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AI Agents vs. Chatbots in 2025: What’s the Difference?

AI Agents vs. Chatbots in 2025: What’s the Difference?

Flo Crivello
CEO
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Lindy Drope
Written by
Lindy Drope
Founding GTM at Lindy
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Flo Crivello
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Last updated:
October 3, 2025
Expert Verified

Chatbots handle conversations, while AI agents can pursue goals on their own. 

Chatbots in 2025 are more advanced than they were a few years ago. They now use AI to answer tougher questions, manage simple transactions, and even hand off complex issues to humans. 

Yet, AI agents are more advanced. They can plan, reason, remember, and execute multi-step workflows on their own. You tell an AI agent its goal, and it will work to accomplish that goal with little to no intervention.

If you’re considering AI agents vs. chatbots, we’ll break down the differences so you can choose the option that best matches your workflows, budget, and goals. We’ll cover the following:

  • Definitions of a chatbot and an AI agent
  • Differences between them 
  • When to use chatbots and when to use AI agents
  • 3 real-world use cases
  • How to pick between the two
  • Why more companies are opting for AI agents

What is a chatbot?

A chatbot is software that interacts with users through text or voice. In the past, chatbots used scripts or rules to reply automatically to user input. Today, however, many chatbots use AI and natural language processing to understand context and generate more conversational responses, making them more powerful than previous chatbots.

However, some developers still program chatbots with simple scripts, so not all chatbots are AI chatbots.

For example, a scripted chatbot on an e-commerce site might only recognize exact phrases like “blue compression shirt” and return a fixed link to that product. However, an AI chatbot could understand broader requests, such as “I need workout gear in blue for running,” and it can suggest relevant options even if the user doesn’t phrase it perfectly.

What is an AI agent?

An AI agent is software that acts autonomously and can plan tasks, apply reasoning, store data, and accomplish goals. It adapts to new inputs and executes multi-step workflows.

For instance, an AI agent could help a customer plan a vacation by comparing flight and hotel prices from multiple websites, suggesting local activities, and adjusting recommendations instantly based on budget changes.

What is the difference between AI agents vs. chatbots?

The difference between an AI agent and a chatbot is that an AI agent operates independently to achieve goals, while a chatbot typically responds to user prompts and may handle limited tasks.

Characteristic Chatbots AI agents
Intelligence Follow scripts or basic commands; advanced ones use AI for better replies Learn from data, adapt responses, and act on their own
Autonomy Complete a single request, like providing store hours Complete multi-step tasks, like checking stock, placing orders, and sending updates
Context-awareness Treat each chat as new, with no memory of past interactions Remember past chats to reference details and tailor future responses
Integrations Limited to basic info retrieval or form submissions Connect with CRMs, payment systems, and scheduling tools to complete actions

In an AI virtual agent vs. chatbot comparison, the AI agent can process a refund across integrated systems, while a basic chatbot can only provide a link to refund instructions.

These functionalities show the differences between chatbots vs. conversational agents with AI:

  • Intelligence: Even the chatbots that use AI offer limited responses and can only execute simple support tasks. AI agents learn from data, adapt their responses based on past interactions, and take autonomous action to achieve predetermined goals.
  • Autonomy: A chatbot doesn’t act on its own and needs manual intervention to operate. Users must prompt it to get a response. AI agents act independently to achieve objectives without any manual user intervention.
  • Context-awareness: Developers can program AI chatbots to reference past conversations from a database. But they don’t use memory to pursue new goals; they only respond to user input or perform simple tasks. AI agents use persistent memory to recall past discussions and autonomously adjust actions to meet set objectives. 
  • Integrations: AI agents connect with software CRMs, payment processors, and scheduling systems to complete actions directly. Chatbots often have limited integration capabilities, restricting them to basic information retrieval or form submissions.

For example, a chatbot can answer a customer’s question about a store’s return policy by sending a link to the policy page. An AI agent can process the return request, generate a shipping label, update the inventory system, and notify the customer when the refund is complete.

When to use chatbots

Chatbots still work well in situations where they respond to user-based prompts or questions. To illustrate, a retail chatbot can provide store hours or explain return policies. With the right integrations, some chatbots can even securely process payments.

