Researchers and companies are accelerating deployment of AI agents that go beyond classification to assist experimental design, hypothesis generation, and therapeutic decision pathways in oncology. A review of agent‑based approaches describes opportunities and challenges for the cGAS–STING axis and other immuno‑oncology targets, while separate work at Colorado State University uses AI to reengineer antibodies into fluorescent probes for live‑cell activity monitoring. Together the studies show AI is delivering both strategic planning tools and lab‑scale reagent innovation. Practical uptake will depend on reproducibility, integration with laboratory information management systems, and regulatory clarity on AI‑assisted discovery.