What is an AI chatbot? The definitive guide

What is an AI chatbot?

Artificial intelligence (AI) chatbots are computer programs trained to simulate human conversation using natural language processing (NLP) and machine learning (ML).

With NLP, AI chatbots can interpret human language and generate relevant responses to users without assistance. Unlike rule-based chatbots that follow pre-programmed scripts, AI chatbots provide unique responses to users based on data they’ve been previously trained on. 

This allows users to lead the conversation in their own words, and get back automated “intelligent” answers for a wide variety of topics. 

Given this flexibility, AI chatbots are effective in many use cases, such as customer support, product recommendations, self-serve appointment scheduling, and more.

Types of AI technologies in AI chatbots

AI chatbots are a subset of conversational AI that use several types of AI technology. Let’s review these terms and how they all work together to create an AI chatbot.

• Machine learning (ML): The foundation of artificial intelligence, machine learning teaches AI engines from data and improves their performance over time without the need to program them.

• Natural language processing (NLP): A branch of AI that focuses on how computers interact with human language, NLP allows the AI to understand language, context, and the intent of human speech.

• Generative AI: A type of AI that generates original text, images, videos, music, code, and more using the data it’s been trained on.

• Conversational AI: An umbrella term for any AI that interacts with humans in a conversational way using technology such as generative AI, machine learning, NLP, and others.

• Large language models (LLMs): An AI program trained on vast quantities of data that can understand and generate responses to human language, as well as content like images, code, and more. Examples: GPT-4o, Llama 3, Claude.

• AI chatbots: The practical application of conversational AI on websites and mobile apps. Used to engage humans conversationally, AI chatbots use the latest LLMs and integrated systems (like a marketing stack) to engage users in human-like ways.

The diagram below illustrates the nested relationship of different types of AI in chatbots, and how LLMs and ML serve as the foundation for AI chatbots.

How do AI chatbots work?

While most companies say they’re using chatbots, it can feel like a challenge to set up an AI chatbot. The truth is, setting up an AI chatbot is so easy that anyone can do it. 

All you need is a good AI chatbot platform and some general knowledge about how an AI chatbot works. Here’s a basic overview.

In a basic sense, an AI chatbot receives a user’s input, interprets it, and turns it into a relevant output. For example, if a mobile app user asks a question, the chatbot will analyze factors such as intent, tone, context, and sentiment, and then return the most accurate, relevant response.

At the heart of every AI chatbot is a large language model (LLM). This equips the chatbot with a base of general knowledge, and enables it to understand the context and intent of a person's words so it can respond in a conversational way. 

But, before an AI chatbot can provide accurate answers about your particular business or industry, it must be trained on additional data specific to your business. 

In other words, you'll customize it with your data. During this training period, the chatbot will be fed data and documentation (like internal wikis or product documentation) in a process called ingestion. 

Once trained, the AI chatbot can answer complex queries about your business with accuracy. For example, a custom-trained chatbot can assist users with specific steps in your onboarding flow, instead of just providing basic information about onboarding in general.

While training a chatbot may sound about as easy as training a lion, it’s quite simple. With Sendbird’s AI Chatbot, for example, you just drag and drop files into our bot trainer interface, link to a website URL, or connect your chatbot to Google Drive, Notion, or Salesforce. 

After ingesting this data, you can customize chatbot responses to common topics to ensure it gives users the right information at the right time.

Now that you’ve got a basic sense of how an AI chatbot works, you might wonder which type of chatbot can help you create the most accurate, rewarding conversational experience for users.

Rule based chatbots vs. AI chatbots vs. AI virtual assistants

Not all chatbots use AI, even though 49% of people say they’ve used an AI chatbot in the last year. 

Here are the differences between AI chatbots, rule-based chatbots, and virtual assistants to help you understand the best option for your use case.

Rule-based chatbots

Rule-based chatbots follow a set script and cannot provide any response that was not pre-programmed. Essentially interactive FAQ programs, rule-based chatbots cannot understand human language or complex questions. 

If a visitor asks a question that falls outside the scripted answers (or there’s a typo) the chatbot won’t be able to answer.

Though not as flexible as their AI counterparts, rule-based chatbots can provide a predictable, automated experience that guides users towards a goal — such as requesting human support or signing up for a demo.

AI chatbots

AI chatbots engage in human-like conversations and answer complex queries using machine learning (ML) and natural language processing (NLP). They’re custom-trained on lots of business-specific data to generate an accurate and original response to users. 

If you’re trying to handle a variety of user requests while delivering more tailored service, AI chatbots are the way to go.

