AI agents and AI chatbots are fundamentally different technologies — and with Gartner reporting that 60% of customer service leaders feel pressure to adopt AI, understanding that difference is critical when choosing automation for your support team.
An AI chatbot follows scripts and handles routine questions. An AI agent makes decisions, takes action, and resolves complex issues independently. Despite the prevalence of AI in support operations (a reported 88% of knowledge workers used it in 2025), these terms are still used interchangeably — creating confusion for teams evaluating their options.
Understanding what sets them apart and when to use each is essential. This guide breaks down what you need to know.
What is an AI chatbot?
An AI chatbot is a type of generative AI that answers questions and assists with simple tasks by following predefined scripts and decision trees.
In customer support, chatbots handle text or voice interactions using natural language processing (NLP) to understand inputs and generate somewhat human-like responses. But outputs are still limited — and often robotic. If you’ve ever used ChatGPT, you’ve probably noticed the stiffness.
That’s because chatbots rely on user inputs and predefined scripts to answer questions and automate routine tasks. These AI systems aren’t capable of autonomous decision-making or problem-solving. More complex tasks and customer queries often need to be escalated to human agents.
That makes traditional chatbots best suited for customer support tasks like:
- Addressing FAQs and common questions using preset answers, scripts, and a knowledge base
- Making basic decisions based on predefined rules or decision trees
- Automating simple and repetitive tasks like:
- Providing order status updates using tracking information
- Guiding users through basic processes (like changing their password or setting up their account)
- Routing customer queries to the right agents or departments based on inputs
These generative AI (GenAI) chatbots can streamline your team’s workflows and also improve your customer experience with accessible and fast customer support. However, reviews among customers are still somewhat mixed.
The customer view on chatbots is conflicted. According to Gartner, 82% of consumers say they’d opt to use a chatbot instead of waiting for a representative to take their call. But only 8% of customers actually used a chatbot during their most recent service interaction.
This gap exists for a few reasons. Despite advancements in AI technology, traditional chatbots still trigger visions of stiff messaging, endless loops, and frustrating delays before customers finally reach a human agent who can actually help them.
That’s why an alarming 64% of customers say they’d prefer companies didn’t use AI for customer service.
And, while chatbots still have their place in customer support, more companies are moving toward AI agents that allow them to reap the benefits of this technology — while still providing a personalized experience that supports (rather than sabotages) customer satisfaction.
What is an AI agent?
An AI agent (or AI assistant) is an autonomous system that makes decisions, takes action, and resolves complex issues without human intervention, and according to a PwC survey, these agents are already being adopted in 79% of companies.
Think of it as several steps beyond a basic chatbot. While chatbots follow scripts and escalate complex issues, AI agents handle nuanced conversations, multi-step workflows, and decision-making that might've previously seemed too complicated for AI.
An important distinction is that customers don’t have a problem with AI in customer service — they have a problem with bad AI.
When interacting with customers, it can dig deep into past interactions and sentiment analysis to understand user intent and help your customers with little to no human intervention. In fact, Gartner predicts that AI agents will autonomously resolve 80% of common customer service issues without any human intervention by 2029, leading to a 30% reduction in operational costs.
Because the capabilities of an AI agent are more advanced, so is the technology. You don’t need to understand the nitty-gritty, but an AI assistant relies on technology like:
- Large language models (LLMs) to process and understand user inputs
- Natural language understanding (NLU) to pull out meaning and context from those customer inputs
- Machine learning to gather and analyze real-time data and improve decision-making
Even with all of that technical stuff under the hood, AI agents also use conversational AI — which means they’re able to provide a user experience that still maintains that human touch. Customers feel like a real, human agent is helping them, rather than a robot.
Put simply, an AI agent offers more adaptability, personalization, and autonomous decision-making. Companies adopting them already see significant benefits, with a PwC survey finding that nearly two-thirds (66%) report increased productivity and over half note cost savings and an improved customer experience.
AI agents vs. AI chatbots: Comparison chart of key differences
The biggest difference: a chatbot follows scripts and requires direction, while an AI agent makes autonomous decisions and takes independent action.
Think of it this way: a chatbot is like a trainee who needs supervision for complex tasks, while an AI agent is like an experienced employee who confidently handles problems end to end.
In practice, their differences become clear. Here’s a detailed comparison so you can understand their ideal use cases and limitations.
This doesn’t mean one is inherently better than the other. Chatbots still serve a purpose and are a solid starting point for support teams who want to begin exploring and implementing AI.
But AI agents offer more flexibility, scalability, and features — making them the clear next (or first) step for companies who have either outgrown the basic features of a traditional chatbot or want to fully leverage the potential of AI for customer support.
