How to Feed Your Brand Voice to AI: A Complete Guide for Marketing Teams

(Fig: Image by Jason Rosewell)

If you’re using AI tools like Claude, ChatGPT, or Gemini to create content, you’ve probably noticed something: the output sounds…generic. Professional, sure. But it doesn’t sound like your brand.

The solution isn’t to abandon AI —it’s to teach these tools your brand voice.

In 2026, the brands winning with AI are the ones that have figured out how to package their brand knowledge and feed it to LLMs effectively. Here’s how to do it.

Why Brand Voice Matters in AI Content

According to recent predictions for 2026, brands that maintain consistency across AI-generated content will dramatically outperform those producing generic AI outputs.

When your brand guidelines are properly integrated into your AI workflow, every piece of content —from social posts to blog articles —automatically maintains your unique voice and style.

Without this setup, your team wastes hours editing AI-generated content to match your brand. With it, AI becomes a genuine multiplier of your team’s capabilities.

What Brand Knowledge Should You Prepare?

Before uploading anything to an LLM, gather these essential brand assets:

Core Brand Documents:

• Brand voice and tone guidelines
• Messaging frameworks and key value propositions
• Visual brand guidelines (colours, fonts, logo usage)
• Product descriptions and positioning statements
• Target audience personas

Example Content:

• 5-10 of your best-performing blog posts
• Top social media posts that capture your voice
• Email campaigns with high engagement
• Video scripts or podcast transcripts
• Customer success stories

Operational Guidelines:

• SEO guidelines and target keywords
• Content structure templates
• Legal and compliance requirements
• Industry-specific terminology

The key is quality over quantity. Ten excellent examples of your brand voice are far more valuable than fifty mediocre ones.

How to Set Up Brand Knowledge in Each Major LLM

ChatGPT: Custom GPTs

OpenAI’s solution is called “Custom GPTs”—dedicated chatbot instances trained on your specific brand data.

Setup Process:

1. Go to https://chatgpt.com/gpts and click “Create”
2. Skip the AI assistant setup wizard and write your own instructions
3. In the Configure tab:
   • Name your GPT (e.g., “Brandkit Content Writer”)
   • Add a clear description
   • Paste detailed instructions about your brand voice
   • Upload reference files (up to 20 files, 512MB each)
   • Enable relevant capabilities (Web Browsing, Code Interpreter, etc.)

What to Include in Instructions:

You are a content writer for [Brand Name]. Our brand voice is [describe tone: conversational/professional/playful etc.].

Key messaging:
- [Main value proposition]
- [Unique differentiator]
- [Core brand promise]

Always:
- Use UK/US English spelling
- Write in [active/passive] voice
- Keep paragraphs to [X] sentences maximum
- Include [specific elements]

Never:
- Use jargon like [examples]
- Make claims we can't back up
- [Other brand-specific rules]

Best Use Cases:

• Blog post generation
• Social media descriptions
• Email campaign copy
• Product descriptions

Claude: Projects and Skills

Claude offers two powerful options: Projects for ongoing work, and Skills for reusable expertise.

Claude Projects Setup:

1. Navigate to claude.ai and create a new Project
2. Add custom instructions in the Settings section
3. Upload brand documents to Project Knowledge (supports PDF, DOCX, CSV, TXT, HTML, RTF, EPUB)
4. Each project gets a 200,000 token context window (roughly 500 pages)

File Upload Best Practices:

• Keep individual files under 30MB
• Use clear, descriptive filenames
• Organize documents logically
• Update regularly as brand guidelines evolve

Claude Skills (New in 2025):
Skills are reusable packages of expertise that activate automatically when needed. Perfect for brand guidelines.

To create a brand skill:

1. Tell Claude: “I want to create a skill that applies our brand styling to any content I create”
2. Provide your brand specifications (fonts, colours, tone, structure)
3. Upload any existing brand PDFs or style guides
4. Claude packages everything into a skill that activates automatically

Pro Tip: According to Social Media Examiner’s guide on Claude Projects, the “Few-Shot Learning” method works exceptionally well. Upload 3-5 examples of your best content for each content type, and Claude learns your patterns far more effectively than from instructions alone.

Google Gemini: Gems

Google’s approach is called “Gemini Gems”—custom chatbots that remember your preferences and brand context.

Setup Process:

1. Access Gemini and create a new Gem
2. Name it clearly (e.g., “Brandkit Marketing Assistant”)
3. Add detailed instructions about your brand voice
4. Include examples of your best content
5. Specify use cases (blog posts, social media, emails, etc.)