Chatbots excel in these use cases:

  • Simple, repeatable customer support: Chatbots handle high-volume support questions. Telecom companies often use chatbots to guide customers through bill payment or plan upgrades without sending the inquiry to a human agent.
  • FAQ automation: Customer service chatbots deliver instant answers to frequently asked questions. Airline chatbots can respond to questions about baggage allowance details, check-in times, or seating rules.
  • Website conversion flows: Web chatbots guide visitors toward completing a specific action on a website. An e-commerce chatbot can respond to user queries about products, add products to their carts, and process payments.
  • Appointment scheduling: Scheduling chatbots manage appointment bookings for service-based businesses. A salon chatbot can show available time slots when asked, take a booking, and send an automated confirmation message to the customer.

When to use AI agents

Choose AI agents if you need to automate tasks that involve context, decisions, and multiple actions. Banks employ virtual agents to approve loan applications, verify customer documents, update internal systems, and send confirmations without human involvement.

Businesses employ AI agents and different AI chatbots for these workflows: 

  • Workflow automation: AI agents handle repetitive, multi-step workflows that span systems and applications. Healthcare organizations use AI agents to schedule appointments, route cases, and update records without manual handoffs.
  • Sales/research assistance: Sales agents support sales teams by gathering lead information, qualifying prospects, and tracking interactions across platforms. A B2B sales agent can compile market research, identify key decision-makers, and draft tailored outreach messages.
  • Creative or strategic co-piloting: To aid innovation, AI agents can brainstorm ideas, draft content, or refine strategies. A marketing agent can analyze campaign data and recommend adjustments that align with brand goals.
  • Customer issue resolution: AI agents resolve complex customer issues that require pulling data from multiple sources. In banking, AI agents can verify account details, detect fraudulent transactions, reverse charges, and notify the customer once the case is closed.

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AI agent vs chatbot: Real-world examples

AI agents and chatbots can perform similar tasks, but they operate differently. For instance, both can handle sales outreach workflows, customer support, and content creation. However, AI agents act on their own while chatbots need a human trigger. Let’s find out some top ways to use these tools for business in 2025:

Sales outreach workflows

Chatbots can respond to human-written sales messages through WhatsApp, website embeds, or email. But leads must engage them first by asking questions. Aside from saying “welcome to our site, let me know if you have any questions,” chatbots don’t initiate conversations with leads on their own.

AI agents autonomously identify potential leads from CRM or external sources, qualify them based on set criteria, draft personalized outreach messages, and follow up automatically. Sales outreach agents then schedule meetings and log interactions in the CRM. 

They don’t need interaction or prompting from humans to execute these tasks. If their goal is to find, contact, and set up sales meetings with leads, they’ll get to work immediately.

The verdict: AI agents outperform chatbots in sales outreach because they combine personalization, automation, and decision-making in one workflow. By executing multiple tasks simultaneously, AI agents reduce human intervention, freeing up time for agents to develop relationships.

Customer support on a website

Chatbots answer questions and share details like store hours, return policies, or order status updates. AI chatbots reference past cases when integrated with a CRM or database. They can adapt responses and manage advanced tasks when connected to business systems.

AI agents surpass chatbots in customer support because they act proactively. They contact customers by email, phone, or text when they detect account issues. For example, an AI agent detects an expiring credit card and sends a reminder before payment fails.

The verdict: AI chatbots answer customer questions and handle routine support. AI agents go further by detecting issues like payment failures or service interruptions and resolving them autonomously. Chatbots react to customer engagement, while AI agents anticipate and act without prompts. 

Content creation workflows

Chatbots can draft simple blogs or social captions, but they follow instructions literally and reflect brand voice or strategy only when you tell them to. Plus, they wait for you to prompt them and won’t create any content unless you tell them. 

AI agents handle content creation tasks on their own. Once fed with a brand voice and strategy, an AI agent researches topics and drafts articles or social posts. With integrations, AI agents optimize content for SEO, adjust tone, post at scheduled intervals, and adapt future content to performance.

The verdict: Chatbots generate content only when prompted and can’t sustain a strategy on their own. AI agents, by contrast, create content automatically, stay aligned with brand voice, and adapt standards over time without much input.

Which should you use?

Which should you use depends on your budget, technical capabilities, and your workflow complexities. A retail team might choose a chatbot for simple FAQs but deploy an AI agent for handling returns, restocking updates, and personalized upselling.

