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A guide to virtual agents for dummies

by uma

By: Sanjeev Kumar, VP EMEA at Boost.ai 

What are virtual agents? How do they work? 

Virtual agents have become more popular across industries as businesses start to understand the benefits that these digital assistants provide. Butwhat exactly is a virtual agent?

And, no, a virtual agent isn’t a computer-based, martini-drinking British spy. It is an intelligent AI solution that uses natural language processing (NLP) to understand user intent and search inquiries. Virtual agents assist businesses by acting as a substitution for human interaction, providing a digital interface as a first line of support for customer service inquiries and undertaking time-intensive tasks to free up employees’ time for more complicated customer requests. 

What’s the difference between a virtual agent and a chatbot? 

On the surface, not too much – those terms can often be interchangeable. You might see virtual agents described as chatbots, conversational agents or intelligent assistants. They all refer to the same building block software, and both can help businesses streamline customer service processes and improve employee experiences. The critical difference is what powers the solution – is it rules-based with a predefined workflow, or is it conversational AI-driven with much broader engagement applications? 

How do virtual agents work? 

The best conversational agents are imperceptibly virtual. These virtual agents respond to customers as human agents might, resolving their queries by providing relevant information in a friendly, efficient manner. 

Of course, digital assistants have existed for some time, but what makes virtual agents different to the traditional “chatbot” is the introduction of conversational AI. Powered by various language understanding algorithms, conversational AI elevates a simple chatbot into a powerful, intelligent, and reflective tool that can resolve many customer inquiries and which is continuously learning and evolving to give better and more accurate responses. 

Unlike rule-based chatbots, virtual agents powered by conversational AI analyse text inputs to process customer requests. They use Natural Language Understanding (NLU) technology to identify user intent and extract other important information from a request. More advanced conversational AI technology leverages proprietary deep learning models (such as boost.ai’s own Automatic Semantic Understanding) to improve a virtual agent’s capacity to understand human language better and further reduce the chance of misunderstanding user intent.

Once the input has been through these processes – all in milliseconds – the agent can formulate the response. Here, personalisation is vital. By combining all the information gathered with a structured hierarchy of conversational flows, a virtual agent can respond appropriately in a conversational manner.

What can virtual agents actually do?

Virtual agents can undertake several functions to support customer service, such as password recovery, account questions, sales recommendations, and solving various customer problems. Importantly, they can operate 24/7, answer questions instantly, and, unlike humans, they don’t ever get tired, resulting in significantly increased support capacity. 

As mentioned, the key to a successful virtual agent is that it can interact with customers in a flowing conversation. Simultaneously, they can identify multiple intents from one request and provide quick and accurate answers to all inquiries. They can also understand the context of a question, ensuring interactions are focused and to the point whilst asking clarifying and follow-up questions to gather actionable data. 

However, virtual agents are only as intelligent and capable as the humans behind them. The best way to maximise their efficiency is to ensure they are well-maintained and refined. 

Are virtual agents going to steal my job?

A common concern with AI is whether people will lose their jobs to robots. Instead, rather than take jobs away, virtual agents can be seen more as a tool to relieve pressure on workers,  giving them time to do more valuable tasks that better utilise their training and expertise.

Moreover, this technology opens up opportunities for new roles in organisations in training conversational AI, ensuring that the solution is well-maintained and regularly updated. New roles in designing conversational AI can also be created for different industries, with developers creating new AI solutions for internal information directories, handling real-estate inquiries and even aiding in healthcare diagnosis.

What does the future hold for conversational AI and virtual agents?

As the technology and its applications become more widespread, the potential of conversational AI to improve customer service and internal support for businesses is far-reaching. The more time a conversational AI-powered virtual agent spends embedded in an organisation, the more it learns, improves and provides value to both customers and employees. Similarly, the more real-world data conversational AI gains, the more it can be optimised and improved, enabling virtual agents to respond to queries faster and more accurately, enabling the automation of a broader range of more complex tasks

In the not-too-distant future, virtual agents may act as a critical piece in a hybrid system in which both humans and machines work together in synergy to provide a seamless customer experience, whether through chat or voice, with conversational AI at the centre driving every interaction. 

 

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