The role of Artificial Intelligence in food allergy: A framework for navigating novel tools

Artificial intelligence (AI) has rapidly penetrated health care and begun to influence clinical care, research, and health system operations. With food allergy, AI offers promise for clinical decision support, personalized care guidance, support of health literacy and a drive toward novel therapies. Despite growing enthusiasm, there are currently no U.S. Food and Drug Administration-cleared AI tools specifically indicated for food allergy, which underscores the need for a structured approach for evaluating, selecting, and implementing AI solutions within the domain. This narrative review focuses on a pragmatic framework for AI tool selection tailored to food allergy use cases. I review the current state of AI in health care and allergy/immunology, describe key dimensions of tool selection, including clinical question definition, data suitability, performance trade-offs, user interaction, governance, and sustainability, and illustrate how these considerations may be applied to food allergy‐relevant challenges. By shifting attention from model novelty to problem-solution fit, implementation readiness, and long-term stewardship, this framework aims to support clinicians, researchers, and health systems to responsibly leverage AI for improved patient outcomes.