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<\/a><\/p>\nAn AI knowledge base uses artificial intelligence to deliver accurate answers to customers. AI tools, like HubSpot\u2019s AI agent Breeze<\/a>, can help teams craft knowledge base documentation to solve common issues. Chatbot integrations can speed up replies while keeping the human touch.<\/p>\n This article features seven AI knowledge base examples from companies utilizing AI and explores:<\/p>\n Table of Contents<\/strong><\/p>\n <\/a> <\/p>\n AI transforms a static knowledge base into an adaptive system that learns from usage patterns, agent input, and customer interactions. In fact, pairing an AI knowledge base agent<\/a> with a customer agent<\/a> can cut resolution times by 40%, according to HubSpot\u2019s research<\/a>. HubSpot also found that an AI system can resolve nearly half of support tickets autonomously,<\/p>\n Before showing AI knowledge base examples, these artificial intelligence features make support documentation easier to use and maintain.<\/p>\n The most common use case for leveraging AI is creating knowledge base documents. AI tools can ingest information from support tickets, new product release announcements, and webinars. From there, agents like HubSpot Breeze<\/a> can write knowledge base articles.<\/p>\n Here\u2019s a personal AI knowledge base example: In my current customer success role, I\u2019m working through this process firsthand by using AI to repurpose webinar content into written articles. That starts with uploading a webinar into an AI tool and asking it to create a guide with clear steps.<\/p>\n While it\u2019s taken a few iterations and prompt adjustments to get where I want it, I\u2019m really excited about the output I\u2019ve landed on. It\u2019s made this process so much easier than trying to pluck out insights from a webinar transcript and write the guide myself.<\/p>\n Pro tip: I ask the tool to write the prompt from a specific point of view or persona. For example, if my webinar presenter is a marketing industry professional, I may create a prompt that says, \u201cYou are a marketing director. Create a guide in a helpful tone and include step-by-step guidance where relevant.\u201d<\/p>\n Knowledge bases degrade when content becomes outdated or irrelevant. Articles with high fallback rates or low usage are a signal to the system that answers are no longer effective.<\/p>\n AI automates the review process and shortens the cycle between identifying gaps and publishing revisions.<\/p>\n In addition, many AI tools will make suggestions for revising the content (or creating something new) to address any gaps. AI can also identify duplicate articles or out-of-date information, recently updated policies, or feature releases that require updated documents. This helps you keep your knowledge base up to date in a more timely manner.<\/p>\n Pro tip:<\/strong> In HubSpot Service Hub, build a content review workflow<\/strong> that flags underperforming articles based on a review trigger:<\/p>\n Use Breeze Intelligence<\/a> to create draft updates and automatically route them to subject matter experts for approval before publishing in the HubSpot knowledge base software<\/a>.<\/p>\n Customer success agents often spend a large share of their time drafting responses to repetitive questions. AI changes this by generating draft replies sourced from knowledge base content and prior conversation history. Automating draft creation shifts the agent\u2019s role from writing to reviewing, improves response consistency, and speeds ticket resolution.<\/p>\n Pro tip:<\/strong> Use HubSpot\u2019s Reply Recommendations<\/a> in Help Desk, which suggests contextually relevant replies directly inside the agent workspace.<\/p>\n AI can also correctly tag and organize documents. That helps keep knowledge bases organized, saving reps from hours of manual work. AI can look at things like the article\u2019s product or topic in order to classify articles, which makes it easier for agents and customers to find the information.<\/p>\n Finally, AI is a fantastic tool for translating documentation. As companies scale, teams may need to update support documentation to reflect new languages. AI can easily translate your existing documentation into new languages.<\/p>\n Beyond that, AI can map KB articles to the customer\u2019s language preference in the CRM, which ensures a smooth customer experience and higher satisfaction scores. No more international customers are left to navigate English-only help content.<\/p>\n Pro tip:<\/strong> Create language variations directly in HubSpot Service Hub, configure chat targeting, and map language preferences in Smart CRM<\/a>. Start with high-volume markets to prove value before scaling to all supported regions.<\/p>\n <\/a> <\/p>\n AI knowledge bases are no longer experimental add-ons. Today, AI-powered support is a core infrastructure of customer support. Of the customer experience leaders who participated in HubSpot\u2019s State of Service report<\/a>, 65% said their teams already use AI across customer experience operations.