A Guide to Optimizing Your Knowledge Base for AI

Assembled explores how to optimize your knowledge base for AI-driven customer support, offering best practices to improve both agent and customer experiences.

Integrating AI into your customer support strategy can be transformative, but only if executed intentionally.

We know that the potential of AI lies in its ability to deliver faster, more accurate customer service at scale, and to truly unlock this potential, you must ensure that your knowledge base is optimized for both AI and agents alike.

An optimized knowledge base is more than just a repository of information. It’s the foundation of how your AI system learns, responds, and improves.

When structured correctly, it empowers AI to deliver relevant and precise answers while also making it easier for customers and support agents to find the information they need.

So, how do you make your knowledge base AI-friendly and future-proof? Here are the best practices to get you started.

First, What’s a Knowledge Base, and Why Is It Critical for Support?

At its core, a knowledge base is an organized repository of information that provides answers to common questions, guides users through troubleshooting processes, and helps resolve issues without the need for direct interaction with a support agent.

It can be a series of FAQs, how-to articles, product guides, or even troubleshooting workflows. Essentially, it’s a self-service hub where customers (or agents) can find the information they need to resolve their problems.

For customer support teams, a well-maintained knowledge base is indispensable. Not only does it empower customers to find answers quickly and independently, but it also serves as the backbone of AI-powered systems.

When set up correctly, it reduces the volume of repetitive inquiries handled by your support agents, leading to faster response times and greater overall efficiency. Furthermore, it enables AI tools to provide accurate, contextually relevant answers in real time, resulting in smoother, more consistent support experiences.

In today’s fast-paced digital world, where customers expect immediate solutions, an optimized knowledge base plays a pivotal role in scaling customer support operations. It ensures that whether your customers are interacting with human agents or AI systems, they receive accurate, high-quality responses.

Integrating AI into your customer support strategy can be transformative. We know that the potential of AI lies in its ability to deliver faster, more accurate customer service at scale. But to truly unlock this potential, you must ensure that your knowledge base is optimized for both AI and human users.

An optimized knowledge base is more than just a repository of information. It’s the foundation of how your AI system learns, responds, and improves.

When structured correctly, it empowers AI to deliver relevant and precise answers while also making it easier for customers and support agents to find the information they need. So, how do you make your knowledge base AI-friendly and future-proof? Here are the best practices to get you started.

Prioritize Quality, Simplicity, and Clarity in Your Content

AI performs best when the information it accesses is clear, concise, and structured. Ambiguity leads to errors, while clear, direct language ensures better performance.

Do: Use Simple, Direct Language

Writing in clear, straightforward terms isn’t just good practice for human readers—it’s essential for AI. Avoid jargon and over-complicated phrasing. Remember, AI thrives on simplicity, and so do your customers. Clear language helps AI systems understand and deliver precise responses.

Example: Instead of “This process can be slow,” use “This process takes approximately 10 minutes to complete.” Precise timing provides the context that AI needs to deliver better responses.

Do: Provide Contextual, Standalone Answers

For AI to generate accurate results, each piece of information should stand alone. Avoid fragmented information that relies on other sections for context. AI benefits when answers are complete and self-explanatory.

Example: Replace “Available in Rose Gold and White” with, “The iPhone is available in two colours: Rose Gold and White.”

Do: Speak in Terms Your Customer Uses

Tailor your content to reflect the terms and phrases your customers use. This not only improves accessibility for your audience but helps AI recognize and match queries more accurately.

Create Discipline Around Structure and Organization

A well-organized knowledge base is critical for both AI and human understanding, and shouldn’t be overlooked. Structuring your content with clear, logical headings, categories, and subcategories enhances searchability and helps AI navigate through the content more effectively.

Do: Create a Logical Hierarchy With Headings and Subheadings

Breaking down complex topics into sections helps AI pull relevant content for specific queries. Organize your knowledge base with clear, intuitive headings that guide the reader and the AI system toward the right information quickly.

Example: use headings such as “Shipping Information” and “Return Policies” to ensure users (and AI) can easily navigate to the relevant sections.

