How conversational systems can help businesses add more context to communication
Nearly 50 years ago, Stanley Kubrick’s science fiction film “2001: A Space Odyssey” hit the big screen. For those who weren’t data scientists or engineers who knew artificial intelligence (AI) was eventually going to be a reality, the concept of a “HAL” was likely pretty wild. However, it’s already happening, and more and more businesses are embracing AI-backed conversational systems to streamline communications with customers, other employees and partners to facilitate person-to-person, person-to-system and system-to-system interaction.
What are conversational systems?
Though customers are already communicating with businesses through text-based chat programs, many businesses are adding more voice chat based on back-and-forth natural language dialogue. A modern conversational business will use a variety of technologies including messaging, voice recognition, chatbots, natural language processing and AI to automate and add more context to communications.
Going forward, these communications systems will not be limited to voice and text, but will also incorporate sight, sound and tactile capabilities to communicate across mobile, digital device “mesh” through APIs or the IoT. The ultimate goal is to gather and use the massive amounts of data generated through the interactions between people and devices and leverage a combination of data analytics and machine learning to make automated conversational systems smarter and more scalable over time.
Business use cases
There is tremendous potential for conversational systems across all industries, but both retail contact centers and healthcare organizations are using the new technologies to improve communications and streamline business processes.
In today’s omnichannel and mobile world, providing a seamless experience to increasingly demanding customers is imperative. By integrating systems and data among all channels, including voice, text, social and web applications, organizations can interact with customers through automated AI-backed chatbots through voice or text. Ideally, these bots have access to the personal profiles of each customer and can resolve and make recommendations about any issues a customer has while gathering data to enable more context as the interaction progresses. If the problem is too complex for the bot to handle, it will be able to recognize that the matter should be escalated to a person based on predetermined rules that can prioritize more urgent issues.
At this year’s Health Information and Management Systems Society conference, messaging and bot vendor Kore.ai made the case for conversational systems and personalized assistants for workers in the healthcare industry. Through smart voice- and text-based communication tools, doctors and nurses can interact more directly with patients, use natural language commands to access or enter data, prepare treatment plans based on the latest research and pharmaceutical information, schedule and view appointments and more. In addition, these systems will get smarter over time and anticipate what professionals will need next. On the other side, patients can also use digital assistants to schedule appointments, determine insurance eligibility and track claims or ask chatbots basic questions about how to handle their conditions and manage their health.
Although conversational systems are still relatively nascent and companies are just scratching the surface of the potential of how machines and people can communicate in more efficient and intelligent ways, there’s no turning back. Simply put, it’s here to stay and, if done right, won’t be as frightening as “HAL.”