# Radiation oncology at crossroads: Rise of AI and managing the unexpected

## TL;DR

This paper discusses how AI is changing radiation oncology and proposes a framework to manage unexpected events in clinical workflows.

## Contribution

The paper introduces a novel framework based on high reliability organization principles to manage AI-driven unpredictability in radiation oncology.

## Key findings

- A framework emphasizing proactive risk assessment and adaptive teamwork is proposed for managing unforeseen events in AI-integrated workflows.
- Human-centered decision-making is positioned as central to managing AI complexities in radiation oncology.
- Cognitive diversity and psychological safety are highlighted as key to fostering collective intelligence in AI-driven clinical settings.

## Abstract

Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflows, enhancing efficiency, safety, and quality. However, this transformation comes with a price of increased complexity and the emergence of unpredictable events. This letter proposes a framework based on high reliability organization (HRO) principles for managing real‐time, unforeseen events. The framework emphasizes proactive risk assessment, adaptive teamwork at the situation assessment point, and reactive learning through incident analysis by placing human‐centered decision‐making at the core. Integrating cognitive diversity, psychological safety, and emotional intelligence fosters collective intelligence, enabling teams to navigate AI‐driven complexities while safeguarding patient safety.