AI virtual assistants

Basically an enhanced form of AI chatbot, AI virtual assistants can handle and automate routine tasks, answer questions, and respond to users through voice inputs. For example, Siri from Apple, or Amazon Alexa.

So what’s the difference between AI chatbots and AI virtual assistants? 

While a custom AI chatbot can tell you the weather forecast tomorrow is showing rain, a virtual assistant can set a reminder for you to bring an umbrella to work, or suggest an alternate route for your morning commute.

Takeaway: These days, the best chatbots combine AI with traditional rule-based programming. These hybrid chatbots allow you to accommodate many topics, answer questions comprehensively, and improve the user experience with automated yet conversational interactions. 

For instance, on high-intent pages like a pricing page, AI chatbots can answer complex questions before passing customers to a sales rep, effectively guiding customers to success long after a rule-based chatbot could keep up.

That said, rule-based chatbots can guide users when the choices are simple and expected, such as requesting to talk to a support agent. While AI chatbots can provide suggested answers and scripted replies through workflows, they’re just not reliant upon them. 

For example, you could add a suggested answer to your AI chatbot for onboarding, support, or sales processes to ensure the best answer to common questions every time.

Use cases for AI chatbots

AI chatbots allow a business to take a proactive yet responsive approach to customer service and engagement, offering fast, 24/7 access to support, content, products, and more. 

Common use cases for AI chatbots include:

• Automated 24/7 customer service: Customer service AI chatbots can handle 80% of routine support tasks and customer questions, according to research by IBM.

• Personalization: Capable of retrieving users’ history and preferences across channels, AI chatbots can create tailored experiences across the customer journey.

• Tailored recommendations: AI chatbots can suggest products, content, or support options based on contextual factors like the user’s tone, behavior, or engagement history.

• Self-serve appointment scheduling: Service-based businesses like healthcare and finance use AI chatbots to allow users to schedule and modify appointments on their own.

• Gather and analyze feedback: In the course of conversation, chatbots ask customers questions and collect information (even using conversational forms) that can later be analyzed for demographic or behavioral insights about your customers.

• Lead generation: AI chatbots can qualify prospects while engaging them, helping to provide educational content, suggesting products, or transferring qualified leads to sales.

Looking for more examples of AI chatbots and their use cases? You can check out our blog about the best ChatGPT alternatives.

AI chatbot benefits

AI chatbots add a conversational element to websites and mobile apps that people often prefer to human agents. By adding AI to the customer experience, you’ll enjoy the benefits of:

• Enhanced customer engagement

• Greater customer satisfaction

• Higher retention and loyalty rates

• More high-quality leads

• Brand differentiation

• Increased efficiency and productivity

How to choose the right AI chatbot (Best practices)

Whether you want to improve customer service, guide product discovery, or just level up your business conversations — here are a few best practices to keep in mind as you consider the right AI chatbot software for you.

1. Prioritize the customer experience

An AI chatbot is an extension of your brand, so its appearance and the content it provides should reflect well on your business. To maintain your brand identity, look for AI chatbot software that allows you to easily customize the look and feel of your chatbot widget. 

To create the best possible AI customer experience, an ideal chatbot should also sound like your brand. Once it’s trained on your content, the AI chatbot should be able to provide non-robotic replies that effectively mimic your brand voice and tone.

2. Compare language models

LLMs are the foundational technology for AI chatbots, providing a base of knowledge and enabling chatbots to understand language and generate relevant replies. While all LLMs are trained on large internet datasets, each will vary in price, performance, as well as data governance and compliance. 

To find the right LLM for your budget and use case, you’ll want to compare the latest LLMs by their cost, speed, and conversational fluency. 

3. Look for easy updates

The best AI chatbots use the latest LLMs with the most up-to-date knowledge base. This means you’ll want a chatbot that makes it easy to update the LLM. For instance, after you release new products or a big LLM update (such as GPT-4 to GPT-4o).

Updating your chatbot knowledge can be tedious, however, so you must look for AI chatbot software that can automatically re-ingest your first-party documents, and stay up-to-date with your latest content updates.

At Sendbird, our AI chatbot software constantly refreshes its knowledge base as you update your content, so all you need to do is upload content from Google Drive, Notion, web URLs, or internal files, and Sendbird’s platform will do the rest.

4. Plan for the future

AI is here to stay, so a good AI chatbot solution will grow with you. You may consider an AI chatbot for your website today, and then for your mobile app or WhatsApp in the future. To ensure the performance of multiple chatbots across channels, look for AI chatbot software with proven scalability to meet your evolving needs.

Ideally, a scalable communication platform will have a track record of serving enterprise-level companies and small businesses. This way, you know the chatbot can handle an increasing number of user queries without compromising performance. 

