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Conversational AI

What is conversational AI?

Conversational artificial intelligence (AI) is intelligent software that is designed to understand, process and respond to human voice input. Conversational AI “bots” engage quickly with prospects, provide superior customer service and amplify your digital brand on social media, websites, mobile devices and a growing range of smart devices.    

What are the business benefits of conversational AI?

Conversational AI increases sales across digital commerce channels with personalized, 24x7 human-like “bots.” These chatbots increase employee productivity and satisfaction by automating high-frequency and routine service desk interactions. They also lower the cost of customer service while improving customer satisfaction and loyalty.

How are companies using conversational AI to simplify customer interactions?

To stay competitive in the present and continue to lead their industries into the future, companies are deploying Conversational AI solutions in multiple ways.

Ford has integrated Amazon Alexa in its newer cars, allowing drivers to do nifty things like check tire pressure, maintenance requirements, gas, etc. right from their homes. Progressive is offering insurance tips to customers via Google Home. Starbucks unveiled “My Starbucks Barista”—AI-based app for mobile orders. RBS launched an AI based bot called “Luvo” to help customers with responses to financial services questions. Domino’s launched a Facebook Messenger chatbot for ordering pizzas. The fashion retailer H&M created a bot designed to be a “Personal Stylist in your pocket.”

What are some important factors to consider in deploying conversational AI solutions?

When designing conversational AI solutions, evaluate how best to address the following five considerations:

  1. Time to value - How much time do you have to experiment? Is your industry already a fast adopter of Conversational AI? Can you set the benchmark for your competitors by moving quickly? 
  2. Focus for the enterprise - Ecommerce channels, employee service desks, customer service centers—there are many places to begin, so start by tying your project to your most pressing needs or best chance at innovation. 
  3. Language support - How many languages do you need to support initially? Long term? Think about the different regions, countries and even dialects that you will want to connect with. 
  4. Data sovereignty - Third party or on-premise? Conversational AI generates significant data with each interaction. Will you want to own it, mine it and get smarter as it grows? 
  5. Platform reach - How many (and which) platforms will you want to target—think about mobile, web, social, messaging, in-home, etc.? What platforms do your customers, employees and partners use to communicate today? 
Is there a proven successful framework for implementing conversational AI?

As a framework for moving forward, consider applying the “three Ms” approach:

  • Raw material – The data generated from conversational interfaces, IoT devices and instrumentation of all people, places and things
  • New machines – “Systems of intelligence” that combine hardware, AI software, data and human input to create value
  • New business models – Commercial models that monetize services and solutions based on systems of intelligence
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