Chatbot vs. AI Agent: What's the difference and why does it matter?

It’s not enough to say you’re integrating AI and automation into your business. You need to understand the difference between solutions that are going to make your customer service extraordinary and solutions that will leave you in the dust behind your competition.

81% of customers expect faster service as technology advances, and 73% expect better personalization according to a recent report from Salesforce.

Chatbots have been a cornerstone of customer service automation for years, but they’re still not enough. 

Last year, Ada introduced its all-new AI Agent, capable of solving any and all unique customer problems with no manual coding or script creation, entirely powered by generative AI

But what makes an AI Agent different from the typical chatbots you’ve used in the past? And why are companies like Square, ClickUp and Wealthsimple choosing to hire an AI Agent instead of training a chatbot? 

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

Chatbots follow scripted conversation workflows that need to be built manually, while AI Agents use generative AI, large language models (LLMs) and natural language processing (NLP) to understand, respond and action customer queries. In short, chatbots regurgitate predefined information, while AI Agents reason. 

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Generative AI unlocks capabilities that far surpass the scripted workflow experience of regular chatbots. As businesses make the switch to generative AI, customers feel the impact on the customer experience. 

Paul Teshima, Chief Client Experience Officer at Wealthsimple, says, “Our AI Agent brings us closer to our customers, reducing operational burden and increasing our automated resolution to help our team think about big picture levers we can pull to create a better client experience.” 

The right solution depends on the problem you're solving

Implementing an AI-first customer service strategy doesn’t need to be difficult. Generative AI has reduced the cost of cognition, and increased the value of strategic, creative thinking. 

With that in mind, there are significant differences between the input and output of a basic chatbot and an AI Agent powered by generative AI. 

Integrating a chatbot

You get what you put into a chatbot, literally. 

Typical customer service chatbots are built by creating a list of common inquiries, like “Where is my order?”. It’s then up to the customer service organization to create a scripted response for each question. These scripted answers can range from brief and straightforward to highly complex dialogues, with branching flows, conditional logic, API integrations with other business systems, and more. 

But the work doesn’t end there. Once an answer has been scripted, you need to provide anywhere from 10 to 500+ examples of how a customer might phrase the question, so the chatbot can learn to recognize the question and serve your customer the correct reply. 

It’s possible to build a good chatbot in this way, but the limitations are clear. Manually scripting and auditing the ever-expanding branches of your chatbot’s conversation workflows is time-consuming and isn’t scalable. 

Onboarding an AI agent

In contrast, onboarding an AI Agent is similar to onboarding a new employee - one with unlimited potential. An AI Agent connects to sources of information you already have — like your help center, knowledge base, and technical documentation — and learns from it in seconds. 

Once onboarded, the AI Agent helps your customers by reasoning through the best solution, instead of regurgitating a predefined script. It helps your customers by solving problems like your agents do: the AI Agent finds relevant information, identifies clear steps to solve the issue at hand, then proceeds with a personalized solution for the customer. 

This isn’t the technology of the future: businesses at the forefront of AI are using it today. According to Allie Hurley, Head of Global Support at ClickUp, "We saw impressive gains when we implemented a scripted chatbot, but were blown away by the results of our generative AI Agent." The benefits of implementing her AI Agent are felt across her team. Jimmy Sullivan, the Manager of Digital Support, sees the difference in the technology first-hand. He says, “I’m impressed that the AI Agent is able to think through the end result that the user is looking to accomplish and pull the specific sections of the help center articles to accomplish that goal. It's far more than just surfacing facts, it's providing actual intelligent resolutions for users.”

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How can AI create extraordinary customer experiences?

Your customers are looking for personalized solutions to their problems, and they want those solutions as fast as possible. 

Data shows that even if you think you’re offering a personalized customer experience right now, you might be wrong. According to Twilio Segment, 85% of businesses say they’re delivering a personalized experience, yet only 60% of customers say they’re receiving one. 

Even if you can provide personalized solutions, you need to deliver instantly. According to customer experience expert Jay Baer’s study on speed, 67% of customers believe speed is as important as price, and 50% of customers won’t spend money with a business that takes longer to respond than they expect.

When choosing between an AI Agent and a chatbot, it’s easy to see how such radically different approaches to customer service automation lead to a different customer experience. A conversation with an AI Agent feels like a conversation with an intelligent customer service representative, whereas a conversation with a chatbot can feel like choosing a preset response from a menu. 

