6 Things You May Not Know About How Conversational AI Works

By Ruth Favela

Artificial intelligence (AI) supports a variety of business practices, including customer support. However, not all AI is the same. There are standard chatbots that use the basics of AI, and then there are those with conversational AI. So, what makes them different? And why are conversational AI chatbots such game changers for customer experiences? 

What is conversational AI?

Conversational AI describes customer- or employee-facing chatbots that attempt a human conversation with a machine. It’s different from a standard AI chatbot, which functions based on if-then statements and decision trees to relay answers from keywords. While standard chatbots are effective in some cases, they don’t provide the same type of interactions as conversational AI, which understands human language.

Conversational AI encompasses several components to deliver these human-centered conversations, including:

  • Natural language processing (NLP) and natural language understanding (NLU) allow AI to understand text in the same way humans do.
  • Machine learning (ML) allows the chatbot to keep learning as it ingests more data.
  • Contextual awareness enables the chatbot to understand the situation of users or devices.

Conversational AI varies from operational AI, so there are likely things you didn’t know about what it can do. 

1. Conversational AI chatbots understand sentiment and intent.

Traditional chatbots typically use AI to identify keywords from the user’s query. They then provide answers from their library to answer the question. In most cases, this doesn’t hit the mark for customers. That’s because traditional chatbots don’t understand sentiment and intent.

This is an important differentiator. The ability to comprehend sentiment and intent has great value in customer support. It can translate what people are typing beyond a keyword. With so many ways to ask a question, conversational AI delivers the most appropriate and accurate response. It can do this because it uses NLP, NLU, ML, and contextual awareness. 

To illustrate how it works, here’s an example. 

A customer asks a chatbot about a return submitted for credit. The standard chatbot would provide the person with a link to the return policy. The conversational AI chatbot would recognize the sentiment and intent of the customer looking for specific information. The latter is able to reference other databases to then provide accurate information to resolve the query. The former makes it necessary for human intervention to serve the customer. 

2. Conversational AI keeps learning.

Conversational AI improves customer experiences and continues to learn by ingesting data from actual interactions. As a result, it improves how it communicates and gives relevant answers to customers. You don’t have to do anything to enable this learning. It happens because the technology is designed to learn. 

3. Conversational AI supports agents too.

Agents need to be as efficient as possible to handle their queue. Bottlenecks often occur when team members spend too much time looking for information. Conversational AI alleviates this by categorizing similar tickets to the one currently ready for a reply. It can then suggest articles or macros to support the agent. 

You can also eliminate the labor-intensive, manual task of labeling tickets because the AI does it automatically. As a result of these features, you can be timelier in responding. This is important because customers have high expectations, with 31.2 percent expecting a response in an hour or less, according to one survey. Meeting this standard can be a challenge for any company. While you can add staff, the real change comes with employing conversational AI throughout the customer service ecosystem. 

4. Activating conversational AI is quick.

Implementing conversational AI isn’t a long process. Conversational AI doesn’t run on a set of rules like traditional chatbots—which can take longer to launch—do. Instead, your AI engine ingests historical data then creates models and frameworks. While it’s a sophisticated process, it’s not one you’ll have to wait months to complete. Your platform will be ready to use soon after you begin, helping you realize the value of your investment rapidly. 

5. Conversational AI enables custom workflows.

In many cases, AI is a black box. When deployed, what goes on behind the curtain stays that way. Conversational AI works differently and provides more transparency. In turn, you can build custom workflows, allowing customers to take complex actions without interacting with agents. 

6. Conversational AI is security-focused.

There are concerns about security measures with any technology you want to leverage. In customer support exchanges, personal information is shared. A conversational AI platform always prioritizes security to ensure compliance and proactive data protection.


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