The power of AI self-service: Benefits and best practices

Contact centers often find their capacity maxed out, with reps frequently tied up handling routine queries. This leads to longer wait times for customers with more urgent or complex issues. AI self-service tools can offer a solution to this problem.

Imagine a phone system where AI picks up the call, listens to what the customer wants, and either resolves the issue or puts them through to the right person. Now add AI that is trained on your products and services, speaking to customers in real time via chat, phone, SMS, email, social media, and the help widget on your site. 

In this article, you’ll learn what AI self-service tools are, the benefits they deliver, and how to track their impact on businesses. We’ll also cover how to implement your own AI self-service solution, including the challenges you might face and how to overcome them.

AI self-service refers to tools powered by artificial intelligence (AI) that let customers interact with a company or organization without having to speak to a human agent first — or at all. The best-known types of AI tools are chatbots, or virtual agents, voice assistants, or voice bots, and interactive help centers. They can answer simple questions or hold more in-depth conversations with you, like choosing the right service plan or troubleshooting an issue you’re having with a product.

Self-service AI tools run on large language models like ChatGPT, Claude, Meta, or DeepSeek. Companies upload documentation about their products and services, like descriptions and manuals, to their knowledge base. You can then set up workflows according to your most commonly asked questions and queries. When your AI self-service tool talks to a customer, it serves the appropriate response to that query based on the workflow and information in the knowledge base. This helps answers stay accurate, compliant, and on-brand.

Some AI-powered customer service tools go further by drawing responses from a company’s customer relationship management (CRM) system. This adds extra functionality like letting customers log in to check their order status, update their personal details, get buying recommendations based on their purchase history, and review previous support requests without needing to speak to a live agent.

AI self-service tools are part of a wider trend toward customer service automation, which involves using technology to support humans when they handle routine jobs. 

A good everyday example is the email confirmation that’s sent after you sign up for a newsletter. A human didn’t send that email. Instead, your signup triggers an automated workflow, just like how an AI tool replies to a support question. AI self-service takes this same principle and applies it to conversations, not just tasks. A new era of agentic AI makes it possible for self-service solutions to resolve more complex queries with minimal human involvement.

AI has moved from a helpful call center feature to a must-have. In fact, 44.1% of companies are working on an AI strategy, up from 33% the year before, according to a Zoom-sponsored report by Call Centre Helper.

Let’s take a look at nine advantages of AI self-service..

24/7 availability and instant support

AI works around the clock, including at night, weekends, and public holidays. Because it never needs sleep or takes time off, customers can get the answers they need whenever they need them.

Reduced wait times for customers

Customers can typically get through to an AI self-service bot without the need for a long queue. It can handle straightforward inquiries and, when appropriate, automatically escalate issues to a human agent for priority support.

Improved agent productivity

Let AI handle high-volume queries that add little or no value to your business, like order tracking, password resets, or FAQs. Give your human agents the more complex interactions, so that your customers will value speaking to a real person.

Cost savings

An AI-powered customer self-service solution can handle thousands of conversations without the need to hire extra staff.

Zoom’s customer service team solves 97% of our customer queries with our AI self-service solution, Zoom Virtual Agent.

Enhanced customer satisfaction

Some customers would prefer AI to take them step-by-step through a process rather than a human. For example, a client setting up and running their first payroll on their accounting software might want to do it themselves so they’re more confident next time around.

Ability to scale

AI customer self-service bots can handle the extra demand that seasonal spikes or a major product launch bring. During peak times, set them up to answer multiple inquiries in parallel across social media, email, chat apps, and messaging apps. Your customers will appreciate consistent, reliable support.

Data collection and insights

Your AI-powered self-service tool can collect and share customer experience data with you. It can pull metrics like the number of interactions, customer response patterns, and the number of issues resolved or escalated. It can reveal the questions people are asking repeatedly, which can be fed back into your AI bot workflows and live agent training to give customers and prospects more valuable answers.

Consistent and accurate information

AI only draws answers from the information you upload. By keeping it current with your latest products, policies, and pricing, customers get correct and consistent responses.

