Hyper-automated AI can analyze vast amounts of historical data, including how past decisions were made, and the data sources and other factors influencing those decisions. It learns patterns, correlations, and trends from this data to understand the decision-making process comprehensively. Once trained, hyper-automated AI can rapidly process and analyze new data to provide quick and accurate recommendations for similar future decisions. This leads to faster and more efficient decision-making processes, allowing organizations to respond promptly to dynamic situations, such as patient care adjustments, physician engagements, and more.