The fuel shuffling problem is posed by the need to reposition partially burned assemblies to achieve minimum X-Y pin power peaks in reload cycles of pressurized water reactors. This problem is a classic artificial intelligence (AI) problem and is highly suitable for AI expert system solution assistance, in contrast to the conventional solution, which ultimately depends solely on trial and error. Such a fuel shuffling assistant would significantly reduce engineering and computer execution time for conventional loading patterns and, much more importantly, even more significantly for lowleakage loading patterns. A successful hardware /software demonstrator has been introduced, paving the way for development of a broadly applicable expert system program. Such a program, upon incorporating the recently developed technique of reverse depletion, would provide a directed path for solving the low-leakage problem.