To this end, look for AI chatbot solutions that offer user interface development kits (UIKits) to help you implement user-friendly AI chatbot interfaces, such as card views, feedback and suggested replies.

Risks and limitations of AI chatbots

AI chatbots offer many benefits, but do come with a handful of limitations. To ensure an effective and responsible deployment, keep these considerations in mind as you think about adding AI chatbots to your website or mobile app.

Hallucinations

AI has the potential to produce incorrect information, which is called a hallucination. For example, ChatGPT has been known to fabricate facts, timelines, and quotes. 

This occurs because AI chatbots devise “probable answers.” While the high probability of the answers makes it most often true, there is no guarantee.

The fix: Test your AI chatbot’s knowledge and response quality before releasing it on your website or mobile app. If you find hallucinations, bias, or inaccuracies, you can optimize response accuracy by ingesting clarifying content that contributes to a better knowledge base for the LLM, by modifying systems prompts, or by switching to a different LLM.

Outdated or inaccurate models

LLMs are trained on huge sets of general internet data, which become outdated, irrelevant, and potentially inaccurate over time. This can lead to false chatbot responses. 

The fix: LLMs vary in quality, so choose an LLM that’s been recently released and ranks highly for performance. It’s a good idea to consult an LLM leaderboard such as Huggingface. You can also look for AI chatbot software that offers all the latest language models like Sendbird.

Security and hacking

AI chatbots may handle sensitive information such as personal details, payment information, and account credentials. This means they’re potentially vulnerable to threats from bad actors, such as malware.

The fix: To protect data from being leaked or intercepted, it’s important to implement security measures such as data encryption, or monitoring and logging to mitigate the risk of hacking. Also look for certified-secure chatbot solutions with ISO 27001 accreditation.

AI chatbot FAQs

Do AI chatbots integrate with my tech stack?

Yes, AI chatbots are built to integrate with every type of tool. A major benefit of using AI chatbots is that they can collect, review, and leverage data quickly — which has a multiplying effect when integrated. 

This means it’s a good idea to choose an AI chatbot platform with plenty of integrations, such as WordPress, Zapier, and Salesforce. In fact, an AI chatbot can use any API or webhook to connect to your stack. 

For example, an AI chatbot synced with support software like Zendesk via Zapier can pass a lead to a support chat agent. Or, Shopify AI chatbots can assist buyers by serving up webstore data about inventory availability, shipping, or return policies.

How do I build an AI chatbot?

Building a custom AI chatbot is a no-code, low-code, or easy-to-code process, depending on your target platform. Say you want a chatbot for your WordPress or Shopify site. With Sendbird, there’s no coding required and all you need is a plugin. If you’re building for other website platforms, the coding is minimal. And for mobile apps, Sendbird offers UIKits that make it fast and simple for developers to implement a custom chatbot interface. 

To launch your chatbot, you’d simply follow a guided flow for chatbot creation, prompt writing, data ingestion and training, and then deployment. You can learn more by reading a blog on building an AI chatbot or watching a quick demo video.

What features should an AI chatbot software have?

As you consider various chatbots, try and get a sense of what will arrive pre-built and what will need to be done in-house. You can expect the following features from leading AI chatbot software:

• • A chatbot builder with:

    • Widget builder

    • LLM parametrization

    • Knowledge base creation

    • System prompt engineering

    • API/function calling, webhooks

    • Testing environments

  • Multiple LLM integrations

  • No-code workflow builder

  • Suggested/scripted answers

  • Chat UI components like cards and forms

  • Analytics & reporting

  • Platform integrations

    • Websites (e.g. WordPress)

    • Ecommerce (e.g. Shopify)

    • Support (e.g. Salesforce)

    • Automation (e.g. Zapier chatbot)

Do I need to train my AI chatbot?

The most effective AI chatbots are trained on sets of data specific to your business or industry. This will ensure your chatbot understands the terms and knowledge of your industry and gives the most accurate responses. This business-specific training is supplemental to the knowledge base that AI chatbots get from a LLM (and LLMs are all pre-trained).

How to get started with AI chatbots

In a world where companies compete for customers based on digital experience, AI chatbots are becoming a key technology for B2B and B2C businesses that want to engage and serve customers better while increasing productivity and efficiency. 

If you’re ready to level up your customer experience with AI chatbots, you’re in the right place. You can launch AI chatbots for free with your choice of LLM without any coding using Sendbird. You can also request a chat demo to see how to get started with AI chatbots from Sendbrid.

For technical information about AI chatbots, you can check out our complete AI chatbot implementation guide.