The growing ability of AI agents to solve complex issues
While traditional chatbots grew strong roots in customer support, AI agents are taking things much further, with research from PwC showing that 57% of companies are actively using or planning to use agents for customer service in the next 6 months. And, as AI technology has advanced, so have the capabilities of these AI agents — and it’s sure to continue shaking up customer service.
As PwC says, “Just as the internet revolutionized communication, commerce, and access to information, AI agents are expected to fundamentally reshape how we work, collaborate, and create value.” And that’s already happening. For example:
- Verizon frontline associates use a personal AI assistant that delivers a 95% customer success rate and cuts transaction times by 2 to 4 minutes.
- H&M allows customers to have their body 3D scanned in store, creating virtual avatars for trying on jeans virtually and using machine learning to generate custom patterns — leading to far fewer return requests
- United Airlines built AI that detects customer friction in real time. If someone struggles to add a checked bag, the AI immediately displays a “Trouble adding a bag?” message and walks them through the process
Gone are the days when AI in customer support was only associated with templates and routine tasks. AI agents are capable of so much more — and they’re getting smarter every day.
AI agent vs. AI chatbot: Make your choice
Choosing between a chatbot and an AI agent depends on your support complexity, growth trajectory, and operational needs. Ask yourself:
- Is your customer support primarily focused on answering simple questions or does it involve troubleshooting, decision-making, and handling nuanced issues?
- Does your customer support require interaction across multiple channels (e.g., chat, email, phone, social media)?
- Are you expecting significant growth in customer inquiries or expanding into new markets where you need to scale your support? Will you need an AI solution that can grow with you?
- Will customers expect personalized, context-aware conversations, or are scripted, one-size-fits-all responses sufficient?
- Do you need the AI to handle decision-making and take actions on behalf of the customer, or is it sufficient for the AI to only provide responses based on predefined scripts?
- Does your AI need to integrate with internal systems like CRM, ticketing, and databases to provide real-time support, or will it function mostly as a standalone solution?
- Does your customer data require strict privacy measures? Will the AI need to navigate compliance regulations (e.g., HIPAA, GDPR) when handling sensitive customer information?
- What is your budget and resource availability for ongoing maintenance of an AI system?
The world of AI is changing fast and it won’t slow down anytime soon — in fact, a PwC survey found 71% of executives agree that AI agents are advancing so quickly that artificial general intelligence (AGI) could be a reality within 2 years. That means straightforward chatbots — while a solid starting point — will likely be obsolete sooner rather than later. So, an AI agent is your best bet if you want to stay ahead of the curve.
Harness the power of an AI agent with Assembled
Fortunately, implementing an AI agent doesn’t need to be daunting. Assembled offers an AI agent for all of your support channels — chat, email, and voice.
It’s built to handle problems of any complexity by automating multi-step workflows, integrating with internal tools, ensuring every resolution aligns with your brand voice, and automatically resolving tickets in a single touch.
Take the e-commerce company Thrasio as just one example. By implementing Assembled, Thrasio was able to:
- Automate 53% of all customer interactions
- Increase customer satisfaction (CSAT) scores from 87% to 97%
- Improve first response times from 1 hour to under 20 minutes
- Save $1.8 million annually
It’s real-world proof of the power of AI for customer support, and your team can achieve similar results. Book a demo to see Assist’s AI-powered support automation in action.
Frequently asked questions about AI agents and chatbots
Are AI agents just advanced chatbots?
No. While both use AI, chatbots follow predefined scripts and decision trees. AI agents, on the other hand, make autonomous decisions, integrate with your systems to take action, and handle complex, multi-step workflows without human intervention.
How long does it take to implement an AI agent compared to a chatbot?
Implementation timelines vary, but modern AI agents like Assembled can go live in hours to days, rather than weeks. Traditional chatbots often require a similar setup time but deliver limited capabilities. The real difference is in ongoing maintenance: AI agents learn and adapt, while chatbots require constant script updates.
Can AI agents integrate with existing support tools and workflows?
Yes. AI agents integrate with CRMs, help desks, and business systems like Salesforce, Zendesk, Shopify, and more. They pull data from these systems, take actions (like processing refunds), and write updates back — keeping everything in sync without requiring wholesale tech-stack changes.
What's the cost difference between AI agents and chatbots for growing teams?
While initial costs may be similar, AI agents typically deliver better ROI through higher resolution rates and lower operational costs. Teams using AI agents see 30–40% lower handling costs and can scale support without proportional headcount increases. Chatbots often create hidden costs through escalations and repeat contacts.
Do AI agents require more technical expertise to manage than chatbots?
Not necessarily. While AI agents are more sophisticated, modern platforms are designed for non-technical support leaders to configure and manage. You define policies, workflows, and brand voice through intuitive interfaces — no coding required. The real expertise needed is understanding your support processes, which you already have.
