The rising issue of antimicrobial resistance (AMR) is prompting an urgent need for new treatments that go beyond conventional antibiotics. Antimicrobial peptides (AMPs) are emerging as viable options because of their varied actions and lower tendency to develop resistance. This review highlights how artificial intelligence (AI) can play a transformative role in speeding up the discovery, enhancement, and design of these peptides. The current AI methodologies can be classified into three main areas: (i) analyzing genomic and metagenomic data with machine learning tools like the Metagenomic Antimicrobial Peptide Predictor (MACREL) and AMPSphere; (ii) employing protein language models and advanced deep learning techniques, particularly Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) networks and Transformers, for large-scale functional predictions; and (iii) using generative models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion frameworks to design new peptide candidates in a controlled manner. Challenges like data heterogeneity, inconsistent benchmarking that can lead to exaggerated performance claims, and the gap between computational predictions and their practical applicability in clinical settings were also discussed. Additionally, the emerging strategies that aim to balance enhancing antimicrobial effectiveness with reducing toxicity to the host were discussed. The review tried to draw a forward-looking roadmap proposing a closed-loop, active-learning system that integrates standardized datasets and rigorous laboratory validation. Overall, the fusion of AI and peptide bioengineering represented a significant shift, offering exciting possibilities for developing next-generation AMPs aimed at combating multidrug-resistant pathogens.

HIGHLIGHTS

• Artificial intelligence (AI) accelerates discovery of antimicrobial peptides (AMPs).
• Three key AI approaches in this field are data mining, functional prediction, and generative models.
• The fusion of AI and peptide bioengineering represented a significant shift in AMPs discovery.