Artificial intelligence (AI) has become a staple of the workday for the majority of employees, with a reported 75% of knowledge workers using it in 2024.
But, despite its prevalence and increasing popularity, there’s still a lot of misunderstanding about the different types of AI tools and their use cases. AI agents and AI chatbots are a classic example. The terms are often used interchangeably, but there are actually several key differences between these two AI solutions.
So, what sets them apart from each other? And when should you use each? This guide breaks down what you need to know.
What is an AI chatbot?
An AI chatbot is a type of generative AI (meaning a type of AI that creates new content based on existing datasets) that can answer questions, provide information, or assist with simple tasks.
In the context of customer support, these traditional chatbots can handle customer interactions that happen via text or voice. They use natural language processing (NLP) to understand and generate relevant answers that somewhat mimic human-like conversation.
However, outputs are still somewhat limited and, as a result, fairly robotic. If you’ve ever used ChatGPT, you could probably recognize some obvious stiffness in the response.
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. So, more complex tasks and customer queries often need to be escalated to human agents.
That makes traditional chatbots the best fit for customer 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 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.
According to Gartner, 82% of consumers stated they would opt to use a chatbot instead of waiting for a customer representative to take their call. But that seems to directly conflict with a separate Gartner survey in which only 8% of customers said they had used a chatbot during their most recent customer service interaction.
Despite advancements in this AI technology, for many customers, traditional chatbots still trigger visions of stiff or robotic messaging, endless loops, and frustrating delays before they’re finally pushed to a human agent who can actually help them. For that reason, 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?
Here’s an important distinction: Customers don’t necessarily have a problem with AI in customer service — they have a problem with bad AI in customer service. When AI tools can help with their specific tasks and specific goals in real time, they’re understandably happy.
That’s where an AI agent (sometimes called an AI assistant) comes in. Think of it as several steps beyond a basic chatbot. It’s capable of handling far more complex interactions than a chatbot — including making decisions independently and completing tasks that might’ve previously seemed too complicated for 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 the year 2029.
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. Not a robot.
Put simply, an AI agent offers more adaptability, personalization, and autonomous decision-making when interacting with customers compared to a standard chatbot.
AI agents vs. AI chatbots: Comparison chart of key differences
The biggest difference between an AI agent and an AI chatbot is fairly straightforward to understand: a chatbot is like a trainee who follows a script and still needs a lot of direction, while an agent is like an experienced employee who can confidently make decisions and take action independently.
What does that look like in practice? Here’s a detailed comparison of AI chatbots and agents 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
Traditional chatbots quickly grew strong roots in customer support, but AI agents are taking things much further. 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:
Frontline associates at Verizon use a personal AI assistant that helps them quickly find answers to customer inquiries with a 95% customer success rate that cuts customer transaction times by two to four minutes
Retailer H&M allows customers to have their body 3D scanned in store. This creates a virtual avatar that allows customers to try on jeans virtually and also uses machine learning to convert the body scan into a paper pattern and measurement list — leading to far fewer return requests for human agents.
United Airlines built AI that picks up on customer signals or friction points and allows for more proactive support. For example, if a customer is struggling to add a checked bag and feverishly clicking the button, the AI agent would detect that and immediately display a “Trouble adding a bag?” message before helping the customer.
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
Still struggling to make your choice? Here are a few questions to help you determine whether you should wade in slowly with a chatbot or dive into the deep end with an AI agent:
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, or 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. 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 Assist
Here’s the good news: Implementing an AI agent doesn’t need to be daunting. Assembled Assist 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 Assist, Thrasio was able to:
Automate 53% of all customer interactions
Increase customer satisfaction (CSAT) scores from 87% to 97%
Improve first response times from one hour to under 20 minutes
Save $1.8 million annually
It’s real-world proof of the power of AI for customer support. Sound like something you need to get in on? We thought so. Check out a demo to see Assist’s AI-powered support automation in action.