Grid computing gives users access to widely distributed networks of computing resources to solve large-scale tasks such as scientific computation. These tasks are defined as standalone components that can be combined to process the data in various ways. We have implemented a planning system to generate task workflows for the Grid automatically, allowing the user to specify the desired data products in simple terms. The planner uses heuristic control rules and searches a number of alternative complete plans in order to find a high-quality solution. We describe an implemented test case in gravitational wave interferometry and show how the planner is integrated in the Grid environment. We discuss promising future directions of this work. We believe AI planning will play a crucial role in developing complex application workflows for the Grid.