16 Dec Defining Conversational AI

If there’s one thing we as a species are very good at, it’s developing technologies that make our lives better. We value speed, efficiency, and quality on top of everything else — even leading us to develop entire industries centered around this while endeavor. Everything from stone tools all the way to the current state of the internet, we’ve succeeded at maximizing the potential of our man-made technologies.
What’s the next big thing? For the last few years, a lot of buzz has been centered around artificial intelligence (AI) solutions and how to integrate them to major industries like customer service, manufacturing, and even health care. Though the latter two are more technical by nature, it’s the customer service aspect of AI that we’re concerned about today.
That’s where Conversational AI comes in.
A Definition
Conversational AI is a process that allows computers to answer customer inquiries in a human-like manner. It is powered by machine learning, a technology long designed to proactively learn human processes quickly and more efficiently. A clear and easy example of conversational AI would be what is generally referred to as Chatbots or Answerbots.
They simulate human conversation by recognizing human speech and text, compare that to a database with examples, and offer a preset answer that comes closest to the question. According to Google, their version of conversational AI uses the following advanced dialogue management technologies:
- Automatic Speech Recognition
- Natural Language Processing
- Advanced Dialogue Management
- Machine learning
- Noise Cancelling AI
Artificial intelligence then uses recorded speech patterns to study the human voice’s fluctuations to avoid sounding robotic and monotonous. Programs like Siri and Google Assistant, for example, are the best examples of conversational AI with exemplary speech fluctuation. They progressively improve year over year, sounding more and more human with every generational improvement in their operating software.
A quick history of Artificial Intelligence
It’s fascinating how we got to where we are now with regards to artificial intelligence, especially when we look back at how far back it was hypothesized. In the 1950s Alan Turing, a British scientist, came out with a hypothesis that someday computer programs would have the ability to interact with human beings. He published his popular article, ‘Computing Machinery and Intelligence’ which starts with the question “Can machines think?”
Working on the question posed by Turing, another scientist from Germany by the name of Joseph Weizenbaum developed a program he called ELIZA in 1966. This program essentially aimed to simulate conversation with real humans by using open-ended questions with a preset number of follow-up responses. ELIZA would then be known as the first answerbot ever developed, paving the way for the versions that we enjoy now.
Sample companies who have adopted AI
Ford, IBM, and HSBC are just a few of the biggest names who have come around to adopting conversational AI as part of their customer service efforts. IBM, HSBC, and Citibank use LivePerson, a global technology company that develops conversational commerce and AI software.
Google, the foremost technology giant in the world, has also developed their own take at Conversational AI. Google Cloud approaches Conversational AI in four ways: customer care, IoT, search engines, and voice assistance.
It is with Customer Care that we will be focusing on in this article, as it is there that we as a communications company will be benefiting from the most.
What are the benefits of Conversational AI?
Artificial intelligence was designed to recognize human processes and behaviors and to convert this knowledge into automated processes. In a contact center context, this yields benefits for both the business and the customer! Let’s have a look at some of them:
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- Better and quicker customer resolution. With the customer service industry putting more focus on the customer experience, utilizing any technology that leads to faster customer resolution is always helpful. AI basically gathers all necessary information that a customer enters and uses it in the most optimal way possible, leading to a quicker customer journey.
- More efficient and accurate interactions. Conversational AI works by using the customer’s speech and text inputs and matches them with the best solutions on your database. A simpler example would be the following: say a customer wants to check on the status of an order, she can simply input her order number and she’s automatically directed to the right department. This saves her from being transferred around queues, and allocates the contact center’s resources better.
- Optimization of your team. With an answerbot or chatbot integration, customers can simply input the necessary information required from them and they are offered the best solutions available. This creates a call deflection. If they want to talk to an agent, they always can. but the fact that they can be offered self-service solutions deflects calls and leaves your agents free to handle more pressing matters.
- Less Operational Costs. When your contact center agents are optimized in their roles, you are saved from having to employ more. This keeps your overhead operational costs low, while offering all the other benefits of accuracy and efficiency. AI is available to offer more solutions while saving you from having to support more agents, justifying the cost of investment.
Takeaway
Conversational AI is really changing the industry in all the right ways. Contact centers have most to gain from it, thereby making the adaption of the technology a top priority! Google is paving the way with its very own Dialoglow, a framework that is designed to enable interaction between humans and computers using NLP or Natural Language Processing. This is a big step for the industry, and for the adoption of artificial intelligence as a whole.
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