  The combination of conduct, emotion, motivation, and thinking is referred to
as personality. To shortlist candidates more effectively, many organizations
rely on personality predictions. The firm can hire or pick the best candidate
for the desired job description by grouping applicants based on the necessary
personality preferences. A model is created to identify applicants' personality
types so that employers may find qualified candidates by examining a person's
facial expression, speech intonation, and resume. Additionally, the paper
emphasises detecting the changes in employee behaviour. Employee attitudes and
behaviour towards each set of questions are being examined and analysed. Here,
the K-Modes clustering method is used to predict employee well-being, including
job pressure, the working environment, and relationships with peers, utilizing
the OCEAN Model and the CNN algorithm in the AVI-AI administrative system.
Findings imply that AVIs can be used for efficient candidate screening with an
AI decision agent. The study of the specific field is beyond the current
explorations and needed to be expanded with deeper models and new
configurations that can patch extremely complex operations.
