How to Build and Maintain an AI Knowledge Base

AI has touched nearly every aspect of business, and knowledge management is no exception.

Knowledge bases have been a staple in customer support for decades. So many aspects of knowledge management can be enhanced and improved with AI, but the end goal remains the same: Delivering the right answer at the right time to your customers.

This guide breaks down the essentials of AI knowledge bases, from selecting the best software to building and maintaining helpful content that serves your customers.

What is an AI knowledge base?

An AI knowledge base is a system that combines traditional documentation with artificial intelligence technology to transform how your self-service content is organized and shared. 

The key difference from traditional systems is that AI knowledge bases don't just store and retrieve information. They actively help users find the most relevant information quickly, even when users are unsure of exactly what to ask for or how to ask for it. They also can speed up the work of creating and maintaining a knowledge base, easing the workload for documentarians behind the scenes.

For example, let’s start with how a knowledge base handles search. Let’s say a customer asks, “How do I integrate with Slack?”

A traditional knowledge base is keyword based and would surface articles that include the keywords “integrate” and “Slack.” This means it’s important that your content uses the same words your customers use to describe an issue; otherwise, the answer to their query may not be returned in the search results.

An AI-powered knowledge base can use NLP to understand the intent behind the question and surface content about “connecting” to Slack or using its API, even if the customer's search didn’t use those terms. Using generative AI, it can even generate a custom, human-like reply that walks the user through the step-by-step process of setting up the integration.

The ML technology works constantly in the background to identify if it matches the intent and answers correctly, making adjustments as needed so that future searches receive the best responses possible. 

That’s one example application. AI can be used throughout a knowledge base to do other things like: 

• Spot knowledge gaps and automatically suggest new content.

• Generate, expand, or edit documentation.

• Make proactive suggestions based on analytics and insights. 

The benefit of using an AI-powered knowledge base

All knowledge bases are beneficial because they:

• Improve customer experience. A knowledge base enables people to solve issues independently 24/7. Customer service teams can also offer more comprehensive (and helpful) answers using knowledge base articles, adding in more screenshots and visual aids than you typically can during a one-on-one interaction. 

• Reduce operational costs. Fewer support tickets and customer calls tend to land in support queues when people can find answers on their own. Support teams can also provide speedier service when product documentation is consolidated and accessible.

The problem is that traditional knowledge bases don’t fulfill those promises as often as you’d think. How many issues do you think are fully resolved via self-service?

A measly 14%.

Customers often find that traditional self-service solutions either misunderstand what they’re looking for or simply don’t have any content relevant to their issue. 

This is where an AI-powered knowledge base can make a huge difference. They can realize the benefits mentioned above, which leads to: 

• Improved content discovery. AI can automatically categorize content, suggest related articles, and understand conversational queries, making it easier for customers to find the information they want. 

• Higher customer satisfaction. Along the same lines, AI-powered technology like intent recognition is more likely to result in customers receiving helpful and accurate information that can actually resolve their issue.

• Better content quality. AI can suggest improvements based on customer feedback and make it easier to maintain content by spotting knowledge gaps and flagging out-of-date information.

• Simplified knowledge management. AI knowledge bases make it easier to scale self-service operations through those quality improvements. They can also drastically reduce the time teams spend drafting articles by creating, expanding, or improving content.

The top AI knowledge base software for 2025

“AI-powered” can mean many different things depending on the knowledge base software you’re considering. Some tools focus on providing conversational AI in a chat window, while others specialize in copilot tools that help teams do their jobs more efficiently.

To help you find the right fit, we’ve explored the top AI knowledge base software options, highlighting their unique strengths and the types of users they’re best suited for.

1. Help Scout — Best combined help desk and knowledge base

Help Scout is a simple but powerful customer support platform that makes it easy for teams to provide great customer service. It’s particularly well-suited for small to mid-sized businesses looking for an intuitive, scalable knowledge base and shared inbox solution.

Help Scout’s knowledge base tool, Docs, allows you to create, organize, and publish help articles that empower customers to find answers independently. 

It has a ton of features to help you build a help center from the ground up:

• You can create internal or external knowledge bases, making it a good tool for both team and customer-facing documentation.

• It has a customizable design so you can ensure it fully matches your brand. If you want an even greater degree of control, you can also use HTML, CSS, or the Docs API to further personalize your self-service experience. 

• You can embed Beacon, the platform’s web widget, on a web page or in-app to share relevant help articles where customers need them the most.

• Docs integrates with Help Scout's shared inbox, so your support team can easily search for and insert articles directly into their customer replies.

