Agentic artificial intelligence (AI) offers a revolutionary approach to analyzing health data, but new research highlights a critical disconnect between organizational focus and actual success factors in deploying AI agents. A study involving researchers from ten institutions examined how an agentic AI system identified adverse events in cancer patients undergoing immunotherapy. Key findings emphasized the need to prioritize sociotechnical implementation aspects over traditional tasks like prompt engineering. While agentic AI can swiftly process hundreds of medical records, effective adoption demands attention to five core areas dubbed “heavy lifts”: data integration, model validation, ensuring economic value, monitoring for model drift, and governance. These aspects require dedicated efforts for successful application in clinical settings and beyond. As researchers note, transforming organizational structures to support these AI systems is essential for impactful deployment. This innovative approach holds great promise for enhancing patient outcomes across various sectors.
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