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What Is Conversational AI?

Written by

 Jeremy Gallemard

Today, conversational artificial intelligence (AI) is everywhere. It’s behind online banking chatbots, powers our favourite home assistants (such as Alexa and Google Home), and even helps companies onboard new employees.

Conversational AI offers a range of tangible benefits—both to companies and their consumers. Companies can provide first-class customer service at all times with minimal cost or manual effort while customers receive instant answers to their questions, reducing unnecessary friction within their buying journey. 

This article dives into conversational AI in detail, exploring:

If you want to learn more about the what, why, and how of conversational AI, you’ve come to the right place.

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What is conversational AI?

Conversational AI is everywhere these days. The market’s going from strength to strength, at a compound annual growth rate (CAGR) of 23.4%. In fact, it will be worth an estimated $29.9BN by 2028. 

So, what exactly is conversational AI? 

According to IBM, “Conversational AI refers to technologies, like chatbots or virtual agents, which users can talk to. They use large volumes of data, machine learning, and natural language processing to help imitate human interactions, recognizing speech and text inputs and translating their meanings across various languages.”

It’s worth noting that ‘conversational AI’ is an umbrella term that encompasses a range of technologies, including AI, machine learning (ML), and natural language processing (NLP). Combined, these technologies provide the ‘brainpower’ that fuels tools like chatbots or home assistants. They ensure these tools can understand customers’ intent, decipher their language and context, and respond to their queries appropriately—whether providing order/inventory updates or playing a piece of music. 

How does conversational AI work?

As mentioned above, conversational AI relies heavily on NLP and ML. Let’s delve into these technologies in closer detail, outlining what they are and how they fuel effective conversational AI.

Natural Language Processing

According to Gartner, “Natural-language processing (NLP) technology involves the ability to turn text or audio speech into encoded, structured information, based on an appropriate ontology.” 

Right, so what exactly does that mean?

Imagine a chatbot. When a customer submits a request, the chatbot needs to process what they’re saying, understand the nature of their request, and respond appropriately. This is where NLP comes in. It’s worth noting that NLP encompasses several different areas, including natural language understanding (NLU), dialogue management, and natural language generation (NLG)—we’ll delve into each of these topics in closer detail below. 

Machine Learning

Conversational AI also requires ML, described by MIT as “a subfield of artificial intelligence that gives computers the ability to learn without explicitly being programmed”. 

ML is what ensures conversational AI gets better over time. It analyses previous interactions to learn from the experience, identifying areas for improvement and changing how it handles similar requests in the future. 

Going from request to reply

Now we’ve defined the core technologies at play, let’s dig into the exact process conversational AI uses to go from a customer’s initial request to providing a helpful response. 

The first step is for the application to receive an initial input. For example, for a user to say “Alexa, play The Beatles” or for a customer to type “I want to return a product” into a chatbot interface. The tool uses NLP to process the request and understand the user’s intent, dialogue management to identify an appropriate response, and NLG to formulate a coherent response. The ML component of conversational AI continually operates in the background, analysing all user/customer interactions and improving how it communicates over time. 

Use cases for conversational AI technology

The use cases for conversational AI are almost endless, but there are four notable examples worth examining in closer detail: 

  • Enhancing accessibility
  • Powering Internet of Things (IoT) devices
  • Supporting training and administrative processes
  • Fuelling first-class customer service and support

Enhancing accessibility

Accessibility—ensuring disabled people can seamlessly access products and services—should be front of mind for all organisations, regardless of their size or sector. 

According to UN estimates, around 1 billion have disabilities (roughly 15% of the global population). Therefore, accessibility is both a moral imperative and good business sense—organisations that fail to design accessibility-first solutions are ignoring approximately 15% of their potential customer base. 

Conversational AI helps people with disabilities to interact and communicate more effectively, whether with individuals or companies. For example, tools like Voiceitt use conversational AI to understand what people with disabilities (such as brain injuries or Parkinson’s) are saying, and normalises their speech to make it more understandable to others. 

Voice-based chatbots help those who struggle with typing access the same level of customer service as their able-bodied counterparts, while chatbots can also help those with hearing impairments to solve their queries on a text-only basis. 


Plus, chatbots are easier for disabled people to navigate and understand. They provide condensed information relevant to the consumer’s particular query, show content in logical hierarchies, ask precise questions, and offer targeted, specific solutions. 

Powering IoT devices

Conversational AI powers Internet of Things (IoT) applications in the home, such as Amazon’s Alexa or Google Home. These examples show the true power of conversational AI, heralding the long-awaited era of robotic, voice-enabled assistance. 

As Amazon proudly states, “With conversational AI, voice-enabled devices like Amazon Echo are enabling the sort of magical interactions we’ve dreamed of for decades. Through a voice user interface (VUI), voice services like Alexa can communicate with people in ways that feel effortless, solve problems, and get smarter over time.”

