Privacy-Aware Business Intelligence Architectures: A Unified Governance Framework For AI-Driven Analytics In Hospitality And Service Enterprises

Abstract

One of the biggest trends is the rise of artificial intelligence (AI)-powered business intelligence (BI) systems for the hospitality and service industries, which can improve customer service, streamline operations, and assist with decision-making. The massive volumes of data collected and processed, though, pose privacy, security, and regulatory issues. Most existing BI systems treat analytics governance and privacy controls as separate tasks, resulting in governance inconsistencies and increased organizational risk. A foundational architecture model to build privacy protection for AI analytics that involves data governance, privacy-preserving mechanisms, adherence monitoring, and accountability of AI. This framework will also integrate principles of privacy by design, access control, data minimization, and explainable or transparent governance of AI involving data, allowing for responsible use of data (as well as its processing). The goals of the proposed architecture are to support regulatory compliance, to gain greater trust in the system among stakeholders, and to provide safe & efficient analytics bones for companies in the hospitality or service industry. The goal was to provide properties, hospitality, and service enterprise users with a secure and efficient way to deliver analytics solutions, while improving regulatory compliance and stakeholder trust.