Gemini Integration Advantage:
Gemini Gems work seamlessly across Google Workspace, making them particularly powerful if your team uses:

• Google Docs for content creation
• Google Sheets for content calendars
• Gmail for outreach campaigns
• YouTube for video content

Beyond Static Files: Connecting to Live Brand Guidelines

Here’s where things get really powerful in 2026: instead of uploading static documents that become outdated, you can connect your AI tools to live, dynamically updating web pages.

Why Live URLs Matter

Your brand guidelines aren’t static. They evolve. Your product descriptions change. Your messaging gets refined. Uploading PDFs means you’re always working with yesterday’s brand voice. Live connections mean your AI always has the latest guidelines.

ChatGPT: Actions and Web Browsing

Custom GPT Actions (Advanced):
Custom GPTs can connect to live APIs to fetch current data. This is perfect for:

• Pulling current product information from your website
• Fetching live pricing data
• Accessing your most recent blog posts as examples

Setup Process:

1. In your Custom GPT Configure tab, scroll to “Actions”
2. Click “Create new action”
3. Provide an OpenAPI schema for your endpoint
4. Your GPT can now call that API to fetch fresh data

Web Scraping Integration:
While ChatGPT can browse the web directly in conversations, Custom GPTs can also integrate with web scraping APIs like Bright Data or Oxylabs’ Web Scraper API to reliably fetch and parse your brand pages.

Example Use Case:
Your brand guidelines live at https://yourbrand.com/guidelines. Instead of uploading a PDF, configure an Action that fetches this page’s content each time, ensuring your GPT always references the current version.

Claude: Web Fetch Tool (Beta)

Claude’s Web Fetch API tool (launched in beta September 2025) is specifically designed for this use case.

How It Works:
When you include the web fetch tool in your API request, Claude can fetch and process full text content from URLs you provide—including PDFs.

API Example:

import anthropic

client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-sonnet-4-5",
    max_tokens=1024,
    messages=[{
        "role": "user",
        "content": "Write a blog post following our brand guidelines at https://yourbrand.com/guidelines"
    }],
    tools=[{
        "type": "web_fetch_20250910",
        "name": "web_fetch"
    }],
    extra_headers={
        "anthropic-beta": "web-fetch-2025-09-10"
    }
)

Key Features:

• Fetches full text content from web pages
• Extracts text from PDFs directly
• Includes safety mechanisms to prevent data exfiltration
• Works with Claude Sonnet 4.5, Opus 4.1, and Haiku 4.5

Security Note:
Claude cannot dynamically construct URLs. It only fetches URLs you explicitly provide or that come from previous fetch results. This prevents malicious prompt injection attacks.

Use Cases for Brand Teams:

• Reference live style guides hosted on your Brandkit account
• Pull current product specs from your website
• Access the latest brand messaging deck stored online
• Fetch recent successful content as examples

Gemini: Real-Time Web Integration

Gemini has native web browsing capabilities and can access live URLs when you enable the browsing feature.

Current Limitations:
As of 2026, Gemini Gems cannot directly pull from live URLs in the same way Claude’s API can. However, Gemini in conversations can browse and reference websites when asked.

Workaround for Gems:
Create a workflow where:

1. Use Gemini’s browsing to fetch your brand guidelines
2. Copy the relevant sections into your Gem’s instructions
3. Update quarterly or when guidelines change

MCP (Model Context Protocol): The Future

The Model Context Protocol is an emerging standard that allows AI models to securely connect to external data sources.

What MCP Enables:

• Direct connections to your CMS
• Real-time access to your brand asset library
• Integration with your style guide platform (e.g. Brandkit)
• Connections to Google Drive, Notion, or other documentation tools

Current Status (2026):
MCP servers are available for Claude through the Claude Code interface and API integrations. Expect broader adoption across other LLMs throughout 2026.

Building Your Own Brand API

For ultimate control, create a simple API that serves your current brand guidelines:

Simple Example (Python/Flask):

from flask import Flask, jsonify
import requests
from bs4 import BeautifulSoup

app = Flask(__name__)

@app.route('/brand-voice')
def brand_voice():
    # Fetch your live guidelines page
    response = requests.get('https://yourbrand.com/guidelines')
    soup = BeautifulSoup(response.content, 'html.parser')
    
    # Extract the relevant sections
    guidelines = {
        'tone': soup.find(id='tone').get_text(),
        'voice': soup.find(id='voice').get_text(),
        'examples': [ex.get_text() for ex in soup.find_all(class_='example')]
    }
    
    return jsonify(guidelines)

if __name__ == '__main__':
    app.run()

Then connect your Custom GPT or Claude integration to this endpoint. Now your AI always has the latest guidelines.

Best Practices for Live Connections

Cache strategically:
Not every API call needs to fetch fresh data. Claude’s prompt caching can store fetched content for reuse, reducing costs and latency.

