Because of the pandemic, several sectors are experiencing substantial hurdles during the recruitment process. Since it’s hard to evaluate individuals online, the IT industry is also having trouble with hiring procedures. As a result the automated interview analysis has risen for the identification of particular personality traits, which has been a topic of current research. Advances in CV and pattern recognition have led to the development of CNN models based on deep learning approaches. This technology has a wide range of applications in domains like human–computer interaction, personality computing, and psychological testing. With a webcam, these models can precisely identify nonverbal signs and attribute personality attributes to people. Companies may utilize interview traits using artificial intelligence to either supplement or supersede the self-reported personality test that is currently in use instruments—which applicants for positions routinely fabricate to obtain socially acceptable results. An AI-based interviewing method was established through the use of AVI and the implementation using individuality prediction algorithms trained on the initial assessment v2 dataset. By extracting pertinent information from the AVI and utilizing facial expressions to generate authentic personality ratings, the goal was to accomplish automated personality recognition (APR). The model is trained using the VGG-16 behavioral model system in order to improve the model’s accuracy in personality prediction.