AI + Knowledge Management for Effortless Customer Support

AI is quietly making life a lot easier. But when it comes to customer support, AI’s impact is truly a game-changer.

What’s supporting this shift? It’s AI’s role in knowledge management for customer support.

Knowledge management, once a tedious and manual process, is now being powered by AI to be more intuitive. AI learns to provide real-time answers that make customer support smoother for everyone involved.

In this blog, we’ll delve into how AI knowledge management is making customer support smoother, for both agents and customers. Let’s explore how it’s changing the game for the better.

What is AI Knowledge Management?

AI knowledge management is the use of artificial intelligence to create, organize, and deliver information across an organization.

In customer support, this means AI can help generate support articles, decision trees, and other content, categorize it intelligently, and surface the most relevant answers to agents and customers in real-time.

As a result, customer service has become truly fast and a lot easier to scale, improving both the agent experience and customer satisfaction.

How AI Knowledge Management Improves Customer Support

AI works behind the scenes to support the people who create, manage, and use knowledge every day. Here are some of the AI Knowledge management benefits:

1. Keeps the knowledge base up-to-date with less manual effort

AI continuously monitors the performance of your knowledge base by tracking which information successfully resolves issues and where users drop off.

When it identifies outdated or underperforming information, AI automatically flags it for review, ensuring that knowledge authors spend less time maintaining and more time creating valuable content.

This reduces the chances of miscommunication or delays, ensuring that customers get the best possible answers in the shortest amount of time.

2. Helps knowledge authors create content faster

AI assists knowledge authors by suggesting article drafts, titles, summaries and more, giving them a solid starting point. It also automates content tagging and categorization to keep it well organized.

As new issues arise or customer queries evolve, knowledge authors can easily update or add information. As a result, agents have access to fresh content faster, which helps them resolve customer issues more quickly.

3. Surfaces the right answers for agents in real time

AI enhances search by understanding natural language, so agents don’t need perfect keywords to find information. It ranks results based on relevance and previous interactions so agents no longer waste time sifting through multiple search results or outdated information when providing customer support.

4. Powers more effective self-service for customers

AI powers FAQs, chatbots, voice assistants, and help centers so customers can find answers on their own without needing perfect keywords or technical language. This means customers can resolve issues independently, reducing the need for direct agent intervention.

AI also helps organize and present content dynamically by surfacing the most likely solution without needing to browse through multiple layers.

5. Deflects tickets with predictive suggestions

AI can detect common patterns in browsing or behavior (like repeated help center searches) and proactively suggest answers before a customer submits a ticket.

Predictive suggestions not only enhance the customer experience by providing faster resolutions but also help optimize support resources, reducing ticket volumes and improving overall efficiency.

Examples of AI in Knowledge Management for Customer Support

AI is leveraged in different ways to enhance knowledge management for customer support. Here are some real-world examples of making these innovations a reality.

1. AI-Powered Chatbots and Virtual Assistants

AI-powered chatbots and virtual assistants are designed to provide support by accessing relevant knowledge base content in real time.

These AI tools can handle both basic queries and more complex issues for a smooth self-service experience. When a query is beyond its scope, these tools can also escalate the issue to human agents.

Examples of AI-powered chatbots and virtual assistants:

• Zendesk Answer Bot instantly pulls relevant knowledge for customers
• LivePerson AI Chatbots deliver personalized assistance, guiding customers through troubleshooting and pulling information directly from the knowledge base.
• IBM Watson Assistant builds intelligent virtual assistants to offer automated support, while continuously updating the knowledge base based on interactions.

2. AI for Knowledge Base Generation and Curation

AI is transforming how knowledge bases are created, updated, and maintained by shifting the process from reactive to proactive.

Traditional methods of updating and generating content often rely on manual effort, such as reviewing tickets or editing articles periodically. AI, however, can assist by monitoring customer interactions, ticket trends, and search queries to help identify potential gaps in content or areas that need updating. This makes the process more dynamic and efficient.

AI is also helping with knowledge article generation based on frequently asked questions or recurring issues, making content creation faster and more responsive.

Examples of AI for knowledge base generation and curation:

• Knowmax uses Max AI to assist knowledge authors in producing relevant content in formats like decision trees, visual guides, faqs and more.
• Zendesk uses AI to analyze support tickets and customer queries, generating draft articles based on common issues.
• Document360 leverages AI to suggest new topics for the knowledge base and identify content gaps.

3. AI for Conversational Automation and Self-Service

AI is changing self-service by enabling conversational automation that can handle complex interactions with ease. These are designed to manage intricate processes that typically require human involvement.

From troubleshooting product issues to guiding users through multi-step product setups, conversational automation systems are built to empower customers to resolve complex problems independently.

These AI systems can guide users through complex decision trees and automate entire workflows, such as product returns, without requiring human intervention. By integrating with other systems (e.g., CRM or inventory management), conversational automation can even perform actions like scheduling appointments or processing refunds.

Examples of AI for conversational automation and self-service:

• Ada’s AI helps guide customers through troubleshooting, order updates, and other multi-step tasks.
• Intercom Resolution Bot is capable of managing complex interactions by offering customized solutions for troubleshooting, guiding customers through step-by-step processes, and providing real-time assistance for a wide range of issues

The Future of AI Knowledge Management in Customer Support

1. AI Will Handle 95% of Customer Interactions by 2025

AI is expected to manage 95% of customer interactions by 2025. It will handle simple, repetitive queries like “What are your delivery times?” freeing up agents to focus on complex issues that require human empathy and deeper understanding.

2. Generative AI Is the Cornerstone of Knowledge Management

44% of experts identify generative AI as the most crucial technology for knowledge management. Its ability to create new content, recommend knowledge assets, and update existing information is changing how organizations manage and disseminate knowledge.

3. Conversational AI to Cut $80 Billion in Contact Center Costs

Gartner forecasts that conversational AI will reduce contact center agent labor costs by $80 billion by 2026. This significant cost-saving is driving businesses to adopt AI solutions for automating customer interactions.

4. AI Agents Are Becoming Autonomous Decision-Makers

AI agents are evolving into autonomous systems capable of making decisions and performing tasks without human intervention. These agents are being integrated into various industries, including customer support, to enhance efficiency and responsiveness.

5. Privacy-Preserving AI Frameworks Are Emerging

As AI becomes integral to customer support, privacy concerns are prompting the development of privacy-preserving frameworks. The Privacy-Preserving Zero-Shot Learning (PP-ZSL) framework leverages large language models to generate responses without local training on sensitive data, ensuring compliance with regulations like GDPR and CCPA.

How Knowmax is Transforming Customer Support with AI-Powered Knowledge

AI-powered knowledge management helps teams keep pace with the growing demand for fast but accurate resolutions. Knowmax is purpose-built to deliver just that. It combines AI’s power with a comprehensive knowledge base to make support efficient.

It is easier to automate content creation and update knowledge in real-time with Knowmax, but it is also smoother to access the most relevant information to support teams, right when they need it.

By making AI a seamless part of the support process, Knowmax helps you scale with high-quality, efficient support across all channels.