Monitor for changes:
Set up alerts when your brand guidelines change so you know your AI will reflect updates.

Fallback to static:
Always keep a recent PDF backup in case your live URL becomes unavailable.

Version control:
Maintain version history of your guidelines so you can test how AI interprets different versions.

Access control:
Use authentication for internal brand guidelines. Don’t expose sensitive brand strategy publicly. For example: Brandkit enables individual brand guidelines to be placed is different Vaults, enabling fine grained user access permissions for individual guides.

Hybrid Approach: Best of Both Worlds

The most robust setup combines static and live sources:

Static uploads: Core brand voice documents that rarely change
Live fetching: Product specs, pricing, current messaging, recent content examples

This ensures your AI has foundational knowledge that’s always available, plus current information when needed.

Advanced Techniques for Better Results

The IPO Framework

Content creator Casey Hill uses the IPO (Input-Process-Output) framework with Claude Projects:

Input: Raw material you provide (transcript, rough notes, topic)
Process: Your brand instructions + few-shot examples
Output: On-brand, ready-to-use content

This framework ensures consistency while allowing flexibility for different content types.

Few-Shot Learning vs Long Instructions

Research shows that providing 5-10 concrete examples of your brand voice produces better results than lengthy written instructions. Your AI learns how you write, not just what you write about.

Example Structure:

• Upload your 5 best blog post introductions
• Upload your 5 best email subject lines
• Upload transcripts from your top 3 videos

The AI patterns match far more effectively than from reading: “Be conversational but authoritative.”

Version Control Your Brand Assets

As your brand evolves, so should your AI training:

• Date your uploads (e.g., “Brand_Guidelines_Jan2026.pdf”)
• Remove outdated examples quarterly
• Test new brand changes in a separate project first
• Keep a changelog of what you’ve updated

Testing Your Setup

Before rolling out to your team:

1. Run comparison tests: Generate the same piece of content with and without your brand knowledge. The difference should be obvious.

2. Check for consistency: Create 5 variations of the same content type. They should all sound distinctly like your brand.

3. Test edge cases: Ask for content types you haven’t explicitly covered. Does it still maintain brand voice?

4. Get team feedback: Have team members use your custom GPT/Project/Gem and report what feels off.

Common Mistakes to Avoid

Uploading Everything: More isn’t better. Focus on your absolute best examples. Poor examples teach bad habits.

Vague Instructions: “Be professional” means nothing. Instead: “Write like you’re explaining to a smart friend who’s new to the industry.”

Ignoring Updates: Brand guidelines from 2023 won’t capture your 2026 voice. Schedule quarterly reviews.

Not Testing Outputs: Even the best setup needs human review. AI should accelerate your process, not replace quality control.

Forgetting Team Alignment: If your team doesn’t know these tools exist, they won’t use them. Create documentation and provide training.

Measuring Success

Track these metrics to evaluate your brand AI setup:

• Editing time reduction: How much less time does your team spend editing AI outputs?
• Brand consistency scores: Run outputs through your internal review process
• Team adoption rates: What percentage of your team actively uses these tools?
• Content velocity: Can you publish more content while maintaining quality?

The 2026 Reality

By 2026, brand visibility isn’t just about SEO—it’s about how AI platforms understand and represent your brand. When potential customers ask ChatGPT, Claude, or Gemini about solutions in your space, you want your brand to appear in those answers.

The brands that document their voice, codify their knowledge, and teach AI tools to represent them accurately will dominate. The ones that treat AI as a generic writing assistant will produce generic content —and disappear into the noise.

Brandkit is primed to act as a single dynamic knowledge source for your brand

Brandkit has evolved from a simple DAM for distributing brand assets, and now has several tools to enable it to act a central dynamic source of all your visual media assets, and brand knowledge —for both human users and AI.

When you upload files like images and video, or add brand knowledge by way of custom web pages, FAQs, Blog Posts, Brand Guidelines, and Links to external media, Brandkit generates structured metadata for you automatically.

It then serves up that metadata and knowledge for crawling and ingestion into LLMs, and use by Chatbots and Agents, as dynamic knowledge sources.

Getting Started This Week

You don’t need to build the perfect system immediately. Start here:

Day 1: Gather your 10 best pieces of content that capture your brand voice
Day 2: Add your best content to your Brandkit (Digital Assets, FAQs, Brabd Guidelines, Blog Posts, Links)
Day 3: Create one Custom GPT, Claude Project, or Gemini Gem for your most common content type
Day 4: Test it with your team and gather feedback
Day 5: Refine based on results
Day 6: Document the process for your team

The setup takes a few hours. The time savings compound forever.

Your brand voice is one of your most valuable assets. In 2026, that means teaching AI to speak in that voice —authentically, consistently, and at scale.

Happy branding :)