Make your decision based on this framework:

  • Budget: Teams with limited budgets might want a cheap chatbot to cover simple interactions. However, many AI agent platforms don’t require high upfront costs, allowing most organizations to deploy AI agents and reduce ongoing labor expenses.
  • Technical capabilities: Nearly anyone can create chatbots and AI agents with no-code building platforms. These let you customize your chatbot or agent using a simple interface or workflow builder. 
  • Workflow complexities: Chatbots work best for simple workflows like answering FAQs or routing inquiries based on customer responses. AI agents, on the other hand, manage more complicated workflows — sometimes even achieving goals you set without step-by-step instructions.
  • Short vs long-term ROI: Chatbots can deliver quick returns by reducing repetitive support tickets that customers initiate. AI agents offer higher long-term ROI by anticipating problems before they occur.

If you need fast, low-cost support for simple inquiries, a basic chatbot works well. But AI agent builders are cost-effective and can independently execute tasks spanning multiple systems. In most cases, they provide greater long-term ROI than chatbots.

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Why companies are moving from chatbots to AI agents

Companies are moving from chatbots to AI agents because they autonomously handle more tasks and perform complex operations beyond chatbot functionalities. They don’t require prompts or engagement to start working. This capability enables them to outperform chatbots by executing complex tasks, multi-step workflows, and memory-intensive jobs.

Build your AI agent team with Lindy

Still deciding between AI agents and chatbots? With Lindy, you don’t have to choose. We are a no-code AI platform that lets you build both — covering tasks across multiple departments.

Here’s why Lindy is an ideal option:

  • Build an agent or chatbot with a prompt: Bring your agent to life by typing a prompt in the chat box. Lindy will create a workflow, which you can edit and deploy. 
  • Integrate with ny software: Lindy’s Autopilot removes the need for thousands of separate app integrations by giving its agents a cloud-based computer that works across any third-party application.
  • Automated CRM updates: Ditch logging a transcript. You can set up Lindy to update CRM fields and fill in missing data in Salesforce and HubSpot, without manual input​. 
  • Lead enrichment: You can configure Lindy to use a prospecting API (People Data Labs) to research prospects and to provide sales teams with richer insights before outreach. 
  • Automated sales outreach: Lindy can execute email campaigns, follow up with leads, and draft response emails based on previous engagement.
  • AI Meeting Note Taker: Lindy agents can join meetings based on Google Calendar events, record and transcribe conversations, and generate structured meeting notes in Google Docs. After the meeting, the agent can send Slack or email summaries with action items and can even trigger follow-up workflows across apps like HubSpot.
  • Cost-effective: Automate up to 40 monthly tasks with Lindy’s free version. The paid version lets you automate up to 1,500 tasks per month, which is a more affordable price per automation compared to many other platforms. 

Automate up to 40 tasks with Lindy and see why it’s the best AI agent builder for your business. Try Lindy for free.

Frequently Asked Questions

Are AI agents more advanced than chatbots?

Yes, AI agents are more advanced than chatbots. Chatbots respond to user prompts, but AI agents can act autonomously and execute more tasks than chatbots.

Can I use both an AI agent and a chatbot together?

Yes, you can use both an AI agent and a chatbot together. Chatbots work best for quick and simple user-prompted tasks like FAQs and order tracking. AI agents handle autonomous, multi-step workflows. Using them together lets you cover routine inquiries while deploying agents for complex processes.

Is ChatGPT a chatbot or an AI agent?

ChatGPT is both. By default, it acts as a chatbot that answers prompts in conversation. With Agent Mode, it also works as an AI agent. In this mode, ChatGPT connects to tools, runs code, browses the web, fills forms, and calls APIs. It can pursue goals through multi-step workflows and carry out tasks with little input.

Are chatbots AI? 

Yes, some chatbots use AI and can respond to prompts and handle simple requests like booking a restaurant table. They can also reference documents or knowledge bases to provide customer support. Advanced AI chatbots retain past interactions for personalized support. Regular folks can build their own AI chatbots using a no-code AI chatbot builder.

About the editorial team
Flo Crivello
Founder and CEO of Lindy

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Education: Master of Arts/Science, Supinfo International University

Previous Experience: Founded Teamflow, a virtual office, and prior to that used to work as a PM at Uber, where he joined in 2015.

Lindy Drope
Founding GTM at Lindy

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

Education: Master of Arts/Science, Supinfo International University

Previous Experience: Founded Teamflow, a virtual office, and prior to that used to work as a PM at Uber, where he joined in 2015.

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