An emerging theme that uses deep learning and artificial intelligence (AI) to upgrade cinematic aesthetics is automated colour grading in movies. Conventional colour grading methods depend on expert human corrections, which consumes time and subjectivity to the process. This research is focused to find out prospects of deep learning for automated color grading, with a discussion of several architectures, including transformer-based models, generative adversarial networks (GANs), and convolutional neural networks (CNNs). With the help of learning using database that are accurately graded, this research provides a real time cinematic color adjustments using an AI powered system. According to experimental data, deep learning approach achieves good intuitive similarity as compared to professional colourist. The finding suggests transformational influence of AI in cinema post production and provides suggestions for further research