Although the financial sector, the automotive industry and the marketing and retail branch are taking the lead in implementing the latest artificial intelligence (AI) and machine learning (ML) technologies, today there is hardly any field that is not being touched by the progress that has been made since the term AI was first coined by John McCarthy in 1956. The biopharma and healthcare sectors are no exception and although acceptance and implementation of AI-driven technologies in these fields have been sluggish, more and more companies come to the realization that it is critical to embrace AI and related technologies to stay ahead of the competition or at least stay current. Progress in natural language processing (NLP) has led to sophisticated algorithms able to recognize spoken and written language which allows machines not only to recognize words and sentences, but as well to understand context and make connections between text in a variety of different formats from spoken words and written documents to scientific publications and electronic medical records (EMRs). Alexa, Cortana, Siri, and Google Assistant all are examples of powerful, AI-driven search engines made possible,in a large part,because of improvements in NLP. Without NLP the biopharma industry would not have seen today's advances in AI-assisted drug discovery, design of and decision making in clinical trialsand complex data mining and analysis of big data sets.