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virtual agent

What is a virtual agent?

A virtual agent -- sometimes called an intelligent virtual agent, virtual rep or chatbot -- is a software program that uses scripted rules and, increasingly, artificial intelligence (AI) applications to provide automated service or guidance to humans.

Virtual agents are commonly used by organizations in their customer service functions to answer routine customer queries, fulfill standard requests and handle simple problems. For example, virtual agents are often used for initial customer interactions with call centers and click-to-chat features on websites. Virtual agents work well to facilitate customer self-service applications; difficult customer questions or concerns are typically escalated to human representatives.

Virtual agents are also used in some organizations to handle employee-driven needs. For example, IT departments often use them to provide some help desk services, such as answering employee requests for resetting computer passwords. They are also used to guide employees through work tasks and processes.

In this way, virtual agents are akin to digital assistants, which are apps that understand natural language processing (NLP) voice commands and are deployed to fulfill people's needs or help them complete tasks.

Technology research and advisory firm Gartner predicted that, by 2025, 37% of customers will try to use a virtual assistant to interact with a customer service department. Gartner has also predicted that, by that same year, half of all knowledge workers will use a virtual assistant daily, an increase from 2% in 2019.

Virtual agent vs. virtual assistant

The terms virtual agent and virtual assistant are often used interchangeably with each other, as well as with the term chatbot. Although all three are types of computerized aid offered to serve people in various capacities, there are some subtle -- although not definitive or universally accepted -- distinctions among them.

Virtual agent and virtual assistant are more closely aligned terms and, thus, more likely to be used interchangeably. However, many associate the term virtual assistant with Apple's Siri, Amazon's Alexa and Google Assistant. All three platforms draw on the internet and other technologies to perform internet searches and digital tasks, such as updating calendars and checking weather forecasts in response to a user's request. The term virtual agent, on the other hand, is more commonly associated with organizational use, where agents are put to work assisting customers or employees.

List of repeatable tasks virtual agents perform
Virtual agents perform repeatable tasks and deliver 24/7 customer service.

A chatbot is a specific type of virtual agent -- a conversational agent -- with capabilities to chat via email, messaging or voice. However, the term chatbot doesn't encompass the wider array of virtual agent capabilities that might also include visual representations, such as holograms, as well as characteristics beyond verbal communication.

The term virtual agent can also refer to a human agent who works remotely from their employer's location to serve customers.

How virtual agents work

Virtual agent technologies initially emerged in the first decade of the 2000s. At the most basic level, virtual agent technologies work on a preprogrammed, scripted model.

Organizations created virtual agents that were scripted to respond in set ways to specific human requests. Organizations identified the particular workflows that the virtual agent would handle, mapping out what the agent should do based on each specific request or inquiry made by a person.

Organizations then created the scripts for the agent to follow when responding to each request. The agent identified a specific type of request based on predetermined keywords that were programmed into the platform. In other words, the virtual agent identified the keywords and responded with the scripted response that, in its computerized analysis, best matched the keywords.

As such, these virtual agents handled routine tasks where a customer inquiry or request could be met with a predictable response. Organizations typically programmed their virtual agents to turn over the customer interactions to human agents when requests hit a certain point in the workflow requiring a handoff or when the inquires digressed from the script.

More recently, virtual agent platforms have incorporated machine learning, NLP and AI technology to create conversational AI. These intelligent virtual agents transcend the limited functionality of traditional chatbots by analyzing human queries and concerns to generate text that mimics human conversations. Conversational AI can process more complex types of queries that have less predictable requests, workflows and responses.

These AI-powered virtual agent platforms can also connect with back-end systems, providing more personalized responses to the customers or employees interacting with the agent systems. Moreover, the capabilities built into these AI chatbots enable them to learn. As a result, they become more efficient and effective as they work, and they develop the capacity to handle a wider range of tasks.

Virtual agent capabilities

As virtual agent software has improved with advances in AI and cognitive computing programs, virtual agents have moved far beyond the early interactive voice response, or IVR, systems. Technological advances have enabled virtual agents to understand customer intent and provide personalized answers to customer questions in a humanlike manner.

However, virtual agents still typically communicate with customers via email or live chat on corporate websites that often include a mobile app version. Companies also use an avatar to provide a visual representation of the virtual agent.

Most companies still use virtual agents to handle highly repeatable tasks. For complicated tasks, live customer service agents are required. In the world of customer relationship management (CRM) software, virtual agents are used to provide 24/7 customer service. They can answer questions on accounts, help with password issues, and follow up on sales and marketing leads via email correspondence.

