We've seeing something interesting in our marketing day jobs: as AI writing tools become more integrated into workflows, maintaining a consistent brand voice has become significantly more challenging. When multiple team members prompt AI differently, the resulting content often feels disjointed or “off-brand.”
A well-crafted style guide for AI-generated content solves this problem by standardizing how everyone in your organization interacts with AI writing tools. Without clear guidelines, team members may default to their personal communication styles or pet prompts, creating an inconsistent patchwork of content that dilutes brand identity.
Through our experience developing Good Bloggy's structured prompting system, we've found that the most effective AI style guides include specific voice examples, prohibited phrases, and sample prompts that demonstrate the desired tone. Unlike traditional style guides that focus primarily on grammar and formatting, AI guides need to emphasize the nuanced elements of voice that generative AI tends to miss without explicit direction.
Teams that invest time in creating comprehensive AI style guides get much better results from their AI-generated content, and their humans spend less time editing it. The structured prompting approach we've built into Good Bloggy addresses this challenge directly, but even users of other AI tools can benefit from the style guide framework we're sharing below.
Define Your Brand's Unique Voice
We've found that the most successful AI style guides begin with a clear definition of brand voice. Start by identifying 2-3 core personality traits that capture your brand's essence. Is your organization authoritative but approachable? Playfully irreverent? Technically precise? These fundamental attributes should guide all AI-generated content.
Example - Good: "At Good Bloggy, we're practical optimists. Our content is helpful and solution-oriented but never promises miracles. We're conversational experts who explain complex topics clearly without talking down to readers.”
In addition to describing how your brand "talks," we recommend collecting a diverse portfolio of existing content that exemplifies your ideal voice. This might include social media posts that perfectly captured your tone, customer emails that received positive feedback, or blog posts that truly embodied your brand personality. These real examples give AI systems concrete patterns to follow.
Your guide should also specify how your voice adapts across different contexts. We've noticed that brands often need subtle variations of their core voice for different channels and audiences. For instance, your support documentation might use the same brand voice as marketing materials but with increased clarity and reduced humor.
Example - Voice Adaptation Across Channels: "Our Twitter voice uses more casual language and occasional humor: 'Just shipped a feature that'll save you hours of editing time. Your weekend thanks us.’"
"Our help documentation uses the same helpful tone but with increased precision: 'To format your post, select the text and use the formatting toolbar that appears. Bold text can help emphasize key points.’”
Include specific instructions about vocabulary preferences, sentence structure tendencies, and the use of idioms or metaphors. We've seen that these detailed elements make the difference between AI-generated content that sounds authentically on-brand versus content that seems generic.
Provide Specific Writing Guidelines
Beyond defining your brand voice, AI requires explicit grammar, mechanics, and formatting instructions. We set clear rules for hyphenation, Oxford commas, sentence length limitations, and paragraph structure in our clients' guides. These precise guardrails prevent AI from defaulting to its own stylistic patterns.
When documenting preferred vocabulary and phrases, we recommend creating two columns: "Use This" and "Not That." For instance, if you're a financial company, your guide might specify "we help clients build wealth" (use this) versus "we help customers get rich" (not that). These direct comparisons give AI clear direction on tone and terminology.
| Use This | Not That |
|---|---|
| We built this feature to help you write faster | Our revolutionary feature leverages cutting-edge AI to transform your content creation workflow |
| Our team noticed that many users struggle with... | Users across the industry have faced significant challenges with... |
| This approach works well for most blog posts | This approach will dramatically increase your engagement metrics |
Including before-and-after examples dramatically improves implementation:
Before: "Good Bloggy's revolutionary AI assistant leverages cutting-edge machine learning to democratize content creation for businesses of all sizes."
After: "We designed Good Bloggy to help you write better blog posts in less time. Our AI assistant suggests edits, checks your tone, and helps maintain your brand voice across all your content.”
We've also found value in creating banned word lists for terms that undermine your brand voice. Common offenders include buzzwords, overpromising terms ("revolutionary," "game-changing"), and industry jargon that your audience might find alienating or confusing.
Example - Banned Word List:
- "Revolutionary" (implies unrealistic change)
- "Game-changing" (overused, lacks specificity)
- "Cutting-edge" (vague tech jargon)
- "Leverage" (corporate speak)
- "Ecosystem" (unless referring to actual biological systems)
- "At its core" (overused transition)
Pair these explicit guidelines with annotated examples showing why specific revisions align with your brand voice. This context helps team members understand the reasoning behind style decisions, not just memorize rules.
Offer Content Structure Guidance
Content structure needs vary significantly between formats, and we've found that detailed guidelines prevent AI from defaulting to repetitive patterns. For blog posts, we recommend specifying a formula that includes hook types (question, statistic, story), body section requirements, and conclusion styles that align with your brand's call-to-action approach. For example:
[Title: How to X: Our Approach to Y]
[Opening paragraph: Start with a specific observation or problem we've noticed]
We've noticed that many content teams struggle with X. While working with clients on their content strategy, we've seen this issue come up repeatedly, especially for teams in [industry/situation]
[Second paragraph: Briefly explain why this matters]
When X happens, it typically leads to [specific consequence]. This affects not just your workflow but also [broader impact]
[Main section: 3-4 key points with subheadings]
## What Works Better
[Practical advice with specific examples]
## Common Pitfalls We've Seen
[1-2 specific mistakes to avoid]
[Conclusion: Sum up key takeaway and small call to action]
We've found that addressing X with these approaches has helped our team create more consistent content with less revision time. If you're trying Good Bloggy for the first time, the [specific feature] can help you implement these practices more easily.
