As AI's presence grows in academia, concerns about the integrity of scientific literature are rising, prompting researchers like Ahmed Abdeen Hamed to develop tools like xFakeSci, which can detect AI-generated papers with 94% accuracy. Meanwhile, a group of AI practitioners is exploring the democratization of AI through low-code/no-code principles to enhance citizen participation in scientific research, emphasizing the importance of open-source models. Former JAMA editor Howard Bauchner predicts that AI will transform scientific manuscript writing and peer-review processes, potentially aiding editors in selecting impactful papers. He suggests that AI could evaluate submissions and provide initial scores to streamline the review process. The ongoing integration of AI in medicine is also noted, as it assists in diagnostic evaluations and aims towards precision medicine. The future of scientific publication is setting the stage for AI to play a pivotal role in both writing and reviewing research.