Conversational AI and chatbots are making how we interact with humans more accessible by enabling brand-new ways to connect with those around us. Chatbot technology is quickly transforming businesses, disrupting industries, and changing how we use our time. Find out how conversational AI will change your life in this article! When it comes to conversational AI and chatbots, there's a lot of promise for the future. Chatbots are already being used to interact with customers in various ways, from customer service to marketing.

In terms of technology with the power to both disrupt and improve the way that people engage with digital health, there is an argument to be made that conversational AI (which includes Machine Learning) and Natural Language Processing (NLP) can be the missing link. According to the World Economic Forum, virtual assistants – and, by association, chatbots – are not only being used in a diverse set of industries (healthcare, education, retail, tourism, and more), but also offer opportunities for companies to integrate NLP into routine or mundane activities. For instance, Amazon's Alexa is the chatbot that the average person associates with the tech, but the key element in every interaction is the ability of NLP to understand what it is being asked and respond with the appropriate information. Simply put, a "chatbot" is AI software that simulates human conversation with end users – this can be text or voice – with the aim being to leverage machine learning algorithms and NLP to deliver required outcomes. The results of the study paper – which was published in the Journal of Mahatma Gandhi University of Medical Sciences and Technology – were especially illuminating when it came to both understanding how chatbots were perceived by the focus group and the adoption rates of providers themselves.

Confident CDAOs and CIOs will come to the rescue to break data logjams. Data scientists often struggle to acquire, transform, and prepare the data they need to start a machine-learning (ML) project. Data lakes, data engineers, and data prep tools have helped, but the real problem is sourcing data from a complex portfolio of applications and convincing various data gatekeepers to play along. In 2020, senior executives like chief data and analytics officers (CDAOs) and CIOs who are serious about AI will come to the rescue, with a top-down mandate to get around the data access problem. Firms with chief data officers (CDOs) are already about 1.5 times more likely to use AI, ML, and/or deep learning for their insights initiatives than those without CDOs.