Virtual Agents vs. AI Agents: Which One Does Your Business Need?

Thinking about using a virtual agent for customer support but unsure where to start? The term is often confused with virtual assistants—human professionals who provide remote admin support, not AI solutions.

Unlike basic chatbots, virtual agents are designed for more than just scripted responses. They can handle customer questions, assist customer service representatives, and scale support without increasing headcount. But what exactly makes them different from AI agents? And how do they fit into a broader automation strategy?

Let’s take a closer look.

What is a Virtual Agent?

A virtual agent is an AI-powered conversational assistant designed to handle customer and employee interactions. Unlike basic chatbots, virtual agents use natural language processing (NLP) to understand, interpret, and respond to customer questions in a way that feels more human-like.

Key characteristics of virtual agents:

• Context awareness – They remember previous interactions within a conversation.
• Conversational AI – They generate responses dynamically rather than relying on scripted replies.
• Integration with systems – They connect with knowledge bases, contact center software, and other business tools.

By using machine learning, an intelligent virtual agent improves over time, learning from interactions to provide more relevant responses and better customer satisfaction.

How Virtual Agents Work

A virtual agent platform follows a structured process to understand and respond to users:

1. Processes user input – Uses natural language processing to analyze text or voice queries.
2. Searches for relevant data – Pulls information from a knowledge base, FAQs, or connected business systems.
3. Generates a response – Uses AI-driven recommendations to provide real-time answers.

While virtual agents handle structured interactions and assist with automation, some businesses require a more advanced AI solution that goes beyond scripted workflows. This is where AI agents come in.

Virtual Agent vs. AI Agent

Both virtual agents and AI agents enhance automation, but their capabilities and use cases differ. Virtual agents focus on structured conversations and customer support, while AI agents operate autonomously and adapt to real-time data without predefined workflows.

How AI Agents Differ from Virtual Agents

Unlike virtual agents, AI agents function with decision-making autonomy. They analyze data, adapt dynamically, and execute tasks without requiring constant human oversight.

• Autonomous Decision-Making – AI agents don’t just provide answers; they assess situations and take appropriate actions.
• Proactive Problem-Solving – Instead of waiting for a request, AI agents predict issues and resolve them before escalation.
• Multi-Tasking Capabilities – AI agents handle multiple tasks simultaneously, integrating across systems beyond customer support.

When to Use AI Agents

AI agents are ideal for businesses that need:

• Advanced workflow automation that goes beyond scripted responses.
• Real-time adaptability to changing conditions, such as fraud detection or supply chain optimization.
• Cross-functional integration where artificial intelligence can streamline operations across multiple business areas.

Understanding these distinctions helps businesses determine whether a virtual agent, an AI agent, or a combination of both is the best fit for their automation strategy.

Key Benefits of Virtual Agents for Businesses

Virtual agents automate customer interactions, reduce operational costs, and improve customer satisfaction. By handling high volumes of inquiries, they free up human agents to focus on more complex issues.

1. Customer Service Automation

Virtual agents can automate routine tasks to enable customer service representatives to concentrate on more complex interactions.

• Reduces wait times – Customers receive immediate responses, eliminating the need to wait for a live agent.
• Provides 24/7 support – Ensures customers have access to assistance at any time.
• Handles high volumes – Capable of managing numerous inquiries simultaneously beyond human capacity.

For example, Filipino airline Cebu Pacific Air introduced "Charlie," a virtual assistant available 24/7 via their website and Facebook page. Charlie assists with pre-flight queries, bookings, check-ins, and provides information on ancillary services.

2. Cost Efficiency

Implementing virtual agents can lead to significant cost savings by decreasing reliance on large contact center teams.

• Deflects repetitive inquiries – Reduces the volume of inbound calls and chats.
• Cuts training costs – Minimizes the need for continuous training of new customer service agents.
• Improves resource allocation – Allows human agents to focus on more complex support cases.

For example, during the COVID-19 pandemic, the Illinois Department of Employment Security (IDES) deployed a virtual agent to handle 140,000+ inquiries daily. This saved an estimated $100 million in staffing costs while maintaining a 94% accuracy rate.

3. Improved Customer Satisfaction

Virtual agents enhance customer experience by delivering consistent, accurate, and prompt responses.

• Personalized interactions – AI-powered virtual agents tailor responses based on customer history.
• Fewer errors – Ensures consistent and accurate responses across all interactions.
• Omnichannel support – Integrates across chat, email, and phone systems for seamless assistance.

