CREATIVE PRINT LAYOUT AUTOMATION USING AI - Garg, Mohan; Kaur, Prabhjot; Johnson, John Bennet; M. Hari Prasad; Meher, Kunal (ShodhKosh: Journal of Visual and Performing Arts, 2025)
The fast growth of artificial intelligence (AI) has transformed the manner in which design processes function by automating difficult creative jobs such as creating print layouts. This research looks into an AI powered system of making creative print plans automatically to meet the functionality and aesthetics needs. The proposed system uses a combination of several types of Artificial Intelligence, such as Generative Adversarial Networks (GANs), which are used to generate the styles, and Transformers, which are used to understand the meaning of the design content, and Reinforcement Learning (RL), which is used to improve layouts in real time. When these models are assembled, the system produces high quality print layouts on the fly that adhere to set design objectives such as brand unity, readability and visual hierarchy. The program uses a two-part optimisation method which checks for aesthetic and structural consistency. This allows designers to be artistic while still making the system usable. It is suggested that perceived measures be used to judge the aesthetic quality and alignment, contrast and content balance scores be used to judge the functional performance. The solution has a dynamic user interface that enables creators to change results, provide input in real time and the directions of learning. Integration with famous design tools shows how it can be used in real life and how it can improve the speed of printing processes. The conclusion of the study is that AI-based technology can make businesses, schools, and advertising workers much more productive, reduces response times, and will make high quality print design more available to everyone. This work helps to add to a growing field of computer creativity and automatic design.