Conversation AI-powered VUIs seamlessly consider multiple factors when processing and responding to customers' requests. This includes:

  • Variety: Understanding the variations in how people might phrase the same requests.
  • Context: For example, when someone asks Alexa at 1am to remind them to do something tomorrow, they might technically mean later that same day.
  • Engagement: Remembering what users have just said and engaging appropriately.
  • Tone: Including personality, emotion, and jokes when appropriate.
  • Memory: Remembering what users have said in the past, whether a few minutes or a few weeks ago. 

By taking these factors into account, conversation AI tools can effectively mimic how humans interact. 

Supporting training and administrative processes

Conversational AI also plays a pivotal role in supporting training and administrative processes. For example, it can help lead new employees through onboarding programs while minimising the time and effort required from the HR team.

So, how exactly does this work?

Consider that onboarding processes are generally the same for most new hires. They’re inherently repeatable—the HR team shares the same must-know information over and over again. For example, this includes WiFi passwords, highlighting the fire emergency procedure, or reminding employees of the company’s working from home policy. 

HR teams can plug this information into conversational AI-powered tools, such as chatbots, to provide value-add onboarding processes that don’t take up any of their time or focus. Conversational AI tools can also check in with employees throughout this process to if they have any additional questions. 

Of course, this applies beyond onboarding alone. Leveraging conversational AI tools, companies can check in regularly to assess employee sentiment and identify potential challenges (e.g. dissatisfaction with senior management) at the earliest possible stage. In fact, employees might be more willing to provide honest responses to automated tools than to another colleague—especially if submissions are anonymous. 

Fueling first-class customer service and support

Conversational AI is best known for its role in fueling first-class customer service and support. 

Put simply, chatbots allow companies to serve customers at scale. Implementing a single AI-powered chatbot, like Smart Bot, allows organisations to seamlessly handle thousands of global customer conversations simultaneously. They can increase their customer service capabilities while decreasing the number of human resources required, keeping customer service teams as lean as possible while still providing stellar customer support.

The benefits of conversational AI solutions

Let’s dig into the specific benefits that both customers and organisations gain from implementing conversational AI solutions. 

From the consumers’ perspectives

89% of US consumers expect companies to have some form of online self-service support portal, while 95% of companies received a massive influx of customer service requests throughout 2021—indicating just how popular they have become among consumers. In fact, the customer satisfaction rate when dealing with chatbots is 87.58%, 2% higher than when consumers speak with human agents. 

But why exactly are they such a hit?

Above all else, consumers crave clarity and rapid responses. The smartphone generation isn’t used to waiting. If they have to hang around to find an answer to their question, they’ll likely leave your site and go elsewhere. This is where conversational AI, such as chatbots, comes in. They provide instant, clear responses—directly answering consumers’ burning questions or signposting them to useful resources. 

In turn, this increases customer satisfaction, loyalty, and retention. Happy customers equal repeat business. It’s as simple as that. 

From the company’ perspective

Chatbots have transformed how organizations approach customer service. Juniper Research estimates that they will save companies a massive $8BN in 2022, with cost savings of around $0.50 - $0.70 per interaction. Meanwhile, in 2023, conversational AI-powered tools are expected to save over 2.5BN customer service hours.  

Chatbots can handle thousands of conversations at once, unlike customer service agents. They’re always available to lend a helping hand—making them ideal for organizations serving a global customer base across multiple time zones. They don’t receive a salary and never take time off. What more could companies ask for?

Implementing conversational AI chatbots

The best conversational intelligence/chatbot solutions are incredibly easy to implement. These ready-to-go tools, such as Smart Bot, integrate seamlessly with a wide variety of potential communication channels: Salesforce, WhatsApp, Zendesk, Messenger, Teams, Slack, and more. 

Best of all, leading conversational AI solutions providers work with your company to ensure you deploy their chatbots correctly—and that you derive tangible ROI from their products. They work hand in hand with your team to get everything set up correctly and will provide ongoing assistance should you run into any issues.  

Put conversational AI at the heart of your customer service efforts

Conversational AI tools are continuing to evolve, capable of handling more complex requests with every passing year. Their machine learning models are continually improving, gaining a deeper understanding of users and enhancing their ability to communicate in a human-like fashion.

Today, they can be used to help provide accessible customer service, act as a digital assistant in homes, cars, or phones, and roll out highly systematic onboarding or training programs. 

In other words, there’s almost nothing they can’t do. 

Businesses that use chatbots to their full potential will maximise their customer service capabilities while minimising costs. In turn, this will boost customer satisfaction and company profit. One thing’s for certain: all businesses need to implement conversational AI tools, fast. 

For more ideas on keeping your customers satisfied, check out our customer satisfaction checklist

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Jeremy Gallemard

Hello! I'm Jérémy, President & Co-founder of Smart Tribune. With my background in the digital & customer experience space I'm happy to share my insight & practical advice on customer experience today & what it might look like tomorrow. Happy reading!

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