• It has satisfaction surveys and reporting capabilities, helping you get a better understanding of how your content is performing and areas where you can improve.

As for AI features, Help Scout takes a customer-first approach, focusing on thoughtfully designed tools that assist your team and create delightful customer experiences. 

AI Assist

AI Assist can streamline content creation by suggesting improvements and optimizing content for clarity and reader engagement. It can correct spelling and grammar, change the tone of your copy, or expand the text. AI Assist can also translate text, enabling your team to provide content for customers in their preferred language, even when it isn’t represented on your team.  

AI Answers

AI Answers is a smart search assistant that can deliver conversational responses to your customers’ questions by pulling information from your help center.

It always lists its sources, avoiding any confusion about whether your customers are interacting with a human or with AI. It also makes it easy to connect with a member of your team or browse articles directly if the AI’s answer misses the mark.

AI Drafts

While not a part of the Docs product itself, AI Drafts uses the content stored in your Docs site and your prior conversation history to automatically generate responses to incoming customer emails. Save time by simply reviewing the draft, editing if necessary, and hitting send.

These features and the Docs product are just a small part of Help Scout. The platform also provides a shared inbox for use with email, live chat, and social media channels, proactive messaging capabilities, and the ability to integrate with many third party applications. 

Best of all? Help Scout is affordable. All plans — including the free plan — come with at least one Docs site, unlimited users, and access to all AI features at no additional cost.

Pricing: Free plan and trial available. Paid plans start at $50 per month. 

2. Guru — Best dedicated internal knowledge base

If your company’s documentation is spread across many different tools and you want one source of truth that everyone can rely on, Guru is the best option.

Unlike traditional knowledge bases that sit on a dedicated website, Guru is a knowledge management tool that focuses on making information accessible everywhere teams work, integrating directly with other common business tools. These integrations mean that Guru can tap into all of your company’s shared knowledge to help answer your search questions.

Along those lines, Guru is a solid choice for teams that chat internally on Slack or Teams, store documentation in Google Drive or Dropbox, and have a customer knowledge base on one platform and their internal info on another. When things are spread out like that, it can be hard to know where to search for an answer, but because Guru can access all of the tools, it becomes a non-issue. 

Guru’s key features include:

• AI-powered search that provides personalized responses based on all knowledge sources you’ve integrated with the platform. Guru’s search is easily its most powerful feature because it can be embedded in your browser and accessed in the other software you work with. This means that you can always find the right information without needing to switch windows or applications. 

• GuruGPT, which lets you access an internal version of ChatGPT that’s trained on your company’s data. That means you can use it in all the ways you would normally use ChatGPT (to draft emails, brainstorm ideas, set up project outlines, etc.), but you’ll have more personalized results gained from the context and knowledge that your data provides.

• The ability to answer questions in Slack automatically through Guru without the searcher having to open a separate DM or window. Since adoption is often the first and toughest hurdle any new tool has to overcome, this type of convenience means employees don’t need to change their natural behaviors and can ask the knowledge base a question in-channel, just like they would a fellow colleague.

• Custom pages where you can curate information to be displayed to each team or department and AI-powered suggestions that can serve up useful information to employees based on what they’re working on.

• AI content assist tools that can help with content creation by correcting spelling and grammar, altering text tone or length, or translating content into other languages.

• AI-powered content summaries that readers can use to get caught up quickly without needing to wade through long articles.

• Duplicate and content gap detection to help keep your content accurate and up to date.

Pricing: Free trial available. Paid plans start at $15/user per month.

3. Document360 — Best for large companies with diverse documentation needs

Document360 is a knowledge base platform built for businesses aiming to create both customer-facing and internal knowledge. It offers robust customization options to handle large-scale documentation projects and has valuable features like version control, multilingual support, and rich analytics. 

When it comes to AI-specific features, Document360 has a lot, ranging from small quality-of-life improvements for article writing to major features that heavily impact your experience of the tool: 

• Its assistive search tool has AI-powered intent recognition that is used to surface relevant content without solely relying on keywords. This is combined with rich search analytics that track the success of searches, analyze user feedback and behavior, and use the data to help improve results over time.

• Eddy AI is their conversational AI tool that both employees and customers can directly interact with. It can remember context from previous chats so searchers can find answers without having to repeat themselves to reestablish context. 

• There are several AI-powered SEO features, such as title recommendations, meta description generation, and automatic article tagging. 

• AI charts is a feature that helps you create pie charts and flowcharts based on a natural language description of the data you want to display. 

