Tidal City Intelligence: A Conceptual Framework for AI-Enabled Service Governance in Cities with Fluctuating Populations

Many cities serve far more people than their civil register counts, and the gap rises and falls with tourist seasons, holidays, pilgrimages and festivals. Municipal budgets, staffing and data systems are nonetheless sized to the register. This conceptual paper introduces the Tidal City, a city whose population present swings in recurring, largely predictable cycles that change how public services must be planned. We distinguish the concept from the service population, tourism seasonality and overtourism; propose a two-part Tidal Index measuring the swing’s amplitude and regularity; and offer a typology of seasonal, day-visitor and event-driven tidal cities. Drawing on dynamic capabilities and adaptive governance theory, we set out Tidal City Intelligence, a four-layer framework (Sense, Anticipate, Adapt, Govern) describing the data and AI capabilities a local government needs, and derive testable propositions for each layer. Published data from Pattaya, Thailand, put the average population present at roughly two to three times the registered population and show annual waste moving with guest arrivals while the register barely changed. With only annual guest data, the case illustrates load and demand regularity rather than the full index. The paper offers cities a common measure of the problem and researchers an empirical agenda.