Bringing Chatbots to Life: The Inner Workings of Conversational AI

    By: Lisa Chai, Sr. Research Analyst & Erica Allaby, Content Manager


    Recently, the capabilities of speech recognition, conversational AI, and natural language processing (NLP) have accelerated to a level that they can finally help make our lives easier – not harder. Whether it’s an initial phone screen that can verify your identity, a doctor’s device that transcribes patient notes through verbal descriptions, or simply asking questions that can be understood and actioned by a responsive chatbot for an online retailer, conversational AI has come a long way. Speech-to-text technology can now represent different backgrounds within broader populations with various accents. 

    We believe that performing customer care using AI presents a tremendous potential in terms of applications across all sectors, and hence, investors should have exposure to these rapidly evolving technologies. Here’s what investors need to know when it comes to the talk about chatbots – and how to capture the growth of conversational AI to come. In our recent whitepaper, you can take a comprehensive look at how chatbots work and the conversational AI companies that are leading the pack.

    Download Report

    Not all AI Chatbots are Created Equally

    Within conversational AI, there are varying levels of complicity in terms of applications. The most basic of these barely scratch the surface in terms of its capabilities and is one you’ve likely interacted with before: a chatbot or FAQ bot. Chatbots are good for solving basic issues. These may simply collect the customer’s name and contact information and basic details, such as order number and description of the issue. 

    The next step up in intelligence is another household presence: virtual personal assistants, like Siri or Alexa. These assistants can converse and fulfill requests in the moment, utilizing technologies like automated speech recognition and NLP. If it can’t solve the problem, then it will be elevated to an agent. 

    Hierarchy of conversational AI

    The most developed applications for conversational AI to date are virtual customer assistants or AI chatbots. These conversational AIs serve a particular purpose and are well versed in that field for dialog management, usually using robotic process automation (RPA) to help streamline operations. These advanced technologies are a true goldmine in terms of use-cases for the betterment of society as it helps you automate simple tasks, improve employee morale, and create better experiences for your customers.

    Uses of Conversational AI 

    Customer service

    FAQ web pages no longer cut it in the days of on-demand service. Chatbots and conversational AI allow superior and immediate service that can get customers from point A to point B faster than ever before. With 2.5 quintillion bytes of data being produced by humans every day, that’s a lot of data that robots are capable of processing to help better the human experience. Small and nimble retailers are able to source a chatbot that can compete with the instantaneous culture Amazon has created. For example, solutions provided by one of our index members Zendesk can empower customers to self-serve 95% of the time, so the customer service reps are free to focus on more complex and urgent concerns. 


    Improve patient outcomes


    The healthcare industry is broken in some nations; but luckily, transformative technologies are being introduced to the industry to help overhaul healthcare systems for the betterment of patient care, and to improve preventative medicine, doctor retention, and more. The technological revolution disrupting the healthcare industry is what inspired the creation of the ROBO Global Healthcare Technology & Innovation Index (ticker: HTEC) to help provide investment exposure to this impending market growth.

    Imagine a world where physicians can speak to their smart computing device, which is tied in with radiology, pathology, and other specialists, to accelerate the time required for a proper medical diagnosis and ultimately, for a better patient outcome. This use case only scratches the surface. 

    In the clinical setting, integrating AI into employee chat platforms can power an ambient clinical intelligence solution, helping to summarize patient-clinician interactions using conversational AI, integrate that data with information from electronic health records through deep learning and automate workflows, and update the patient’s medical records. 

    The CEO of Microsoft, Satya Nadella, recently called AI in healthcare “the most urgent application.” The company’s recent acquisition of Nuance proves its dedication to moving into healthcare, along with the likes of Amazon, Alibaba, and Apple. 


    Mental health response 


    Far beyond the word of hospitals and e-commerce shops, AI chatbots are beginning to be used for more human applications and for the betterment of society. As the more human level of NLP continues to grow and learn, AI chatbots can be used to help when it comes to mental healthcare, suicide prevention, and even domestic abuse response. 

    When it comes to therapy, it’s no surprise that for many people, the idea of openly sharing secrets and deep-seated emotions with a stranger can be terrifying. In fact, a recent survey from Workplace Intelligence and Oracle found that only 18% of the 12,000 participants surveyed would prefer humans over robots to support their mental health, with a whopping 68% preferring to talk to a robot over their manager about stress and anxiety at work. 

    During the COVID-19 pandemic, demands for dealing with depression have soared, creating a shortage of options when it comes to new patient in-take. The non-judgmental and 24/7 nature of conversational AIs are proving to be an interesting fit for basic mental health responses. 

    While AI has some ways to go in simulating human empathy, we will undoubtedly see continued progress in this field by the developer community.

    Back to All Entries