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What Is a Virtual Agent?
Virtual agents are evolving, and helping companies build better connections with customers. Here’s how they work.
Justin Lafferty, Senior Editor
Virtual agents are evolving, and helping companies build better connections with customers. Here’s how they work.
Justin Lafferty, Senior Editor
Until now, virtual agents have felt more like a hassle for customers to deal with, versus talking with a person. They’ve been limited in their knowledge, unhelpful in their responses, and have often frustrated people into giving up and screaming “REPRESENTATIVE” into the phone. But that’s changing. With the introduction of agentic AI, virtual agents can now provide the support that customers expect — and some can even improve over time.
We’ve moved beyond the days of basic chatbots replying to customer inquiries with information that someone could probably just find on their own. Now, virtual agents can use your trusted customer data to deliver personalized, helpful responses that don’t feel robotic and detached.
Simple chatbots might not be able to tell you the status of your order, but virtual agents can autonomously let you know your order is on its way, giving you a tracking number and updates.
So what can these kinds of AI-powered agents do for your business? We’ll define what a virtual agent is, the benefits they provide, and go through some great use cases.
A virtual agent is a program that uses artificial intelligence (AI) to answer questions and deliver updates in a conversational manner, as well as automate processes. Virtual agents include chatbots, copilots, and autonomous agents. They’re often used to reply to simple customer questions, handle routine tasks, and automate work that would take much longer for humans to do manually.
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While virtual agents might make it seem like there’s someone on the other side of the screen, answering questions immediately, it’s really the work of natural language processing (NLP) and AI working in a conversational user interface.
Some virtual agents (like chatbots) could use predefined rules, but some might have more sophisticated reasoning, powered by large language models (LLMs). They’re AI-powered software applications designed to interact with people, typically providing customer service or support.
Virtual agents can automate basic support interactions, like offering store hours or populating answers from your help center, helping your human agents not get bogged down with simple requests. They can provide a summary of service requests, triage problems, and send more complex issues to your customer support team.
Here’s a look at how a few major versions of virtual agents work:
Chatbots, some of the most common virtual agents, use a decision tree flow to provide answers. This usually comes in the form of having the customer select from a series of pre-determined options, instead of asking questions in their own words. While this is great for simple information, it doesn’t help when someone has more than a basic question.
However, more modern AI chatbots use LLMs instead of a decision tree flow, allowing them to give more detailed and relevant answers. There are many differences between AI agents and chatbots. One is the way in which chatbots rely on pre-scripted responses to handle basic queries, while AI agents use advanced intelligence to offer personalized, adaptive support for more complex needs.
Digital assistants enhance customer experiences by providing instant, personalized support across channels. Powered by AI, they understand natural language, anticipate needs, and deliver solutions in real time, ensuring seamless interactions day or night.
Unlike traditional chatbots, digital assistants are dynamic and context-aware. They can handle complex workflows, integrate with backend systems, and continuously improve through machine learning, making them a smarter, more effective solution for modern businesses.
Copilots are the next level up, in terms of complexity, from chatbots. Whereas chatbots can handle simple questions, a copilot is more of an intelligent assistant. Copilots can learn from interactions and become more helpful over time. Instead of just reacting to queries, an AI copilot can proactively suggest actions, provide insights, and even automate tasks.
AI copilots often integrate with other systems and can analyze data to provide insights and make predictions, going beyond the simple question-and-answer format of chatbots. For this reason, copilots tend to be more of an internal tool used by employees of a company, rather than a technology customers would interact with.
Autonomous agents, the newest type of virtual agents, do the work of chatbots and copilots — but without human intervention. They pull company data from different places, like customer conversations, past transactions, and external databases.
Using machine learning algorithms, they analyze this data to find patterns and predict what's likely to happen. They use these insights to make decisions that align with the goals you’ve set, autonomously helping you and your team to better focus on your customers.
Once a decision is made, autonomous agents carry out the required actions. With each cycle, they keep updating their knowledge base and improving their decision-making algorithms to perform better over time.
Want to try it for yourself? At the bottom of your screen, you can interact with Agentforce, the agentic layer of the Salesforce platform.
Virtual agents and AI agents might seem like interchangeable terms, but they work differently. Virtual agents are tools that simulate human interactions, whereas AI agents are a broader category of programs and applications that perceive an environment, make decisions, and act autonomously to achieve goals.
A virtual agent is typically rule-based and follows pre-defined scripts or workflows. It can handle simple, predictable tasks and provide canned responses based on specific keywords or inputs. They are great for straightforward customer service tasks, like answering FAQs or guiding users through basic processes. However, they often struggle with complex or nuanced queries and don't learn or improve over time.
In comparison, AI agents use LLMs to understand context, make decisions, and escalate more complex issues to human agents.
Some virtual agents (such as chatbots) could use pre-defined rules, but some might also have more sophisticated reasoning via LLMs. In this case, a virtual agent can use an LLM to power its NLP capabilities, but may not be able to take action autonomously. For example, it may be able to serve up the link to a request form to update an order, but would not be able to update the order autonomously.