Aligns with customer preferences

The thought of speaking with a rep stresses 82% of customers, according to a Tidio report. Plus 80% of those who’ve had success with bots prefer them always, often or sometimes, according to recent Zoom commissioned Morning Consult research. Give your target audience what they want in the format they’re most comfortable with.

The promise of AI self-service extends beyond answering customer questions. The technology can:

• Enhance your knowledge base: Ask your AI self-service solution to highlight which topics customers are most likely to talk about. Then, check your current knowledge base and, if the information it’s drawing on is missing, outdated, or unclear, revise or expand it so customers get the right answer the first time. The more accurate your content, the more queries your solution can resolve. 
• Utilize natural language processing (NLP): Use AI to analyze how your customers use language, then ask your AI tool to adjust its tone, phrasing, and vocabulary to match them. This’ll make its responses over live chat, SMS, or social media more relatable to customers. 
• Utilize virtual assistants: Use AI to deal with routine inquiries, like answering basic product questions and tracking orders. This reduces call volumes, shortens waiting times, and frees up your agents to work on cases that need human oversight, lessening the team's overall workload. 
• Create personalized recommendations: Build an AI self-service agent that suggests the best products and services based on customers' past interactions, purchase history, and browsing behavior. This can help customers find what they want more easily and discover great products they may have missed before. If a customer wants to buy from a human, AI can automatically transfer the full conversation and history so the customer doesn’t have to start from scratch.

Troubleshoot: Give your customers the option to raise issues with your AI tool, whether that’s walking them through a potential fix or helping them word a complaint email. If an unhappy customer feels the AI is genuinely trying to help, this can reduce tension and the chances of escalation. If the issue does need to be passed to a team member, they will see the full context, making it much easier to resolve the issue quickly and professionally.

Deploying AI can free up your agents to focus on complex or high-stakes issues that need a human touch. Here are four key metrics to keep an eye on to see just how much value AI is adding to your business:

• Customer satisfaction scores (CSAT): CSAT scores show the level of happiness customers have with your product or service. Program your AI bot to request a CSAT rating at the end of each chat. If you get a low score, look back at that call or conversation to see why and coach the agent on how to better handle similar situations next time.
• Self-service success rate: This measures how often your AI solves issues without human intervention. At the start, expect a low figure as you learn how to train your bot. As you feed it more knowledge base content, it’ll get better. Help it along by finding out which questions get escalated the most. Check if it has the right information to respond, and review how it phrases answers to make sure they’re easy for customers to follow.
• Average response time: This is how long it takes to reply to a customer query. With AI, that’s seconds compared to minutes or sometimes days for emails and web forms. Use this information, along with other metrics, to show that self-service works and your contact center is succeeding in being more responsive without adding more headcount.
• Self-service containment rate: This shows how many routine queries your AI handles without passing them to a live agent. A high containment rate suggests customers are getting the outcomes they want, giving your team more time to work on complex issues.

Additional ways to track the performance of your AI self-service tool include:

• A/B testing: Test out different opening prompts on your AI self-service tool to see which lead to better outcomes. Choose the best-performing prompts to increase your issue containment rate.
• Data segmentation: When you know which prompts work, go deeper. If customers log in to your AI self-service tool, group them by purchase history, intent, and query type. Then use that information to deliver custom responses for each group. This extra personalization can improve resolution rates and lead to more upsell or cross-sell opportunities.

CRM integration: When customers log in, make sure your CRM saves the conversation. Agents can see what customers have already asked about, and your AI can build a bigger picture of intent to predict what they’ll need next. This can make your human support feel more unified and customer-centric.

AI self-service offers the potential for major commercial gains. But as with all new technology, there are a few practical hurdles businesses have to clear first. Here are four common challenges and how contact center leaders tackle them:

Maintaining a human touch

As we discussed earlier, it’s possible to change AI's tone and vocabulary to sound more like a human. However, this is not always convincing because AI lacks emotional intelligence and context awareness.

This may present a problem if something goes wrong. Your self-service bot may be AI, but your customers aren’t. They still want and expect understanding and empathy.

If a customer feels your AI is robotic or dismissive, it can escalate the situation and damage their trust in your brand.

