An industry analysis published by BioTecNika projects that artificial intelligence will transform drug discovery pipelines and personalized medicine by 2033. The report synthesizes case studies where machine learning reduced target identification timelines, optimized lead selection and aided biomarker discovery. It also flags regulatory, data‑governance and validation hurdles that firms must overcome to move AI models from retrospective fit to prospective clinical decision tools. Companies highlighted are deploying AI across target discovery, in silico toxicology and trial‑patient matching, accelerating go/no‑go decisions.