An AI agent could be customer-facing, but ultimately they’re performing tasks on the customers behalf without their input or interference. AI agents can learn over time and become more helpful.
For instance, virtual agents can help your service team reply to customer questions around the clock. With Agentforce, virtual agents use a company’s trusted customer data to resolve cases and offer a personalized experience, making it feel much less robotic.
Virtual agents can also offer a boost to your sales reps. Agentforce Sales Development Representatives autonomously answer product questions, handle customer objections, and book meetings for sales reps. All responses are grounded in customer data, so each interaction feels tailored to the customer, not a cookie-cutter conversation. You’re able to decide how often, on which channels, and when virtual agents engage customers before handing cases off to your sales reps.
Get inspired by these out-of-the-box and custom AI use cases.
Chatbots manage customer interactions through a decision tree flow, with pre-selected options, while virtual agents can go beyond pre-written answers and learn more about the context behind the request. Unlike chatbots, virtual agents can learn over time and adapt to your needs and preferences.
Think of a virtual agent as somewhere between chatbots and AI agents, or autonomous agents. However, more modern chatbots can also use LLMs instead of decision tree-style programming, allowing for greater flexibility and more relevant answers.
While the end user might see virtual agents in the form of chatbots or AI agents, under the hood, there are a few different types of virtual agents to know about. Here’s a look at how they differ.
End-to-end solutions are the complete package for companies, offering help from setup through integration and beyond. Providers of end-to-end solution virtual agents guide you through setup and maintenance, as well as integration into the applications and workflows your teams use every day.
Looking for a simpler entry into the world of virtual agents? SaaS platforms now offer virtual agents with low-code and no-code solutions, making it easier than ever for businesses to implement and manage. These tools are designed for companies that lack the technical staff or resources to dedicate to building and maintaining this technology, providing an accessible way to enhance customer support.
Virtual agents also take the form of scalable pro-development tools, for companies that don’t need the full gamut of support. These platforms are great for companies who already have that kind of support system in place, with developers who can manage implementation.
There are also virtual agent platforms that complement your current tech stack, working best with what you’ve got now. This could be a chatbot or AI agent directly built into the customer relationship management (CRM) software your team uses every day.
More and more companies are turning to virtual agents to help boost employee activity. We’ve found that virtual agents (such as Agentforce) are paying off big for companies, with virtual agents working as a complement to their employees. Brands using this technology are seeing return on investment as high as 213%, showing that virtual agents can help take your business to the next level.
What are some of the key benefits of using virtual agents?
Virtual agents working with your staff allow your company to get more done, and place the focus where it belongs: on your customers.
Here’s a look at a few key features of virtual agents that can help your business:
See how you can create and deploy assistive AI experiences to solve issues faster and work smarter.
Now that you know more about what virtual agents are, and what they do, let’s take a look at how they can help specific teams across your company.
While virtual agents can help your sales reps move leads down the pipeline faster, they can also help your staff improve their skills. For instance, with Agentforce, your reps can practice pitching, handling objections, and negotiating. Agentforce offers realistic scenarios tailored to different types of deals, individual employee goals, and your business strategies.
It’s like putting in practice before game day. You’ll get consistent, accurate feedback on seller strengths and areas for improvement, as well as clear steps they can take to advance deals.
With Agentforce helping your service team, you can engage customers on any channel, at any time. Before, if a customer service inquiry came in overnight, the customer would have to wait until your business opened the next morning.
Now, virtual agents can handle those questions and set your service reps up for success. You can get a virtual agent up and running in minutes with prebuilt templates, or customize it quickly with low-code tools.
Agentforce can help make life easier for your commerce team by providing shoppers with personalized product recommendations. While not everyone can afford a real-life personal shopper, your virtual agent can make customers feel like VIPs.
With conversations directly on your commerce site or the customer’s preferred messaging app (like WhatsApp), virtual agents can help shoppers find products and make purchases faster.
Your marketing budget can go further with Agentforce, which can create and optimize campaigns from start to finish. Virtual agents can build tailored, relevant campaigns for your customers based on their preferences and history.
With Agentforce, marketers can use virtual agents to help generate campaign briefs, audience segments, and customer journeys. Virtual agents can also use generative AI to create relevant content for your audience and continually analyze performance against your key performance indicators — so they can proactively make recommendations.
Virtual agents can offer a much-needed boost to your employees and your business. Instead of having them bogged down with low-value tasks, Agentforce provides better, more personalized care for your customers and makes your company more efficient.
Agentforce helps companies respond to inquiries around the clock, and around the globe. Instead of relying on basic chatbots that feel dated and unhelpful, you can use this AI-powered technology to get closer to your customers and deliver the service they’ve come to expect.
Justin Lafferty is a writer and editor based in Las Vegas, currently coaching writers as a Senior Editor at Salesforce. He's contributed to Adweek, the Las Vegas Review-Journal, the San Diego Union-Tribune, the East Bay Times, and many more outlets.
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