For example, Bank of America's virtual assistant, Erica, has handled over 2 billion interactions across 42 million clients. It provides balance inquiries, bill payments, and personalized financial advice. Erica’s automation capabilities helped boost Bank of America's earnings by 19%, while also improving customer engagement and reducing wait times.

4. Scalability

Virtual agents can adapt to business growth without the need for additional hiring or training.

• Manages peak demand – Efficiently handles surges during events or seasonal spikes.
• Supports multiple languages – Expands reach to a global customer base.
• Seamlessly integrates – Fits into existing systems and workflows easily.

For example, Nordea, a leading Nordic bank, implemented a comprehensive conversational AI strategy across four markets. They deployed 12 virtual agents that achieved over 90% resolution rates for customer inquiries. This approach allowed Nordea to manage thousands of daily customer service requests without a corresponding increase in human agents. 

Should Your Business Implement a Virtual Agent?

Deploying a virtual agent can transform customer service operations, but businesses need to evaluate their specific needs, infrastructure, and ROI before making the investment.

Guiding Questions for Decision-Makers

Before implementing a virtual agent, decision-makers should assess:

• What are the cost implications, and does the potential ROI justify the investment?
• Do we have the internal resources and expertise to deploy and maintain a virtual agent?
• How will a virtual agent impact our current customer service team?
• Will a virtual agent provide a competitive advantage in our industry?
• How seamlessly can a virtual agent solution integrate with our existing technology and workflows?

Industries Benefiting from Virtual Agents

Many industries use virtual agent software to improve customer interactions and automate key processes.

• Retail & E-commerce – H&M’s Virtual Assistant helps customers browse products, check availability, and get styling recommendations.
• Healthcare – Mayo Clinic’s Chatbot assists patients with appointment scheduling, symptom checking, and general health inquiries.
• Banking & Finance – Bank of America's Erica automates balance inquiries, bill payments, and account alerts.
• IT & HR – Unilever’s HR Virtual Assistant helps employees access company policies, request leave, and complete administrative tasks.

Choosing Between Virtual Agents and AI Agents

Virtual agents are ideal for handling structured conversations, automating routine tasks, and supporting customer service teams. However, businesses with more complex needs may require AI agents, which operate autonomously and adapt to real-time data.

When to Choose an AI Agent

While virtual agents follow predefined workflows, AI agents analyze patterns, make independent decisions, and optimize business processes without human intervention. Consider an AI agent if your business needs:

• Autonomous decision-making – AI agents assess situations and act without human oversight.
• Proactive problem-solving – They detect and resolve issues before they escalate.
• Cross-functional integration – AI agents optimize workflows across departments, not just customer support.

For example, a banking virtual agent may assist customers with basic inquiries, while an AI agent proactively detects fraudulent transactions and takes preventive action.

Blended Approach: Best of Both Worlds

Many enterprises combine virtual agents and AI agents to create a seamless automation strategy:

• Virtual agents handle customer questions, routine service requests, and scripted interactions.
• AI agents analyze trends, make decisions in real time, and automate complex workflows.

As businesses scale, AI-driven automation continues to evolve. Agentic AI, the next stage of AI automation, will allow systems to not only execute tasks but also learn, adapt, and optimize business processes with minimal human input.

FAQ: Everything Business Leaders Need to Know About Virtual Agents

Still have questions about virtual agents? Here’s what business leaders frequently ask.

What is an example of a virtual agent?

A virtual agent is an AI-powered tool that interacts with customers in real time. For example, Bank of America’s Erica assists users with balance inquiries, bill payments, and personalized financial insights.

What is the difference between a virtual agent and a live agent?

A virtual agent automates routine tasks like FAQs and appointment scheduling, while a live agent handles complex, high-value interactions requiring human judgment.

What is the difference between a virtual agent and an AI agent?

A virtual agent follows structured workflows and predefined responses, whereas an AI agent adapts dynamically, making autonomous decisions based on real-time data and context.

TL;DR

Virtual agents streamline support, cut costs, and improve customer experience. By handling routine tasks, they free up human agents to focus on complex issues while ensuring faster, more consistent service.

However, as businesses scale, AI agents offer a more advanced approach—bringing decision-making autonomy, real-time adaptability, and proactive automation. Looking ahead, agentic AI will push automation even further to allow businesses to optimize workflows without human intervention.

Want to see AI agents in action? Book a demo with Arcee AI today!