Healthcare’s “new normal” is destined to become artificial intelligence using predictive analytics and/or cognitive computing. The technology has seen exponential growth and the cost is coming down. Advanced neural networks, the most complex of algorithms, now exist as 100 layers of stored and built information. These networks are so advanced they can be given data (even an output) and are capable of extracting features. There will soon no longer be a need to address the formatting of unstructured data for input which is currently prevalent in healthcare. Examples of their existence in healthcare practice today include the development of operating room block times and outpatient scheduling systems. Big data sets exist for researchers to mine, model, train, and enhance machines that ultimately aid human intelligence. Soon, healthcare will see these changes implemented more frequently in imaging diagnostics, optimized workflows, and resource allocation. AI trained on big data to learn will provide healthcare invaluable insights in the future. References Bini, S. A. (2018). Artificial intelligence, machine learning, deep learning, and cognitive computing: What do these terms mean and how will they impact healthcare? The Journal of Arthroplasty, 33(8), 2358-2361. https://doi:10.1016/j.arth.2018.02.067 Chen, M., & Decary, M. (2020). Artificial intelligence in healthcare: An essential guide for health leaders. Healthcare Management Forum, 33(1),10–18. https://doi:10.1177/0840470419873123 Corwin, E., Redeker, N. S., Richmond, T. S., Docherty, S. L., Rita, H., & Pickler, R. H. (2019). Ways of knowing in precision health. Nursing Outlook, 67(4), 293–301. https://doi:10.1016/j.outlook.2019.05.011 Genomics Education Programme. (n.d.). Introducing genomics in healthcare. https://www.genomicseducation.hee.nhs.uk/education/videos/introducing-genomics-in- healthcare/ Google Cloud Tech. (2017, August 31). The 7 steps of machine learning [Video]. YouTube. https://www.youtube.com/watch?v=nKW8Ndu7Mjw