Do: Utilize Bullet Points and Lists for Clarity

When explaining multiple steps or complex processes, use bullet points or numbered lists. This makes content easier to digest for human readers and helps AI better interpret the structure and meaning of the information.

Example: When explaining a return process, break it into numbered steps:

• Contact support
• Pack the item
• Ship the item with a provided label

Optimize for Text Over Any Other Format

AI systems excel at processing plain text but often struggle with visual elements like tables, graphs, or complex formats. Whenever possible, convert these formats into simple text to ensure AI can interpret and retrieve the information.

Do: Convert Visuals and/or Data Into Descriptive Text

Instead of using charts or tables, rewrite the information as descriptive text. This helps AI process the data without losing valuable insights.

Example: Instead of a table showing shipping costs, use: “Shipping is $5 for orders under $50, and free for orders over $50 in the continental U.S.”

Do: Use Simple, Structured Tables When Necessary

If tables are required, ensure they’re simple and use clear headers. Avoid merged cells or nested tables, as these confuse LLMs.

Maintain a Single (Not Multiple) Source of Truth

To avoid conflicting or outdated information, centralize your knowledge base into one platform. Having multiple repositories creates inconsistencies and errors, both for your AI system and human users.

Do: Limit the Number of Knowledge Systems

A single, well-maintained knowledge base is easier to manage and update. It also prevents AI from pulling incorrect or outdated information, ensuring higher accuracy in responses.

Example: use one main system that integrates seamlessly with all other platforms to maintain consistency in your support knowledge.

Do: Streamline Content Updates

Regularly audit and update your knowledge base. Assign dedicated team members to ensure your content is always up-to-date, removing outdated or irrelevant information.

Assign Dedicated Knowledge Managers

Maintaining your knowledge base is a continuous process. To keep it effective, assign team members who are responsible for managing and updating the content regularly.

Do: Establish Clear Ownership (Read: Make This Someone’s Job!)

Having someone in charge of knowledge base management ensures your content stays accurate and relevant. This helps both AI and human users get the best possible experience from your support content.

Example: dedicated knowledge manager can track usage trends, collect feedback, and ensure the knowledge base evolves with your customer needs.

Do: Create Cadences for Continuous Review and Iteration

AI-driven support systems learn from their interactions, but they need human oversight to perform optimally.

Regularly review the AI’s performance, identify gaps in the knowledge base, and refine the content accordingly.

This includes encouraging your support agents and customers to submit feedback on articles. This will help you spot gaps in content and ensure the knowledge base remains a valuable tool for AI systems and users alike.

Keep Your Knowledge Base Customer-Focused

At the end of the day, your knowledge base exists to serve your customers. Organize your content in ways that make sense to them and anticipate the questions they’re likely to ask.

As you optimize your knowledge base for AI, it will become temping to design for LLMs, and not for your users. Resist this temptation, and remember who benefits the most from your content.

Do: Think Like Your Users

Structure your knowledge base based on common customer inquiries. This not only improves the user experience but helps your AI system anticipate and respond to customer queries more effectively.

Example: If your customers often ask about shipping times, create a dedicated section titled “Shipping & Delivery” with FAQs, estimated timelines, and policies.

Do: Design for Self-Service

Remember, a well-structured knowledge base should empower customers to help themselves. The more intuitive and well-organized it is, the easier it is for customers to find what they need—without ever needing to contact support.

Future-Proofing Your Knowledge Base for AI

Your knowledge base is more than just a collection of articles – it’s a dynamic tool that can empower your AI and transform your customer experience.

By following these best practices, you’ll not only improve the quality of your AI responses but also ensure that your knowledge base remains a valuable, easily accessible resource for your customers and support teams.

This blog post has been re-published by kind permission of Assembled – View the Original Article

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Assembled is a Support Operations platform that helps companies maintain exceptional customer experiences, no matter what lies ahead. Leading brands use Assembled's workforce and vendor management capabilities to make optimal staffing decisions, gain visibility into performance and productivity, and unlock new ways to serve evolving customer needs.

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Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Author: Assembled