Chatbot vs Virtual Agent

What Are Chatbots and Virtual Agents?

A chatbot is a software program that conducts text-based conversations with users, typically following scripted flows or basic NLP. A virtual agent (also called an AI Agent) is an autonomous system that can perceive context, reason across data sources, take actions, and resolve multi-step customer issues end to end. The difference is not just capability. It is architectural. Virtual agents are built to complete tasks, while chatbots are built to carry conversations.

Key Differences Between Chatbots and Virtual Agents

Chatbots respond to what a customer says. Virtual agents understand what a customer needs and take action to deliver it. A chatbot might tell a customer their refund policy. A virtual agent will look up the order, verify eligibility, process the refund, and confirm completion, all within a single conversation.

This distinction aligns with the industry shift toward agentic AI, where AI systems move beyond responding to actively resolving. Virtual agents connect to backend systems, CRMs, order management tools, and ticketing platforms through APIs, giving them the ability to act rather than just inform.

Why the Distinction Matters

The gap between chatbots and virtual agents has significant business impact. Chatbots typically resolve 10-30% of inquiries (often measured as deflection), while virtual agents can achieve 70-93% true resolution. For teams managing high support volume, this difference translates directly into lower cost per ticket and higher CSAT.

Gartner predicts that by 2029, agentic AI will autonomously resolve 80% of common customer service issues, cutting operational costs by roughly 30%. (Gartner, 2025)

As customer expectations rise and support volumes grow, the chatbot model is reaching its limits. Organizations that invest in virtual agent capabilities see measurably better outcomes across resolution rate, handle time, and customer satisfaction.

Chatbot vs. Virtual Agent Comparison

Core function

• Chatbot: Carries conversations
• Virtual Agent: Resolves tasks end to end

Autonomy

• Chatbot: Reactive, waits for input
• Virtual Agent: Proactive, plans and executes steps

System access

• Chatbot: Limited or none
• Virtual Agent: Connects to CRMs, APIs, databases

Learning

• Chatbot: Static or basic ML
• Virtual Agent: Continuously improves from interactions

Channel support

• Chatbot: Typically web chat
• Virtual Agent: Omnichannel: chat, voice, email, SMS

Escalation

• Chatbot: Basic handoff
• Virtual Agent: Context-rich AI escalation with full history

Resolution rate

• Chatbot: 10-30% deflection
• Virtual Agent: 80-93% true resolution

The Maven AGI Advantage

Maven AGI is purpose-built as a virtual agent platform, not a chatbot with upgrades. The platform's AI Agents reason across your entire knowledge ecosystem, execute multi-step workflows through 100+ integrations, and deliver true resolution rather than deflection.

Enumerate achieves a 91% resolution rate with Maven AGI. Roo reduced ticket volume by 50% after deploying Maven's virtual agent across its contact center.

With conversational AI that truly understands context, plus enterprise compliance (SOC 2 Type II, HIPAA), Maven AGI gives teams a virtual agent that is ready for production, not just a demo. Explore the broader comparison in our AI Chatbot vs. AI Agent glossary entry. (McKinsey: The future of CX with agentic AI)

Frequently Asked Questions

Is a virtual agent the same as an AI Agent?

The terms are closely related. "Virtual agent" has been used for years to describe advanced automated support systems. "AI Agent" reflects the latest generation of agentic AI that can reason, plan, and take action autonomously. Maven AGI's AI Agents represent this newer, more capable category.

When is a chatbot sufficient?

A basic chatbot may be sufficient for very low-volume, single-topic use cases, such as directing visitors to the right page or collecting contact information. If your customers ask diverse questions, expect quick answers, or need actions taken on their behalf, a virtual agent is the better investment.

What should you look for in a virtual agent platform?

Prioritize true resolution rate (not deflection), breadth of integrations, deployment speed, knowledge base connectivity, escalation quality, and enterprise security. The platform should also provide analytics so you can measure support ROI and continuously improve.

Related Terms