Emerging hospitality markets confront a two-speed ecosystem where operational digitalization outpaces strategic AI readiness, creating a benefit-feasibility gap. Providers recognize substantial technology value yet face implementation constraints from costs, integration complexity, and skills shortages, while guests demonstrate acceptance conditional on trust with privacy concerns suppressing willingness to pay. Drawing on dual-perspective empirical evidence derived from Albania's accommodation sector, integrating a national provider readiness assessment and a guest acceptance study, this Design Science Research study develops a segment-differentiated technological blueprint through systematic integration of Design Thinking, service blueprinting, and systems thinking methodologies.
Integrated TAM-TOE-DOI framework analysis reveals three distinct provider segments requiring differentiated implementation pathways: Tech Leaders positioned for AI capabilities, Selective Adopters benefiting from smart modules, and Skeptics requiring foundational capabilities. Empirical evidence establishes that regional ecosystem characteristics outweigh organizational scale in determining adoption feasibility, trust operates as gating condition moderating acceptance and financial commitment, and supply-demand misalignment creates bottlenecks invisible to single-perspective assessments.
Theoretical contributions extend TAM-TOE-DOI frameworks from explanatory constructs to design requirements, conceptualize supply-demand alignment as adoption mechanism, and generate two generalizable design principles: dual-constraint satisfaction requiring simultaneous provider feasibility and guest acceptance, and trust-as-architecture embedding trust mechanisms as structural properties. Practically, the blueprint provides differentiated guidance for policymakers, technology vendors, education providers, and accommodation providers, with transferability to Western Balkans, Mediterranean, and post-transition economies facing comparable heterogeneous readiness and resource constraints.