This study examines the performance and limitations of image-generative artificial intelligence through actual generative photo production. The goal is to identify the possibilities and problems of generative artificial intelligence by generating images that are visually no different from photographs based on machine learning of Korean portraits. The images produced using generative artificial intelligence based on Generative Adversarial Networks not only maintained similarities with portraits, but also showed very realistic visual characteristics. However, although the generated image looks like a photograph, the Chosun's hat expressed in the portrait were not synthesized properly. In other words, generative AI has revealed its limitations in transforming and distorting elements that are not in the learning data. In addition, when the GAN value is set to 100, in short, in the case of fully automatic generation, all portraits showed convergence to the stereotype. It means that the characteristics of individual characters disappear. After all, the direction of generative artificial intelligence has been decided, and the ultimate result is the world of robots. To combat this contradiction and grim prospect, active human intervention is required.