Faster and Easier Customer Self-Service

An Intelligent Virtual Assistant is an AI-driven software agent that uses natural language processing (NLP) and natural language understanding (NLU) models to interact with customers in a human-like manner. It can answer questions and help users 24/7 through chat or voice, providing instant support without waiting for a live agent. By handling routine inquiries and tasks – often with generative AI and agentic AI — an IVA delivers faster resolutions and consistent service, which improves customer satisfaction while allowing human agents to focus on more complex issues.

The difference between an IVA and a simple chatbot comes down to sophistication and flexibility. Basic chatbots often follow preset scripts and only respond to specific keywords, which means they can fail if a customer’s question isn’t accurately phrased. An AI-powered virtual assistant, by contrast, understands context and intent using machine learning and NLP. It can handle complex, multi-step conversations – asking clarifying questions, offering personalized answers, and even gathering info to seamlessly hand off to a live agent if needed. An advanced intelligent virtual assistant can also use generative AI to find information from a range of approved knowledge sources. In short, IVAs are more conversational and capable than traditional rule-based chatbots.

IVAs greatly enhance the customer experience by providing fast, convenient self-service. They are available 24/7, so customers can get help any time without waiting on hold. This immediacy reduces frustration – in fact, 84% of consumers prefer to do business with companies that offer easy self-service support. A well-designed IVA can greet users by name, remember context from prior interactions, and give consistent answers, all of which boosts customer satisfaction and loyalty. IVAs often go far beyond just providing answers, though. Today’s IVAs can provide actionable resolutions for a customer, like scheduling an appointment, checking a bank account balance, or requesting insurance documents, for example. By resolving issues quickly on the first contact, virtual assistants create a low-effort experience that today’s customers appreciate.

Yes – a major advantage of intelligent virtual assistants is their ability to offload routine work from contact center agents. By automating frequently asked questions and simple tasks, IVAs can contain a large portion of interactions that would otherwise go to agents. (Many organizations report containment rates ranging from 30% up to 80+% with a good IVA.) This means lower call/chat volumes for your team, shorter queues, and ultimately reduced operational costs. For example, companies using Verint’s IVA have automated millions of customer interactions – one saved about $10 million by handling inquiries with AI instead of live staff. Additionally, by handling tier-1 issues, the IVA frees human agents to spend time on higher-value or complex customer needs, improving overall efficiency.

Implementing an IVA is easier than many expect. Modern AI virtual assistant platforms offer quick deployment options and integration tools. For instance, Verint’s IVA can be deployed alongside your existing IVR system – you don’t need to “rip and replace” anything. Many companies start with a small use-case (like one call flow or a few common chatbot intents) and can go live in around a month. Because today’s IVAs often come with low-code design interfaces and pre-built components, you can gradually expand automation at your own pace. In short, you can add an IVA to your customer service stack with minimal disruption and see results quickly. Today’s intelligent virtual assistants also can easily plug into third-party large language models (LLMs) for optimal performance.

A good IVA is smart about its limits. It will attempt to understand the customer’s request using AI and even ask follow-up questions if needed. If the query is too complex or outside its scope (for example, a sensitive account issue), the IVA will automatically escalate to a human agent. Advanced IVAs ensure a seamless handoff by transferring the conversation context to the agent. This means the customer doesn’t have to repeat information – the agent can see what the virtual assistant and customer discussed. By recognizing when to step back and involving a person at the right time, IVAs make sure customers get accurate help on complicated issues without frustration.

Yes, most customers are open to AI-driven help, especially if it saves them time. Studies show that nearly 80% of consumers would speak with a chatbot or virtual assistant to avoid waiting on hold for an agent. The key is that the virtual assistant must be well-designed to truly help the customer. When an IVA provides quick answers and solves the problem (or seamlessly connects to a person when needed), customers are typically satisfied with the experience. In fact, many people now prefer self-service options for straightforward issues as long as they are easy to use and effective. A properly implemented IVA meets this expectation by delivering speedy support, which in turn improves customer sentiment.

Most cutting-edge IVAs incorporate generative AI and large language models to make responses even more natural and comprehensive. Traditional IVAs already use AI techniques like machine learning and NLP to understand queries; adding generative AI enables them to draw on vast knowledge and produce more fluid answers. For example, with an LLM (Large Language Model) integrated, an IVA can answer more open-ended questions by generating replies based on a huge database of information. This can reduce the need for extensive pre-programmed scripts. However, organizations still train and supervise the AI to ensure responses stay accurate, on-brand, and helpful. In summary, the latest IVAs do leverage generative AI to enhance their capabilities – it’s a growing trend in the quest for more human-like automated assistants.