Virtual assistants, chatbots and conversational AI: Creating better experiences for employees, customers, and businesses

Pop culture is replete with examples of humans and computers talking to each other, whether it be HAL 9000, KITT or Jarvis—just to name a few examples. All cheesiness aside, the ability to talk with computers fascinated humans much earlier than the invention of the virtual assistant, chatbot, and conversational AI in general. In the 1940’s, computer scientists began working on Natural Language Processing (NLP), which would help computers understand human language, both spoken and written. But it’s only in the last few years that advances such as BERT, Google’s open-source NLP engine, have led to more natural human-computer interaction, creating better experiences for employees, customers, and businesses.

Today, the conversational AI market is valued at around $6.8 billion (USD) and IDC forecasts that it will grow at a compounded annual rate of nearly 29% between now and 2025. Much of this growth could come from companies that, until recently, held off from investing in conversational AI due to burdensome development and training costs.

Now, a number of new and more powerful use cases are emerging that expand on early applications of conversational AI, and could offer a more compelling business case to get started. Here are a few examples to consider:

Chatbots lead to increased customer satisfaction

HSBC uses Liveperson’s Conversational Cloud and Conversational Builder to automate its contact center operations. Conversational Builder gives HSBC’s contact agents, who are on the front lines responding to customer requests, a code-free tool to create new automated chatbot conversations, as well as build and manage chatbots. Agents can also join a chatbot conversation and offer additional information and assistance to ensure customers’ needs are met. With this level of responsiveness, HSBC saw a 90% increase in customer satisfaction, week-over-week.

Virtual assistants help automate business processes

With the proven capabilities of conversational AI in mind, companies have begun expanding their use of chatbots and virtual assistants to other areas of their business. Resorts World Las Vegas, a 3,500-room integrated resort on the Strip, recently deployed an intelligent virtual agent platform based on the Amelia Integrated Platform. Called RED, this conversational AI platform acts as the resort’s digital concierge, improving the guest and employee experience. If a guest wants to order tickets to a show, order room service, or schedule a wake-up call, RED is just a phone call away. And RED also automates the IT help desk, enabling employees to submit their requests at any time. Eventually, the resort plans to expand its use of the conversational AI technology to HR and other internal departments.

Conversational AI transforms call centers

Bradesco, Brazil’s largest bank, needed a faster way to answer employee’s questions so customers didn’t have to wait. The company worked with IBM to deploy a conversational AI call center that would answer employee’s questions in seconds, instead of minutes. After just five months of training, IBM Watson could understand 100% of the written questions, and 83% of those that were spoken. At the 10-month mark, Watson could answer all of the questions with 96% accuracy. Now in production, Watson answers 283,000 questions a month with 95% accuracy.

These are just a few examples of how conversational AI creates better experiences for employees, customers, and businesses in their call centers—and throughout their organizations..

A key component to the success of any AI solution is the quality of the data used to train its machine learning algorithms and the frequency of retraining those algorithms for continuous learning. According to Deloitte, 20% of the conversational AI-related patents that have been filed in the U.S. over the last two years are focused on improving the training process.

Whether you are just starting to develop your Conversational AI strategy or looking to expand, you’ll want to make sure you have a thorough training data strategy that supports your goals and can scale as you deploy the technology to an increasing number of users. LXT has extensive experience improving Conversational AI solutions and can develop a custom data program to meet your needs.

To speak with one of our AI training data experts, contact us today at