By P.V. Kannan
By 2017 AI was everywhere, it seemed like every company added “AI” to their software whether it truly leveraged artificial intelligence or not. So let’s start with a definition of AI. It is 1) a branch of computer science dealing with the simulation of intelligent behavior in computers, and 2) the capability of a machine to imitate intelligent human behavior. These definitions work as a basic filter, and help identify true AI solutions from quasi AI solutions.
Businesses are taking a very critical look at anything calling itself AI. Companies are asking whether the technology they’re buying will truly improve human capabilities and could potentially augment the human workforce or not. If it can’t do these things, what’s the point? If it can do these things, then it can help companies deliver real, compelling business results.
While some view AI with fear, I encourage people to look at AI with a more open and positive mind. Consumers expect smarter forms of transaction and interaction with businesses, and AI offers a way for businesses to deliver faster and more personalized experiences.
The AI differentiator and other trends include:
[24]7.ai, Google, Amazon, Apple,OpenAI, Nvidia, MSFT, Salesforce. Each serves a specific purpose, and they don’t necessarily need to interact with each other to be successful. Think of it as each company having its own superhero, each with unique powers. Like the Avengers, AI superheroes have different capabilities but when they come together they create a better world.
AI technology can go beyond simply recognizing what someone is saying. It can actually carry on conversations the way a human would. Furthermore, that same “brain” can carry on conversations whether it’s via text or over the phone. That’s why we’ll increasingly see large companies ditch their IVR systems in favor of AI-powered speech. Callers to conversational systems have the option to move to chat, or be able to use their smartphone to choose things from a list. These multimodal experiences are becoming common as they can better serve today’s digitally-engaged millennials.
Large enterprises are deploying virtual agents. These VAs solve many issues, but work hand in hand with humans. Human agents become far more effective because they are augmented with automated sequences. For example, AI can guide consumers through the automated steps that are monotonous for a human agent.
Large enterprises have discovered new ways to use AI to develop user profiles that help them determine with great accuracy who the consumer is and how to treat them. This allows companies to authenticate users for everything but financial transactions. As Blockchain technology takes a stronger hold, that opens up even more possibilities.
AI is helping companies analyze huge amounts of data in order to predict customer intent and therefore create personalized solutions. The way forward is blended AI—a collaboration between human agents and AI to augment what human agents are doing. This collaborative journey is more like Ironman and Jarvis working together than Terminator-like robots taking over.
We all have friends with whom we don’t talk for weeks or months but when we do, we pick up exactly where we left off. This is what customer and brand interactions should be like. Companies are working towards taking this approach to e-commerce and customer service, allowing consumers to pick up a conversation exactly where they left off. No need to start over. Therefore, customer interactions will have to focus on those conversations and not on channels in which they take place, and context will need to transfer between channels.
Machine learning is being integrated into all forms of automated conversations in order to improve. Computers are learning to interpret many forms of organic, unstructured human expression more easily and better understand what the consumer wants. Interactions are growing smarter.
Contact [24]7.ai to learn more about AI-powered conversational IVR.
