise

Why AI Content Sounds the Same

How Language Models Work

AI generates text by predicting what words should come next based on patterns in training data. This means AI naturally gravitates towards:

  • Common phrases and structures
  • Middle-of-the-road positions
  • Safe, expected language
  • Patterns that appear frequently

This is great for correctness but terrible for distinctiveness.

The "AI Writing" Problem

You've probably noticed AI-typical patterns:

  • "In today's fast-paced world..."
  • "Let's dive in..."
  • Excessive use of "importantly" and "certainly"
  • Overly enthusiastic transitions
  • Lists where paragraphs would be better

These patterns emerge because AI optimises for plausibility, not originality.

Volume Over Value

AI makes producing more content easy. This creates pressure to:

  • Publish more frequently
  • Cover more topics
  • Fill more channels

Quantity increases while distinctiveness decreases. The unique brand voice gets lost in the flood.

Warning

If your content sounds like everyone else's AI-generated content, you've paid for software to make you invisible.

What Makes Brand Voice Distinctive

Elements of Authentic Voice

Perspective:

  • Point of view on industry issues
  • Willingness to have opinions
  • Specific positions, not generic statements

Personality:

  • Consistent tone (serious, playful, direct, warm)
  • Recognisable rhythm and cadence
  • Signature phrases or approaches

Stories:

  • Real experiences and examples
  • Specific, not generic, illustrations
  • Human elements that connect

Imperfection:

  • Quirks that make content human
  • Occasional departure from convention
  • Personality that can't be templated

Why It Matters

Distinctive voice:

  • Gets remembered
  • Builds connection
  • Attracts aligned customers
  • Repels wrong-fit customers (a feature, not a bug)
  • Creates competitive moat
Marketing team collaborating on creative work
Brand voice emerges from human creativity that AI can assist but not replace

Framework for AI-Assisted Authenticity

Define Before Automating

Before using AI for content:

Document Your Voice:

  1. What words do we use? What do we avoid?
  2. What's our tone? (Formal? Conversational? Direct?)
  3. What perspectives do we hold?
  4. What makes us sound like us?

Create Voice Examples:

  • Best examples of your content
  • Explanation of why they work
  • Patterns and approaches to maintain
  • Things that violate your voice

AI as Assistant, Not Author

Good Use:

  • First draft generation
  • Research and synthesis
  • Structure suggestions
  • Alternative phrasing
  • Editing and polishing

Bad Use:

  • Publish without human review
  • Replace human creativity
  • Generate "thought leadership"
  • Create content on topics you don't actually know

The Human Finishing Layer

Every AI-assisted content should have:

Voice Check: Does this sound like us? Would someone who knows our brand recognise it?

Opinion Injection: Where's our actual point of view? Have we said something meaningful?

Story Addition: Can we add a real example, experience, or anecdote?

De-AI-ing: Remove AI-typical phrases. Fix the rhythm. Add personality.

Pro Tip

The value of AI is in the time saved on structure and research. Use that saved time to add the human elements that make content distinctive.

Practical Approaches

Prompt Engineering for Voice

Train AI to match your style:

Provide Examples: "Write in the style of these examples: [your best content]"

Specify Personality: "Use a direct, conversational tone. Avoid corporate jargon. Include specific examples."

Constrain Output: "Don't use phrases like 'dive in' or 'in today's world'. Avoid excessive enthusiasm."

The 70/30 Split

AI generates 70%, human adds 30%:

  • AI provides structure, research, first draft
  • Human adds voice, opinion, stories, polish

This preserves efficiency while maintaining authenticity.

Review Checkpoints

Before publishing, verify:

  • Does this sound like our brand?
  • Have we expressed an actual opinion?
  • Is there something memorable here?
  • Would this stand out from competitors?
  • Does it contain original examples or stories?

When AI Works and When It Doesn't

AI Works Well For

Content TypeWhy AI Helps
Data summariesAccuracy and speed
Technical explanationsComprehensive coverage
Product descriptionsConsistent formatting
SEO-focused contentKeyword integration
First draftsFaster iteration

AI Struggles With

Content TypeWhy Human Essential
Thought leadershipRequires genuine thought
Brand storytellingNeeds authentic experiences
Controversial opinionsAI avoids strong positions
Emotional connectionRequires human understanding
Humour and witAI humour often falls flat

Hybrid Approaches

Case Studies: AI structures and drafts, human adds actual client stories and insights.

Blog Posts: AI researches and outlines, human adds perspective and voice.

Social Media: AI generates options, human selects and personalises.

Email Campaigns: AI creates variants, human ensures brand consistency.

Protecting Voice Over Time

Avoid Voice Drift

As AI use increases, voice can gradually drift towards AI-generic:

  • Regular voice audits
  • Comparison to historical content
  • Fresh examples of good voice
  • Feedback loops from audience

Build Voice Guardrails

Style Guide Updates: Document AI-specific guidance:

  • What AI can and can't do
  • Required human elements
  • Review requirements
  • Examples of AI-typical issues to fix

Training: Ensure everyone using AI understands:

  • Why voice matters
  • How to maintain it with AI
  • What to look for in review
  • When to reject AI output
Info

Your brand voice is a competitive asset. AI should strengthen it, not dilute it. Treat voice protection as seriously as any other brand asset.

The Long-Term View

As AI content becomes ubiquitous, authentic voice becomes more valuable:

  • Generic content drowns in noise
  • Distinctive content stands out more
  • Human elements become differentiators
  • Audiences crave genuine connection

The businesses that win will use AI for efficiency while doubling down on authenticity for differentiation.


Struggling to maintain brand voice while using AI? We help marketing teams implement AI tools and processes that enhance rather than erode brand distinctiveness.

Book a consultation to discuss your content and automation challenges.

Ben Gale

Ben Gale

25 years IT and leadership experience. Based in Woodley, Reading. Helping Thames Valley businesses automate workflows and reduce admin overhead.

Learn more about Ben →

Frequently Asked Questions

Why does AI-generated marketing content all sound the same?

AI generates text by predicting likely next words based on training patterns, naturally gravitating towards common phrases, middle-of-the-road positions, and safe expected language. This optimises for correctness but not distinctiveness.

How can I maintain brand voice while using AI for content creation?

Document your voice before automating, use AI as an assistant for first drafts and research rather than the author, and apply a human finishing layer that checks for voice, injects opinions, adds real stories, and removes AI-typical phrases.

What is the recommended split between AI and human work in content creation?

The 70/30 split works well where AI generates 70% providing structure, research, and first drafts, while humans add the remaining 30% including voice, opinion, stories, and polish. This preserves efficiency while maintaining authenticity.

What types of content should not be fully AI-generated?

AI struggles with thought leadership requiring genuine perspective, brand storytelling needing authentic experiences, controversial opinions since AI avoids strong positions, emotional connection requiring human understanding, and humour which often falls flat when AI-generated.

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