• AI writer shortens the time it takes to write an article by helping you improve your text’s tone, spelling, grammar, and length. The tool can also translate copy to another language.

• AI summarizer can quickly boil down long documents allowing you to absorb content more quickly.

• You can also automatically generate a business glossary, which is especially useful if you’re in a field or industry that uses a lot of specialized vocabulary in your help content.

• An FAQ generator automatically produces FAQs at the end of an article to boost the quality of your content and make it more comprehensive and helpful.

Beyond AI, the knowledge base itself has a few unique features that are worth mentioning. These are specifically targeted at organizations with complex or specialized documentation needs:

• Audio assist allows users to consume help content by listening to it.

• A range of editing interfaces helps users draft and edit help articles, including a drag-and-drop homepage builder. 

• URL mapping provides context-aware help that allows you to surface a group of articles based on a manually-created URL.

Pricing: Free trial available. Contact for pricing. 

4. Notion — Best for sharing help content in various formats

Notion is a productivity and knowledge management platform that provides a good balance between organizing information and task management. Its biggest plus is that it has a highly customizable interface. You can create content in many formats, from simple text notes to complex databases, kanban boards, and even calendar views, making it a very versatile tool. 

Most of its AI features are bundled in Notion AI, an add-on feature which can be added to any plan for $8/member per month. Here is some info on the included features: 

• AI-powered search allows users to ask questions of the system in natural language and uses generative AI to respond in kind. You can also integrate multiple knowledge sources such as Slack, Google Drive, and Asana so that it can use all of your information to inform its answers.

• Its AI writing assistant helps users draft content, summarize text, and generate ideas based on prompts. These tools can be handy for all sorts of things. For example, you can paste in a transcript from a recorded meeting and ask Notion to automatically generate a summary, taking care of the task of documenting the meeting’s outcome. From there, the summary becomes part of your team’s knowledge base, and anyone who missed the call can easily ask Notion to fill them in.

• Beyond basic writing tasks, the AI can automatically suggest ways to streamline workflows, like creating templates or generating little snippets of code.

• Interacting with Notion AI is very intuitive. It’s powered by GPT-4 and Claude, so you’re able to communicate in the same way you would with ChatGPT. In addition to using the AI as just a search tool for your own info, you can also use it to access information across the web, or, like with Guru, use it to draft emails or standard operating procedures (SOPs) in your specific business context. 

• It has very granular controls for who can access which pages as well as many other security features, ensuring that your company data isn’t used to train AI models and that its data retention is minimal. 

When it comes to use cases, Notion is most suited to businesses looking for a company-wide internal knowledge solution, though it is possible to house public documentation in Notion as well. For instance, if you don’t have a ton of customer-facing support documentation, then it would be easy to throw up a FAQ page for easy access. It would even allow for the use of additional ways to display your content like flow charts, tables, videos, and contact forms.

However, if external customer support is your primary knowledge use case, then it’s probably best to go with a tool that integrates with your help desk and comes with more dedicated support features.

Pricing: A free plan is available. Paid plans start at $10/seat per month, with AI features offered as an add-on to any plan for an extra $8/member per month. 

Tips for building and maintaining an AI-driven knowledge base

Aside from data training (which is typically handled by your chosen software), building and maintaining a knowledge base with AI isn’t much different from any other knowledge base. However, there are a few specific tips that can increase your success.

Focus on high-volume issues

Customer service is a field that’s typically dominated by the 80/20 rule. 

This rule says that 80% of your conversation volume is probably caused by 20% of the issues your customers face. As such, the best approach to creating help content for any knowledge base starts with identifying the top 20% of high-impact, high-volume cases. Having great help content for the biggest issues will mean that you see a higher ROI more quickly.

AI can also help speed up ROI. If you’re setting up a knowledge base for your customers, try choosing a system that can use your conversation history as one of its data sources. That way, the AI can get more exposure to the way your customers ask for information, increasing its accuracy in identifying their search intent. 

For example, if password reset issues represent 15% of your ticket volume, the AI will quickly recognize the various ways customers express this:

• Direct requests like, "How do I reset my password?"

• Contextual queries like, "can't log in."

• Problem statements like, "forgot my password."

Then, it can adjust its algorithm so that the appropriate information is provided, even when those phrases don’t appear in your documentation.

Optimize help content for AI

Writing for AI isn’t very different than writing for people. 

The key difference is in how you structure the content. Here are some best practices for how to write help articles for AI-powered knowledge systems: 

• Each article should have a distinct focus. Overlapping information is much more likely to conflict, resulting in confusing answers. 