Let’s use a simple example: a customer has accidentally transferred funds to the wrong account. 

The chatbot experience

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A chatbot might not be able to resolve an issue this complex, instead providing a link to an article. Or if it was able to solve the problem, it would have required enormously complex decision trees full of complicated logic to handle all the variables and possible scenarios.

The AI Agent experience

In contrast, an AI Agent has the capacity to recognize the urgency of the customers' questions, address the complexity of multiple tasks, reason through the best solution, and take action immediately. 

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While chatbots can help resolve common scenarios, there’s no denying the experience can frustrate customers that receive unnatural and robotic answers to complex questions.

An AI Agent powered completely by generative AI results in a far more user-friendly, human-like conversation, easily handling all inquiries (not just FAQs) with natural language and constantly adjusting its approach to fit each unique scenario it encounters. 

Coding vs coaching: The investment behind your automation solution

78% of customer service professionals say AI and automation helps them spend more time on the most important parts of their role, according to a report by Hubspot. This is because implementing an AI-first approach does more than transform your customer experience: it can elevate the customer service organization as a whole. 

But which solution is a better fit for your team’s resources and time? 

Coding a chatbot solution

A chatbot with scripted conversation workflows requires a human to manually update it on a regular basis. This means writing conversation workflows when the chatbot needs new content, continuously improving training questions so the chatbot better understands user intent, and combing through conversations to understand gaps in the chatbot’s capabilities. 

Companies that have hundreds of conversation workflows in their chatbot may require several full-time employees to maintain its performance. The best chatbots often require large teams, but it’s worth noting that even a large team cannot change a chatbot’s inherently robotic conversation experience and its inability to resolve complex issues. 

A chatbot can field common questions from your customers, which will reduce work on your team overall, but will only grow and improve when you invest time into manually growing and improving its responses. 

Coaching an AI Agent

Your AI Agent shouldn’t be a tool you integrate, it’s a new hire you onboard. New hires, even impressive ones, need coaching to thrive.  

This means you don’t need to invest time in manually updating scripts, but you do need a top-performing AI manager. If you ask Ada CEO, Mike Murchison, he says, “Calling AI an ‘employee’ can sound like a stretch. But we're fast approaching a time when, for many managers, the first team member they oversee will be an AI. As the leader of a company that specializes in AI customer service, I've seen first-hand the return that businesses get by treating an AI Agent like a member of the team — greater productivity, cost savings and happier team members, to name a few.” 

Like any extraordinary employee, the effort that you put into nurturing their growth can create returns far surpassing even the most ambitious expectations. 

When working with an AI Agent, giving feedback is as easy as sending a direct message. Share guidance with your AI Agent in plain language by requesting it to “avoid speaking negatively about competitors,” or “list complicated instructions one at a time.” Not only that, an AI Agent can identify topics of conversations it’s struggled with, and suggest specific improvements that would help it do improve. As an AI manager, you can coach it on how best to proceed. Watch it implement your feedback immediately. With an AI Agent, there’s no need to worry about training questions, decision trees, or script maintenance as you would with a chatbot— because it’s connected to your knowledge base and other documentation. Any updates you make to your materials automatically sync with your AI Agent, so it always has the most accurate information on hand. 

In reality, coaching and continuously improving an AI Agent not only allows your team to spend time on more important parts of their role. When you onboard an AI Agent, it  evolves the growth paths within the customer service organization, and maximizes your ROI as the team focuses more on AI strategy, analytics, and continuous improvement, and less on maintaining a library of content. 

The solution for the AI-first customer service future

Generative AI is powering a new generation of AI Agents, making scripted chatbots a thing of the past. 

Businesses that invest in their customer experience and onboard an AI Agent are differentiating themselves rapidly, leaving behind the limitations of traditional chatbots and scripted conversation workflows. 

Give yourself a competitive advantage by partnering with specialists that can help you leverage the AI and automation technology of the future. Transform your business with Ada’s AI Agent.

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Grant Oyston
Grant Oyston

Grant Oyston is a Product Marketing Manager at Ada. Before working in tech, he was an innkeeper, a crepe chef, a nanny, a bartender, and an ecommerce support agent, where he personally answered over 100,000 emails asking about where someone's order was.

More info about Grant Oyston: LinkedIn

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