The electricity industry has undergone a series of radical economic, policy, and technology changes over the past several decades. More changes are to come, to be sure, but their nature and magnitude is highly uncertain. Such changes in market fundamentals profoundly impact the economic value of transmission. This paper quantifies the economic value of stochastic programming for transmission planning over a multidecadal time horizon, considering how generation investment reacts to network reinforcements and how the grid can be adapted later on as circumstances change. The economic value is the difference between the probability-weighted present worth of cost of (1) a stochastic model that chooses first-stage (through 2024) lines to minimize that cost and (2) a stochastic model whose 2024 lines are constrained to be those that were chosen by a suboptimal process, such as deterministic decision making. Even considering a small number of scenarios can drastically improve solutions.