How to Build an AI Chatbot Using ChatGPT

An illustrated man standing by a laptop piecing together conversation bubbles to suggest bot building.

No programming skills? No problem. With OpenAI’s open API (hey, we don’t choose the names) anyone can build an AI chatbot using ChatGPT — no coding skills required.

Do you have what it takes to build a support bot? We reckon you might. While bot building used to be the preserve of techy folks like software engineers and computer scientists, today just about anybody can build a generative AI chatbot for their customer support.

But before we get into how to build an AI chatbot, let’s take a look at the what and the why.

What is a generative AI chatbot?

If you haven’t heard of generative AI — you’re doing a pretty good job of avoiding news headlines, Twitter storms, and viral reddit posts about the threats and opportunities (and comedic potential) of recent advances in artificial intelligence. Just so we’re all on the same page: Gen AI is a form of machine learning that can create original output. This might be text, images, videos, audio, and more.

Text-based generative AI is built using large language models (LLMs). As the name suggests, these models are trained on vast amounts of data. ChatGPT, for example, learned from every text posted online, up until 2022. LLMs use their expansive set of training data to mirror human speech with uncanny ability.

Check out our humanized AI video series to dive into generative AI and LLMs in more detail.

Gen AI chatbots like ChatGPT and Google Bard have set a new — much higher — standard for conversational experiences with bots. And that means support leaders are looking for generative solutions (like UltimateGPT, our own gen AI offering) to level up their customer service.

Looking for the best AI chatbot on the market? Here’s a roundup of the top 15 contenders.

Why should you create an AI chatbot for your support?

With all the hype around ChatGPT, everyone is jumping on the generative AI bandwagon. According to McKinsey, the adoption of AI has more than doubled since 2017. And our in-house customer service trends research found that 60% of business leaders reported they were more likely to invest in AI automation in 2023 than the previous year.

But if FOMO isn’t reason enough, here are some solid business arguments for why you’ll want to build an AI-powered bot for your support. With a gen AI chatbot you’ll be able to:

  • Provide 24/7 customer care and instant resolutions to common customer requests (without any need for human involvement)
  • Drive cost per interaction down and increase productivity, bringing cost savings across your entire support department
  • Give your team the tools to easily manage contact volume spikes and relieve the stress of busy season
  • Future-proof your contact center by leveraging AI technology to scale your support as your business grows
  • Free up agents to spend more time on strategic, high-value work, and the cases that require a human touch (which in turn provides greater job satisfaction and reduces churn)

These are some of the business-wide benefits you’ll see with an AI chatbot on board. And if you need any more convincing, let’s take a look at a few practical examples of how building a generative AI bot can supercharge your support.

3 generative AI chatbot use cases for customer service

1. Creating the most natural conversational experience

Gen AI has raised the bar for what customers expect from automated interactions. After playing around with ChatGPT and seeing the ability of this bot to mimic natural human speech — there’s no way your customers will be willing to tolerate the clunky chatbot experiences of old. Give the people what they want (natural, human-like chatbot conversations) and keep ahead of the competition while doing so.

Read how generative AI is revolutionizing the ecommerce customer experience.

2. Keeping all customer interactions on-brand

One of the most impressive things about LLMs is the ability of these models to adapt their responses stylistically. Ask ChatGPT to give you an answer in the style of the King James’ Bible or a 1930s New York gangster, and you’ll receive. In the customer support sphere this allows brands to create tone of voice settings — to ensure a seamless experience across channels. Take UltimateGPT: with our gen AI bot you can choose from 4 personas to fit with your brand identity.

For even more use cases, check out this article on how to leverage gen AI for your support.

3. Pulling info from your knowledge base instantly

Another area where generative AI excels is summarizing textual information. And this has had a dramatic impact on the process of bot building itself. Instead of manually designing dialogue flows for every single customer intent, with gen AI you can create a bot that pulls information from any text-based source directly — including your customer service knowledge base.

Not only does this mean that you can launch a support bot in minutes, but it allows you to do away with the process of bot training and maintenance altogether. Want to know how it works?

The evolution of bot building

Building an AI chatbot used to involve a fair amount of manual effort and technical skill. But not anymore. Here's what you no longer need to get an AI chatbot set up:

  • Time. Previously it could take anywhere from 3 weeks to a couple of months to launch an AI chatbot. But with generative AI, you can build a bot and start resolving customer requests in mere minutes.
  • Historical support data. In order to automatically answer all of your customers’ most pressing questions, it used to be important to analyze your historical support conversations to determine the most valuable customer intents to automate. Today, a generative bot can draw on your entire knowledge base to answer any query your support articles cover, without any need for an intent system.
  • Dialogue flows. For every customer question you wanted to automate, you would have to build out a conversation flow — with different pathways depending on the details a customer provided. LLMs draw on their huge training data set to generate free-form answers that don't  require pre-built dialogues.
  • Initial training and ongoing maintenance. Once your AI bot was set up, you used to have to train the model to improve performance. These days, generative bots don't require any training or upkeep.
  • People power. Investing time and effort means investing people resources — whether that be IT professionals to get the bot set up, or automation managers to optimize its performance.

How to build an AI chatbot in minutes

Today, all you need is two things: A text-based source of truth that answers all of your common customer support queries, and an API integration with OpenAI’s ChatGPT (or another gen AI provider).

This is how it's done:

  1. Provide the URL of your public customer service knowledge base or FAQ page, or import this as a CSV file
  2. Connect to your gen AI provider via API integration and launch your generative bot
  3. Set the bot tone of voice (if your provider offers this feature) and start generating natural, human-like responses
  4. Optional: Add dialogues for advanced workflows and greater end-to-end automation (but note that you can only add dialogues if your provider supports this function)

Yep, it really is as simple as one, two, three. And sometimes four.

Looking for a generative AI solution? We’ve done the hard work for you — and put together a list of the 10 best AI providers.

Generative AI bot building best practices

Of course to see the most value from this groundbreaking tech, there are a few best practices to follow when you create an AI chatbot.

  • Get your knowledge base into fighting form: And do this before plugging in a generative AI solution. Your bot is only as useful as the data source it answers from — so if your knowledge base contains conflicting information or doesn’t cover FAQs, it won’t be able to provide accurate and relevant support.

Read more on how to prep your knowledge base for generative AI.

  • Choose a provider that has an in-built application layer: Building a generative bot using an API integration with ChatGPT might seem like the best option (OpenAI brought us the original gen AI bot, after all). But while open-source models shared this innovation with the masses, these are foundational technologies — which means they’re missing an application layer that provides seamless UX and other advanced features. 

Psst: UltimateGPT has one of these application layer and is custom-built for support.

  • Make sure you have guardrails in place: The magic of LLMs is that they allow generative bots to talk about anything and everything. But in a customer support setting, you might not want your bot to start waxing lyrical about the meaning of life. That's why it's important to put guardrails in place to keep support conversations on track.

“We spent a lot of time putting the genie back in the bottle and controlling the accuracy of the model. Putting in that control is the absolute first step you have to get right.”

Reetu Kainulainen, CEO and Co-founder, Ultimate

As you can see, it’s easier than ever to get started on your automation journey. With generative AI, the technical barrier to bot building has been leveled. Today, anyone can build an AI chatbot using ChatGPT — and instantly start resolving customer issues in the most conversational way possible.

Experience the future of AI-powered support