Genetically modified soybean [Glycine max (L.) Merr.] cultivars containing herbicide resistance have become the predominant cultivars marketed in the USA. This technology dramatically changed weed management strategies in the USA and created controversy and new challenges within various segments of the industry. This review seeks to summarize many of the issues that arose within the soybean industry surrounding the introduction of the world's first major transgenic crop. Hopefully, the experiences gained during this transition period will benefit future efforts to commercialize transgenic crops. Initially, the new transgenics made the already difficult, yet critically important, task of cultivar selection even more arduous and confusing. Lack of university data, high cultivar turnover rates, and the added burden of factoring in technology fees, yield lag, and weed control costs into the decision of which cultivar to plant were frustrating to most producers. Industry's early insistence on separate cultivar performance trials for Roundup Ready (RR) cultivars taxed limited testing resources and increased the size of the already massive data sets generated. Most often, the end result did not provide a direct comparison with popular conventional cultivars. As this new technology has become fully accepted and assimilated into our industry, comparisons with conventional cultivars are less important since most farmers are selecting only among RR cultivars. The current literature indicates that soybean variety test (SVT) programs with limited resources can effectively compare soybean cultivar performance using combined trials treated only with conventional herbicides with little risk of yield loss or herbicide x cultivar interactions. However, the use of a systems approach or separate RR trials to evaluate the performance of soybean cultivars is now commonplace in the USA due to the sheer dominance of RR cultivars. Many larger SVT programs will soon consider discontinuing separate trials for conventional cultivars as their numbers and importance diminish.