Two reports highlight AI’s expanding role across biotech workflows. A broad piece argued that AI agents are being deployed across drug discovery tasks—target identification, design and candidate prioritization—accelerating timelines and enabling hypothesis generation. Separately, Colorado State University researchers used AI to modify antibodies into fluorescent intracellular probes, enabling live‑cell readouts of gene‑expression errors relevant to cancer and other disorders. The antibody probe work demonstrates how AI can optimize paratope modifications to retain binding while enabling intracellular stability and brightness, shortening the design‑build‑test cycle. The broader piece notes that while AI speeds early discovery, robust validation, reproducibility and regulatory engagement remain essential. For R&D teams, these studies underscore a near‑term shift: AI will lower entry costs for complex reagent design and expand internal capabilities, but companies must invest in validation pipelines, data provenance and governance to convert AI leads into regulated therapeutics.