Antimicrobial resistance (AMR) is currently one of the most dangerous crises facing the world. There has been an unsettling rise in the antimicrobial resistance (AMR) identified in animals, which may transfer to people through direct contact, environmental pollution, and food consumption. Efficient poultry health and welfare management and quick diagnosis of bacterial infections in poultry farms can lessen the demand for antibiotics, which is reflected on the spreading of epidemics and AMR. Internet of thinking and machine learning are branches of Artificial intelligence that enable intelligent autonomous systems with human workers remotely managing operations. Machine learning technology plays a role in tracking and preventing infections in poultry farms, which can reduce the need for antibiotic treatment in poultry and, as a result, limit the transmission of antibiotic-resistant pathogens to humans. This information is further analyzed by powerful processing computers with the aid of massive storage devices to seek for trends and hints to pinpoint the locations of disease outbreaks and cases of resistance. The utilization of this knowledge will make it easier to prevent epidemics in the future, reducing the demand for antibiotics. Therefore, this review offers insight on the current AI practices in the management of poultry farms as well as opportunities and concerns around antibiotic resistance throughout the world.