AURA (Adaptive Unified Resort AI) is a conceptual framework for a unified, multi-module artificial intelligence architecture designed to function as an integrated intelligence layer across the full spectrum of hotel operations. The framework addresses a structural gap in contemporary hospitality technology: existing AI deployments treat discrete operational domains in isolation, reproducing the siloed logic of the legacy systems they are intended to improve. AURA proposes an alternative in which eight interdependent modules, termed hemispheres, share a common data substrate and generate compound operational benefits that no individual component could produce alone.

The eight hemispheres are the Command Bridge (real-time operational coordination and dashboard aggregation), Unified Guest Intelligence (longitudinal guest profiling and hyper-personalization), Spatial Engine (predictive space allocation and IoT-integrated environment management), Empathy Engine (affective computing applied to staff-guest interaction and real-time sentiment coaching), PAR Intelligence (predictive physical asset and resource optimization), Revenue Intel (AI-driven dynamic pricing integrated with guest lifetime value data), Cultural Intel (culturally responsive programming and communication), and Privacy Sovereignty (consent management and privacy-by-design compliance).

The paper contextualizes this architecture within the scholarly literature on hospitality technology, affective computing, revenue management, and privacy engineering, and identifies the absence of a unified orchestration framework as the central research gap the architecture addresses. A conceptual evaluation framework is proposed, including KPI definitions, a quasi-experimental pilot study design, and a phased module-level validation sequence. Ethical and governance considerations specific to AI-augmented hospitality environments are examined in detail, with particular attention to biometric data, affect-sensitive inputs, staff surveillance, and regulatory compliance under GDPR and the EU AI Act.

All performance projections cited are illustrative, drawn from adjacent industry evidence, and await validation through controlled pilot studies. The paper's contributions include a unified architectural taxonomy for hospitality AI, the orchestration gap as a novel research construct, a hospitality-specific privacy governance model, and a comparative analysis of traditional, fragmented, and unified AI technology paradigms in hotel operations.