Let the Conversation Flow

Conversational AI has come a long way since the Eliza chatbot was developed in the 1960s. Today, enterprises in every industry are adopting the technology for an expanding range of use cases. Meanwhile, virtual assistants like Alexa, Google Assistant, and Siri have been welcomed into consumers’ homes to help with everything from smart lighting to home entertainment. They even tell jokes. 

But there are still some rough edges. Human language is a flexible system developed over millennia. We naturally understand each other despite our imperfect grammar, hesitations, and ambiguities. We read the emotional context from facial expressions, tone of voice, and other cues. Conversely, our interactions with virtual assistants lack that rich context and conversations tend to falter after two or three turns – although we have developed fallback mechanisms like asking more questions to clarify or passing the conversation to a human operative. For those who are not computer literate, the need to learn an interface can be a significant barrier. Conversational AI promises to remove these barriers between people and technology.

It might seem like science fiction, but with considerable innovation already underway in these areas, the dream is on track to become a reality over the next few years.

For instance, today, we’re creating hybrid voice, text, and graphics experiences to enable richer, more free-flowing conversations across different contexts. This could be a voice in the car to minimize distractions, text for checking your bank balance in a public space, or graphics so a virtual shopping assistant can bubble up images of suitable items to choose from. Further, with graphical user interface elements blended into the experience, the next best actions can be suggested and accepted with the click of a button, guiding the user all along the journey.

Capabilities like these are already solving some tough business problems for our clients. For example, in our work with the Government of India, we’ve developed a multilingual citizen assistant to connect people – including those who live in remote rural communities – with several services at the federal and state levels. 

Meanwhile, the virtual banking assistant we built for a leading Asia-Pacific bank can interact with users using natural language. It handles 12 million queries monthly, provides instant, personalized recommendations, and generates thousands of qualified leads. Its ability to carry on multiple conversations simultaneously means it can handle the workload of hundreds of humans.

Also in work are the hyper-personalization capabilities to enable timely, focused suggestions in response to the user’s context, interests or habits.

For instance, if a bank customer receives big money in their account, the virtual assistant can proactively recommend a fixed deposit product to earn a better interest rate.

It’s not all about the latest technologies, though. By reaching out across social media channels with conversational AI, enterprises can deliver a more intuitive and immediate experience that keeps time with the communicative rhythms of hyper-connected digital natives. These users are plugged into an array of social media apps, and they expect every organization they deal with to meet them on their channel of choice. It’s impossible for the human workforce, but conversational AI can easily cover it. Recognizing a user signed into a secure channel can cut out repetitive authentication processes, so the conversation flows more easily.

Finally, as we work towards frictionless communication between people, machines, and organizations, we must address the ethical issues head-on. However human-like – or even superhuman – the technology becomes, we need to make sure it explains itself and is inclusive and unbiased at every turn. It needs to represent the best human interaction – then, it can become the smart, perceptive, and trusted associate who helps us get where we want to go and who we’re happy to take along for the ride.