Meeting evolving customer needs

AI self-service bots are only as good as the information you feed them. Uploading information to them is not a set-it-and-forget-it situation. If your AI offers a product you no longer stock or you’ve updated your return rules, it will generate false responses.

If your support team receives a call from a customer and tells the customer something different to the chatbot, this is likely to damage the customer’s confidence in your business.

Embracing new technology

Rolling out any new system or technology can be a challenge for a business. This is especially true for AI as agents may worry about their jobs and the C-suite may be concerned about return on investment.

Be sure to show your agents and stakeholders the benefits of AI to encourage internal buy-in and greater adoption.

Managing security and privacy concerns

Customers want reassurance that their data is safe, particularly if they can log into your chatbot to access their order history and financial details.

Explain the measures you’re taking to keep sensitive data safe, and that your self-service AI tool follows data and privacy regulations.

AI is not only an opportunity to cut costs but also a chance to offer high-quality service to your customers. Here are three ways you can make it a success:

Create a strategy

First, decide what purpose your AI tool is there to serve. Start by looking for the points in your customer journey where demand for sales and service support is the highest.

Look at the questions customers ask:

• Pre-sale, across your chat, email, and call logs. Then set up your AI bot to answer these questions to generate leads
• Post-sale, to find out where customers are most likely to get stuck using your products and services

Don’t start off with a grand plan. Target four or five use cases to launch with and note your successes and failures from your earliest tests before you add more scope to your AI tool.

Continue training the AI

Earlier, we covered the importance of keeping your AI’s content and knowledge base current. You’ll also need to regularly update and teach your AI to answer questions more accurately and reliably.

Many AI self-service tools use a technology called retrieval-augmented generation (RAG). This is a separate but connected database the AI accesses to answer questions. It sounds technical, but it’s no harder than managing a shared folder on your desktop or cloud platform.

The benefit of working with RAGs is that you can improve the quality of information the AI pulls from and tweak how it responds. So, if you’re going through chat logs and notice a poor answer, you can find what data the AI used to generate that answer and replace it with something better.

Your bot doesn’t pull answers out of nowhere — it looks them up. The key is to place the best content in its RAG library and test whether it’s finding the right answers when customers ask for help.

Find out how Zoom’s own customer service team is using RAG with Zoom Virtual Agent to achieve a 97% self-service rate. Read the blog.

Customize it to seamlessly escalate interactions

No matter how well you train your AI, there’ll always be cases and situations it can’t resolve. What matters most is how quickly and smoothly it hands over to a human.

If a customer presents a complex or urgent problem to your AI or their words suggest they’re feeling emotional, make it easy for them to connect to a live agent.

Set escalation rules for signals like repeated questions, emotional language, or sentiment, and issues that AI fails to resolve after a set number of replies. Build your bot to act on these signals and program it to let customers know human help is on its way.

Pull actionable data from your self-service solution

AI self-service tools improve the customer experience and provide valuable data that can influence other areas of your business. By analyzing interactions with your AI self-service tool, you can gather insights to make more informed decisions across various departments.

For example, customer care teams can monitor AI interactions to spot common issues or areas where customers need additional support. This data helps refine training, improve service delivery, and enhance the quality of responses. 

Beyond customer support, your product teams can use AI insights to pinpoint feature gaps or recurring requests, guiding future product development. By integrating these actionable insights across teams, businesses can align their strategies with real customer needs for a more customer-centric approach.

Check out how Cricut is upleveling the service they provide and even improving their products with insights from Zoom Virtual Agent.

A recent Morning Consult research report, commissioned by Zoom, shows 80% of those who have had past success using AI chatbots or voice bots say that they always, often, or sometimes prefer support that doesn’t involve a human. Train your bot with the right data and build in the right escalation paths to turn your AI self-service tools into a fundamental, strategic channel for your business.

Zoom Virtual Agent, part of our Zoom CX solution, takes CX to the next level. It’s an agentic AI powerhouse that has autonomous, proactive conversations with customers to drive end-to-end resolution.

Learn how you can incorporate AI self-service into your own virtual call center solution. Learn more and ask for a personalized demo to see the system in action.