The Evolution of Artificial Intelligence in Oncology: Impact on Trials, Workflows, and Outcomes

AI’s role in oncology has evolved significantly, emerging as a powerful tool for enhancing care and research from its early days as a “hallucination-prone punch line.”
The National Cancer Institute highlights AI’s potential to transform cancer care through improvements in training models, hardware upgrades, and access to large data sets in imaging and genomics.
The emphasis is on validating AI and machine learning technologies in clinical practice and developing “explainable” AI to better integrate the technology into oncology workflows.
Specialized large language models, AI-assisted CT scans, and foundational models are increasingly used to assist in clinical processes and streamline oncology research and documentation.
AI technologies, such as AI-assisted mammograms and cardio-oncology models, are aiding in early cancer detection and improving patient care.
Experts discuss the potential of AI to expedite the process of drug discovery, predict patient risks, and address the shortage of pathologists through foundational models.
The industry anticipates 2026 as the year when AI will begin to industrialize in oncology, enabling faster drug discovery with improved oversight and governance to maintain safety and accuracy.

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