Abstract
Antibiotic resistance (AR) has become a significant worldwide public health concern in the twenty-first century. Antimicrobial resistance (AMR) occurs when microorganisms, such as bacteria, fungi, parasites, and viruses acquire genetic changes that make them resistant to antimicrobial drugs, including antibiotics. AMR, often known as the "Silent Pandemic," requires prompt and persistent intervention rather than postponement. Failure to take preventative measures will result in AMR becoming the primary cause of mortality worldwide. In the fight against multidrug-resistant bacteria to halt antibiotic resistance, conventional techniques for developing drugs are expensive and time-consuming. However, AI systems can rapidly scan extensive chemical libraries and forecast possible antibacterial agents. Considering the slow progress of ongoing antibiotic research, it is essential to accelerate the development of novel antibiotics and supplementary treatments. The acceleration is essential to effectively address the increasing health risk posed by antibiotic-resistant bacteria and to ensure that we maintain an advantage in combating these emerging threats. The use of AI in medical research holds significant promise, particularly in addressing multidrug-resistant (MDR) infections to battle AMR. This study focuses on the effective applications of AI in addressing AMR and its potential benefits for humanity. It covers fundamental concepts of AI, current available resources for AI, its uses and scope, as well as its benefits and limitations.AI algorithms consistently observe antibiotic usage, diseases occurrences, and resistance trends. This review explores how AI is used to identify AMR markers, diagnose AMR, develop smallmolecule antibiotic and also emphasizes emerging research domains, such as AMR detection and novel medication development, which contribute to managing AMR.