For example, a virtual sales agent in a CRM application can email potential customers to request a meeting with a live sales agent. When a customer agrees to a meeting, the virtual agent obtains a phone number and collects other information a sales rep might need to conduct a live conversation.

This is useful for sales and marketing teams, as they typically only focus on high-quality leads. With a virtual agent, all leads can be followed up on, which could result in higher sales. In addition, virtual agents cost significantly less than human employees.

How to use a virtual agent

Companies interested in adopting end-to-end virtual agent software through a cloud service provider or software vendor must invest time and resources to train the virtual agent. Training can involve methods such as feeding the agent information from a knowledge base. This initial setup period can take months to complete, depending on the level of confidence the company desires. Virtual agents are based on machine learning technology, which improves over time as the system ingests more data and learns through continued use.

Virtual agents can only provide information that has been fed to the AI system, and if the system contains bad data, customers receive false information. This makes the setup phase critical. The initial time investment is worthwhile when it results in reduced call volume and frees up live agents to focus on complex customer service tasks, while simultaneously providing a good customer experience.

There are a number of cloud-based virtual agent platforms that are pre-trained for customer service tasks. These programs require no coding or machine learning knowledge; instead, users configure the virtual agent to suit their business needs and branding.

For example, IBM's Watsonx Assistant is trained to understand common customer support requests in the many ways customers ask questions. And, as with any software-as-a-service platform, Watson Virtual Agent doesn't require installation, and improvements are added automatically.

Carnegie Mellon professor discusses her work on making bots socially aware.

Virtual agent benefits

Virtual agents can deliver a number of benefits to the organizations that use this technology, including the following capabilities:

  • Round-the-cloud automated service. Customers or employees can get 24/7 answers to basic questions and access to information, tools and forms. Automation enables virtual agents to provide those services quickly and save organizations from having to hire full-time workers.
  • Faster and more consistent responses. Virtual agents answer customer or employee requests and inquiries quickly with the same information every time. They can also be scaled to meet anticipated needs.
  • Better compliance. Virtual agents can be programmed to undertake set actions that ensure regulatory and legal requirements are adhered to.
  • Increased customer satisfaction at a lower cost. The combination of round-the-clock access and faster, more consistent service results in happier customers at a lower cost than hiring full-time employees.
  • Human agents available for challenging tasks. By handling routine and mundane requests, virtual agents free up human agents to focus on the complex tasks that require more skills and critical thinking. This approach ensures human agents are available to handle complex customer interactions and provide real-time responses when needed.

Virtual agent use cases

Industry-specific use cases for virtual agents are broad and attest to their usefulness. Intelligent virtual agents can deliver even more benefits to an organization.

According to research firm Everest Group, these agents help with payment collections, cross-selling, upselling, customer retention and customer acquisition. Everest Group said these additional capabilities can serve specialized needs in various industries, including banking, insurance, healthcare, travel and hospitality, as well as in different organizational functions, such as human resources.

Tasks virtual agents can tackle include the following:

  • Insurance claims. Virtual insurance agents field questions on coverage, policy updates and filing claims. These types of inquiries are often simple enough to avoid escalation to human agents.
  • Order fulfillment and management. Virtual assistants respond quickly to requests regarding order status, delivery dates and related concerns that can be addressed without human involvement.
  • Event scheduling and reservations. This is important in the hospitality industry, where virtual agents can handle routine event planning and reservations.
  • Surveys and customer feedback. Unlike years ago, human-to-human interaction is no longer necessary for collecting customer feedback; virtual agents can conduct surveys and record responses.
  • Troubleshooting and technical support. Virtual agents can guide customers or product end users through routine fixes to technical difficulties. This use frees tech professionals to focus on more complex problems.

Virtual agent examples

Most consumers and many workers today have interacted with a virtual chat agent or agent system. For example, virtual systems are often used to help customers and employees with application and computer passwords.

Similarly, customers who have clicked on a website's messaging interface, such as the chat feature, likely interacted with an agent system. Less successful have been attempts at airports to use hologram virtual agents to respond to passengers' requests for information.

Additionally, tech vendors offer businesses the ability to create their own chatbots tailored to their needs. For example, Microsoft Power Virtual Agents, part of the vendor's Power Platform, lets businesses create apps with the necessary functionality to handle customer and employee queries. In addition, Microsoft's Omnichannel for Customer Service lets businesses consolidate multiple customer communications channels, including virtual ones, within a single interface.

This was last updated in August 2023

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