<\/p>\n The following AI knowledge base examples illustrate how organizations at different growth stages implement AI features and see a positive impact.<\/p>\n Small SaaS teams don\u2019t have the headcount to absorb ticket growth. Companies reduce support ticket volume by implementing AI-powered knowledge bases. They start small, scope narrowly, and still free up agent time.<\/p>\n RevPartners is a RevOps SaaS consultancy that builds go-to-market systems on HubSpot. Recently, they launched a Breeze Customer Agent<\/a> called Jarvis. In just 30 days, the team cut down their repetitive support load.<\/p>\n The focus wasn\u2019t on building a chatbot for everything. Instead, the team focused on deflecting the same SaaS onboarding and pricing questions their team kept answering over and over.<\/p>\n Pro tip:<\/strong> Start by publishing those onboarding and billing articles directly inside the HubSpot knowledge base software<\/a>. That\u2019s where you can build articles, set deflection rules, and connect content to your CRM so the AI assistant never pulls from unapproved sources.<\/p>\n Konnected is a DTC brand selling smart home alarm and automation panels. On their support hub<\/a>, they introduced Kai<\/strong>, an AI-powered support specialist that sits alongside their knowledge base. Customers can ask questions directly in chat, and if Kai can\u2019t answer confidently, the conversation escalates to a human agent with full context.<\/p>\n For DTC brands, this hybrid model shortens the drafting time for repetitive tickets and lets agents focus on more complex cases.<\/p>\n When I asked Kai for help with selecting garage openers, he thought for a few seconds and pulled up a quick breakdown of models and use cases. Kai also drafts replies like shipping clarifications or warranty coverage explanations. I found that Kai did an amazing job for an AI agent.<\/p>\n Companies that scaled to mid-market are dealing with a new suite of support issues. They need to create handoff workflows based on plan tiers and provide multilingual answers. AI can help these teams level up.<\/p>\n Enterprise and high-tier clients demand a superior CS experience. For that, Lemlist provides personalized deflection by connecting the AI knowledge base with CRM data. Their chatbot analyzes whether or not a customer is on the Enterprise plan and decides who to route the ticket to.<\/p>\n Source<\/em><\/a><\/p>\n Enterprises operate at a scale where fragmented support systems quickly undermine the global customer experience \u2014 especially when 82% of customers<\/a> want their issues solved immediately. AI-driven knowledge bases also help reduce the need for massive agent headcount.<\/p>\n Let\u2019s explore the most popular enterprise-level knowledge base features.<\/p>\n The world\u2019s largest online retailer offers an unparalleled international user experience through AI-driven chatbots. These systems adapt to the language of each browser or switch to another language upon request.<\/p>\n Source<\/em><\/a><\/p>\n Knowledge base articles are localized with region-specific content such as delivery times, return policies, and payment methods. This way, Amazon ensures relevance across dozens of markets without added headcount.<\/p>\n Payoneer, a global fintech platform, integrates AI chatbots in its customer support to triage inquiries at scale. The system uses natural language processing to detect sentiment in messages, such as frustration or repeated demands for escalation.<\/p>\n When a customer insists on speaking with a human \u2014 as seen in the screenshot \u2014 the AI bypasses menus and routes the case directly to a live agent.<\/p>\n Source<\/em><\/a><\/p>\n It took me two attempts to escalate the chat, but it worked, and the agent jumped in within a minute.<\/p>\n Payoneer\u2019s \u201cI\u2019m the new AI-powered search assistant!\u201d functions as an AI-driven FAQ layer. It sits on top of the knowledge base, parses common customer intents, and serves back ready-made answers in conversational form.<\/p>\n For customers, it saves time on getting a direct answer quickly. Plus, customers don\u2019t need to know which article to click or where to look. The assistant interprets intent and surfaces the right snippet.<\/p>\n Source<\/em><\/a><\/p>\n <\/a> <\/p>\n To select AI knowledge base software, CX leaders weigh in on technical capabilities, governance, and usability. The following checklist outlines the core features that determine whether a platform can scale beyond basic deflection and support long-term customer experience goals:<\/p>\n HubSpot Service Hub<\/a> delivers all these capabilities on a single platform with a shared data layer, native AI (Breeze agents), and proven service workflows that scale from startup to enterprise.