Many factors introduce the prospect of changes for the demand environment that a firm faces, with the specifics of such changes not necessarily known in advance. If and when realized, such changes affect the delicate balance between demand and supply and thus should be anticipated to the extent possible. We study the dynamic pricing problem of a retailer facing the prospect of a change in the demand function during a finite selling season with no inventory replenishment opportunity. In particular, the time of the change and the post-change demand function are unknown upfront and we focus on the fundamental trade-off between collecting revenues from current demand and doing so for post-change demand, with the capacity constraint introducing the main tension. We develop a formulation that allows to isolate the role of dynamic pricing in balancing inventory consumption throughout the horizon. We establish that in many settings optimal pricing policies follow a monotone path up to the change in demand. We show how one may compare upfront the attractiveness of pre- and post-change demand conditions, and how such a comparison depends on the problem primitives. We further analyze the impact of the model inputs on the optimal policy and its structure, ranging from the impact of model parameter changes to the impact of different representations of uncertainty about future demand.