Artificial intelligence (AI) has become an inevitable part of the healthcare industry. The disease ontology is expanding at an alarming rate, and it is close to impossible for medical practitioners or healthcare professionals to deal with vast data in clinical records, submit lab reports, medical imaging data, drug targets, phenotypes, and genomics data, or find a concrete justification or treatment as per individual variability in disease management. AI can learn feature patterns from these huge datasets and can aid these professionals with robust and reliable predictions. With the integration of AI in immunology, the enhancements in diagnosis, drug discovery, and personalized therapy have significantly improved healthcare outcomes. The application of AI in immunology can be exploited for antigen-specific vaccine design, as well as the prioritization of potential immune epitopes from bacterial pathogens that activate human T cells.