<\/p>\n <\/a> <\/p>\n AI tools streamline knowledge base development and maintenance. Teams can use these tools to analyze data from support tickets, identify content gaps, and create the content to guide customers. AI excels at cross-referencing existing articles with new information and managing updates at scale.<\/p>\n Here are tips for making the most of AI in your knowledge base.<\/p>\n Start with the data, and use AI to help analyze it. Service teams can find friction points by evaluating support ticket themes, customer feedback, or other sources of data. AI can help you surface the most important challenges to address.<\/p>\n I personally leverage AI to help me cross-reference support ticket data and customer pain points to surface the top themes. In my prompt, I specifically ask AI to focus on themes that I can address with education or training. I think it\u2019s incredibly important to consider customer feedback in every step of the journey, and using AI to analyze that feedback makes the process much quicker!<\/p>\n If the team\u2019s customer support software has an AI component, it can easily surface content gaps and show what questions aren\u2019t being answered with existing articles. AI tools like Breeze might even offer to write knowledge base content based on support tickets.<\/p>\n When the knowledge base software leverages Natural Language Processing (NLP), the search function can understand more than just keywords. By understanding sentiment and the core of their questions, AI platforms can assign the most relevant articles to help.<\/p>\n Bonus points if it offers an AI-Assist that creates a summarized response for customers. That gives them the option to skim as they self-serve!<\/p>\n\n
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Top 5 AI Knowledge Base Features That Improve the User Experience<\/h2>\n
AI can create knowledge base content.<\/h3>\n
AI flags underperforming articles and drafts for updates.<\/h3>\n
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<\/p>\nAI-drafted replies for customer success agents.<\/h3>\n
AI can keep your knowledge base organized.<\/h3>\n
AI-driven multilingual knowledge base.<\/h3>\n
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<\/p>\nAI Knowledge Base Examples From Companies That Cut It<\/h2>\n
Startup AI Knowledge Base Examples<\/strong><\/h3>\n
Startup SaaS AI knowledge base example: RevPartners deflects repetitive onboarding questions with HubSpot AI.<\/strong><\/h4>\n
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<\/p>\nHow to Replicate This AI Knowledge Base Example in HubSpot<\/strong><\/h5>\n
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Why This AI Knowledge Base Example Works<\/strong><\/h5>\n
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<\/p>\nSmall ecommerce AI knowledge Base example: Konnected\u2019s AI agent excels at suggested replies.<\/strong><\/h4>\n
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<\/p>\nHow to Replicate This Knowledge Base Example in HubSpot<\/strong><\/h5>\n
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Why This AI Knowledge Base Example Works<\/strong><\/h5>\n
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Mid\u2011market Knowledge Base Examples<\/h3>\n
Mid\u2011market SaaS example: Lemlist\u2019s AI agent tailors deflection by plan tier.<\/strong><\/h4>\n
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<\/p>\nWhy This AI Knowledge Base Example Works<\/strong><\/h5>\n
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Enterprise AI Knowledge Base Examples<\/h3>\n
Enterprise online retailer example: Amazon uses a multilingual knowledge base and chatbots.<\/strong><\/h4>\n
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<\/p>\nWhy This AI Knowledge Base Example Works<\/strong><\/h5>\n
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Enterprise FinTech example: Payoneer\u2019s AI-driven customer support analyzes sentiment and escalates angry chats to a human agent.<\/strong><\/h4>\n
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<\/p>\nHow to Replicate This AI Knowledge Base Example in HubSpot<\/strong><\/h5>\n
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Why This AI Knowledge Base Example Works<\/strong><\/h5>\n
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Enterprise FinTech AI knowledge base example: Payoneer AI-driven FAQs to simplify self-service.<\/strong><\/h4>\n
![\"an](\"https:\/\/53.fs1.hubspotusercontent-na1.net\/hub\/53\/hubfs\/an%20ai-driven%20faq%20example.webp?width=650&height=252&name=an%20ai-driven%20faq%20example.webp\")
<\/p>\nWhy This AI Knowledge Base Example Works<\/strong><\/h5>\n
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Buyer\u2019s Checklist for the Best AI Knowledge Base Software<\/h2>\n
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Tips for Building AI Knowledge Bases<\/h2>\n
Make the most of data.<\/h3>\n
Find the gaps.<\/h3>\n
Host your knowledge base on an AI-powered platform.<\/h3>\n
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