Conversational AI: All You Need To Know

If you run a business, you know the power of automated responses.

10:01 21 April 2021

Even better are chatbots that can give immediate responses to common questions, find relevant information, engage with customers, and essentially delight them.

 

But customers today are looking for more targeted, human-like experiences when conversing with computers. In essence, human experiences are better when computers speak human. This is where conversational AI technology comes in.

 

What Is Conversational AI?

 

Conversational artificial intelligence creates a bridge between computer and human language by making it natural and easier.

 

For this to be possible, different technologies have to be integrated. These work together to recognize and decipher the human language, understand commands and respond in a way that mimics human conversation.

 

Components of Conversational AI

 

Conversational AI merges machine learning with Natural Language Processing (NLP). NLP processes deliver constant feedback with machine learning processes to improve AI algorithms.

 

As a unit, these two components allow conversational AI to understand and generate natural responses. Here is a deeper look at each component:

 

1. Natural language processing

 

Currently, this is the method used to analyze language alongside machine learning. In the future, it's expected that deep learning will transform conversational AI by advancing its language processing capabilities.

 

NLP consists of:

 

Input generation

 

Here, users give input via an app or website. This can be via text or voice.

 

Input analysis

 

This takes two different channels depending on the mode of input.

 

If the input is text-based, conversational AI will use natural language understanding (NLU) to get meaning and determine intention.

 

On the other hand, if the input is speech-based, a combination of automatic speech recognition and natural language understanding is leveraged to analyze data.

 

Dialogue management

 

In this step, Natural Language Generation is used to formulate responses.

 

Reinforcement Learning

 

Over time, machine learning algorithms are meant to refine responses to enhance response accuracy gradually.

 

2. Machine Learning

 

This is the second component of conversational AI.

 

Machine learning is a smaller field of artificial intelligence comprising a cluster of features, data sets, and algorithms that self-improve with experience.

 

The more input they get, the better AI platforms get at recognizing patterns and using these to generate more natural responses.

 

Your Competitive Advantage: Benefits of Conversational AI

 

Let's get down to business. Conversational AI is beneficial to businesses in several ways. These include:

 

1. Lowered customer care costs

 

This is a major one as anything that reduces overhead costs is good for business.

 

Traditionally, companies would have needed to hire customer care personnel. Hiring a team big enough to ensure responsiveness within minutes and cover communication 24/7 is an expensive undertaking.

 

Conversational AI can handle higher volumes than humans and be faster and more accurate at a fraction of the cost. Automating these functions means savings on salaries, benefits, and overtime.

 

2. Improves Customer Experiences

 

Differentiating becomes a challenge with companies in the same industry offering similar services and products at identical price lines.

 

One way to separate yourself from the pack is through your customer experiences.

 

Customers today need fast service. This includes almost instantaneous responses and resolution to questions and problems. Conversational AI can handle simultaneous requests like delivery tracking and password resetting.

 

As this happens, human agents can handle more complex matters requiring a human touch. At times, people skills are what is needed to build robust customer relationships.

 

The Bottom Line

 

In the coming years, conversational AI will be central to customer service. What we have now is a glimpse into the future that is about to become bigger and better. Conversational AI in coming years should be more accurate and will sound much like you and me.