• Articles should state the question and the answer. Long, verbose articles describing everything there is to know about a feature are often not helpful for AI or for humans. Focusing on concise and precise information is much more effective. 

• Include context. This is the most complex part to get right. Including too much information can confuse the AI (and your customers!), but too little information can result in hallucinations where the AI tries to answer a question that it doesn’t have accurate answers to. You need to find the right balance between “as much as necessary” and “as little as possible.” 

• Describe images in the text. The solution to an issue should be explained in the article’s content. If you want to display the information visually, you can try using tables which are more accessible to AI. This is a best practice for accessibility anyway, but it’s also important for an AI knowledge base, as the tools aren’t always able to process images or screenshots.

• Use formatting. Use numbered lists, bullet points, and headings in your documentation. These make articles scannable for people and make it easier for an AI model to identify the specific part of the article that’s relevant to the question. 

• Be explicit. Don’t assume that people have (or AI has) a clear understanding of the overarching concepts that influence how your product works. Say you offer multiple products that work in totally different ways. Each article should always state which product you’re talking about, even if your documentation is broken up into separate product categories. Assuming that customers (or the AI) will prioritize the categorization over the information in the article can lead to misunderstandings.

Incorporate quantitative and qualitative feedback 

Feedback is critical when it comes to fine-tuning the AI capabilities of your knowledge base. 

AI features can significantly enhance user experiences — or create frustration — depending on how well they’re implemented and maintained. 

That means actively collecting and analyzing both quantitative and qualitative feedback.

Most quantitative data will likely come in the form of analytics offered by the knowledge base software:

• Search success rates can show where you have gaps in your knowledge base content or misalignment in intent recognition.

• Resolution rates often suffer from being a double-edged sword. High resolution rates for cases handled by an AI search assistant could mean great interactions or indicate frustration that led to customers abandoning their searches. 

• Engagement metrics can show you information like how many users interact with a smart search or chatbot feature. Spikes in specific areas can reveal popular topics, while low engagement may highlight confusing or irrelevant AI recommendations.

Quantitative data identifies problem areas, and then qualitative insights can be analyzed to understand the root causes and find actionable solutions. For example, if resolution rates are low for certain search terms, examine user feedback to see if the AI misunderstood intent or if the content itself was lacking.

Here are some ways to get that qualitative feedback:

• Regularly monitor and review interactions. This is especially important at the beginning, when the AI hasn’t been trained on hundreds of interactions yet. 

• Ask for feedback post-interaction. Ideally, ask for more than a simple satisfaction rating or score. Have a simple, open-ended question that allows users to explain their rating to you.

• Ask your team. If you’re using an AI knowledge base for external, customer-facing documentation, your support team will likely be able to tell you if and why AI-handled interactions aren’t going well. If you’re using the system for internal knowledge, ask colleagues for their experiences.

Turn maintenance into a team responsibility

Maintenance is even more crucial with an AI tool than with a traditional knowledge base. The AI’s effectiveness will always depend on the quality of its training data. 

To avoid bad information and major misunderstandings, you need a regular auditing process so you can identify those issues quickly and rectify them. Developing a process for rapid updates when your product changes is also a good idea. 

While having one or more dedicated knowledge managers isn’t a bad idea, getting involvement and engagement across your whole team will make a big difference in your ability to keep data accurate and up to date. Make sure it’s easy for anyone to flag outdated information, suggest improvements, or make small updates on their own. 

Establish processes to scale content

As your knowledge base grows, maintaining quality can become more and more challenging. 

Here are some ways to set yourself up for success:

• Streamline content creation with the help of AI. Features that help you draft content quickly can make it much easier to stay on top of updates.

• Implement a review process. Make sure all (human and AI) content is proofread by a subject matter expert and verified for accuracy before publishing.

• Have clear guidelines and templates for content creation. Both save time and ensure consistency.

• Automate your auditing process where possible. Lean on search analytics and AI tech to identify content gaps, analyze usage patterns, and highlight out-of-date content for review. 

Delivering quality self-service with AI 

AI knowledge management can help businesses provide employees and customers with quick access to knowledge that leads to a better work and product experience, and it will undoubtedly continue to improve over the coming years.

However, while AI can dramatically improve how we deliver help content, it's important to remember that the true measure of our success isn't the sophistication of the AI tools we use. Success is measured by how effectively we help people solve their problems and achieve their goals.

Just remember, it’s OK to get there through human effort, AI effort, or a mixture of the two.