Landing pages require different structural guidance. The most successful AI style guides include wireframe-like templates showing the preferred headline-subheading hierarchy, ideal paragraph length (we suggest 2-3 sentences for web pages versus 4-5 for blog content), and placement of social proof elements.
Reading-level specifications are essential but often overlooked. In our experience, B2B content performs best at a 4th-6th grade level, while technical documentation might target 10th-12th grade. Include these targets explicitly in your guide.
Readability factors extend beyond reading level. For example, paragraph length dramatically impacts engagement – shorter paragraphs (40-60 words) typically perform better in digital formats. Similarly, specify when and how to use bullet points, numbered lists, and subheadings to improve scanability.
Optimize for SEO and Engagement
Modern SEO requires a more nuanced approach than simply stuffing keywords into content. We recommend creating a section in your style guide that lists primary and secondary keywords alongside example sentences demonstrating how they should appear in context. This can help AI (as well as humans) incorporate keywords while keeping content meaningful.
Example - Keyword Usage in Context: Primary keyword: "AI style guide" Secondary keywords: "brand voice consistency," "AI writing tools"
Good usage: "Creating an AI style guide helped our team maintain brand voice consistency across all our content, even when different team members use AI writing tools."
Poor usage: "Our AI style guide for AI writing tools ensures brand voice consistency when using AI.”
Headlines and subheadings require special attention since they significantly impact both search visibility and click-through rates. We've seen businesses succeed with templates that balance SEO value with brand voice - for instance, showing how a bland "How to Use Product X" can become "Transform Your Workflow: Our Team's Approach to Product X" while still maintaining keyword relevance.
Example - Headline Transformation:
Basic SEO headline: "How to Create an AI Style Guide”
Good Bloggy voice with SEO: "Building an AI Style Guide: What We've Learned From 50+ Content Teams”
Meta descriptions often get overlooked in style guides, but they're crucial for setting expectations and improving click-through rates. We suggest including character count guidelines (typically 150-155 characters) and formulas that incorporate primary keywords while maintaining the brand's unique voice. Similar guidelines for image alt text help maintain consistency across visual elements.
Fact-Checking and Attribution Standards
We've learned through trial and error that AI systems sometimes "hallucinate" statistics or combine elements from different sources incorrectly. For this reason, any style guide should require manual review of any specific numbers, dates, or named individuals mentioned in AI drafts before publication.
When AI suggests information that feels questionable but potentially valuable, we tend to rephrase them as qualified statements ("Some experts suggest..." or "According to recent industry discussions...") only when basic verification confirms the general direction is accurate.
Example of specific data requiring manual review: "83% of content teams report inconsistent brand voice when using AI tools, according to a 2023 Content Marketing Institute report.”
Example - Attribution Framework: "When discussing industry trends, we prefer to use our own observations rather than specific statistics unless we can verify them from primary sources. If mentioning general patterns, use qualifying language like 'we've noticed,' 'in our experience,' or 'according to conversations with our clients.’"
Brief AI on Staying in Lane
In our experience, AI systems often stray into topics outside a brand's expertise or authority, which can damage credibility and potentially create liability issues. We recommend explicitly listing subject domains where your brand has established expertise versus areas to avoid entirely.
For sensitive topics that might intersect with your brand's domain, we recommend a "refer but don't resolve" approach. This means acknowledging the existence of contested issues without attempting to definitively settle debates. For example, a financial technology company might acknowledge regulatory debates without making specific compliance claims that could mislead users.
When topics exceed your AI's appropriate knowledge boundaries, create a standardized response framework. We typically include links to trusted external resources like industry associations, government agencies, or recognized authorities in that specific field. This approach maintains user trust by acknowledging limitations rather than attempting to fake expertise.
For medical, legal, or financial topics, it’s especially important to include mandatory disclaimers that make clear the AI is providing general information, not professional advice. These should be written in plain language that reflects your brand voice while clearly directing users to qualified professionals for specific guidance.
Remember that knowing when to say "we don't cover that" actually strengthens user trust in the areas where your AI does provide assistance.
Example - Subject Domain Boundaries: "Good Bloggy content focuses on content creation, writing processes, and AI-assisted editing. We offer practical guidance based on our team's direct experience with these tools and processes.
We don't provide:
- Legal advice about copyright or intellectual property
- Medical guidance about wellness or health impacts
- Specific financial ROI predictions for content strategies"
Example - Refer But Don't Resolve Approach: Too definitive: "Using AI writing tools is completely safe from a copyright perspective, and you won't face any legal issues."
Better approach: "Content ownership in AI-assisted writing is an evolving topic. We focus on using AI as an editing assistant rather than a primary creator, which aligns with current best practices. For specific legal guidance about your situation, consulting an intellectual property attorney is advisable.”
Conclusion
We've found that a comprehensive AI style guide isn't just a nice-to-have document - it's essential infrastructure for maintaining brand consistency when you're using AI models to create content. When implemented properly, an AI-aware style guide can prevent the jarring voice shifts that often happen when multiple team members use AI tools with different prompting approaches.
Remember that implementing a strong AI style guide isn't about restricting creativity – it's about creating guardrails that enable more consistent, high-quality content creation across your entire team.