American healthcare organizations face serious personnel shortages across the field of nursing, with the current (and projected) demand for registered nurses (RNs) far exceeding the supply of qualified candidates. The U.S. Bureau of Labor Statistics projects that by the year 2022, the U.S. job market will need 1.1 million new registered nurses (RNs) to replace retirees and fill new positions created by changing patient demographics (including the aging baby-boomer population). High RN vacancy rates are not only expensive, but they can trigger a vicious, perpetual cycle of negative impacts; including overburdening current staff as well as the exorbitant costs associated with backfilling and hiring contract staff. These conditions, if left unchecked, will ultimately lead to negative impacts on patient care and customer service. One of the most effective ways to minimize the impact of nurse attrition on your organization is by building a data model that uses artificial intelligence (AI) with machine learning capabilities to produce predictive analytics on nurse attrition.