Scenario planning is a commonly used method that various organizations use to develop their long term plans. Scenario planning for risk management puts an added emphasis on identifying the extreme yet possible risks that are not usually considered in daily operations. While a variety of methods and tools have been proposed for this purpose, we show that formulating an AI planning problem, and applying AI planning techniques to develop the scenarios provides a unique advantage for scenario planning. Our system, the Scenario Planning Advisor (SPA), takes as input the relevant news and social media trends that characterize the current situation, where a subset of them is selected to represent key observations, as well as the domain knowledge. The domain knowledge is acquired using a graphical tool, and then automatically translated to a planning domain. We use a planner to generate multiple plans explaining the observations and projecting future states. The resulting plans are clustered and summarized to generate the scenarios for use in scenario planning. We discuss our knowledge engineering methodology, lessons learned, and the feedback received from the pilot deployment of the SPA system in a large international company. We also show our experiments that measure planning performance and how balanced and informative the generated scenarios are as we increase the complexity of the problem.