AI-DRIVEN INTELLIGENT AUTOMATION FRAMEWORK FOR OPTIMIZED HOSPITALITY OPERATIONS AND PREDICTIVE WORKFLOW MANAGEMENT

Abstract

It has made the operation in the hospitality industry complex, labor is expensive and handling of huge amounts of booking and service data is unproductive. The present paper will incorporate a recommendation of an intelligent automation framework developed on the AI in an endeavor to streamline the business of the hotel industry through predictive analytics, automated workflow, and real time decision making. The framework does not merely rely on machine learning algorithms to forecast not just the demands but also the analysis of intelligent documents but also spots anomalies to allow the system to reduce the number of human interventions, and react on the trends of operational changes regularly. It is known that the proposed system will reduce the number of manual processing operations by at least 50 percent, an increase in the operational rate by 35 percent and the rate of decision making by 25 percent as opposed to the traditional management processes. The model advances the API scalability and automation of the complex working mechanisms to consider the quality consumer experience to the large quantities of consumer data. The US national interests that will be discussed in this research are the improvement of its actions in the hospitality industry, the minimization of the economic losses on the impact of inefficiency, the workforce, consuming its services in the most efficient environment, and the technological superiority in the automation of its services. The suggested solution will offer a hopeful, smart, and fact-based method of changing the business in the hospitality sector and securing the assurance of competitiveness.