New policy statement emphasizes pediatric data representation, patient privacy safeguards, and clinical oversight.
RT’s Three Key Takeaways:
- Pediatric-Specific Design: The American Academy of Pediatrics advises that generative artificial intelligence tools should be specifically designed using pediatric datasets rather than adapted from adult clinical models.
- Data Privacy and Disparities: Developers must incorporate strong data security safeguards and representative demographic data to prevent exacerbating existing healthcare disparities among young patients.
- Human Oversight: Generative artificial intelligence is intended to assist pediatric clinical workflows and decision support while maintaining direct clinician oversight and family-centered care.
The American Academy of Pediatrics (AAP) has released clinical guidance addressing the use of generative artificial intelligence (Ai) in pediatric medicine.
The policy statement, titled “Recommendations for the Development and Implementation of Generative Artificial Intelligence Tools in Pediatric Clinical Care,” is published in the November 2026 issue of Pediatrics and was developed by the AAP Council on Clinical Information Technology and the AAP Section on Innovation in Therapeutics and Technology.
According to the AAP, generative Ai models offer emerging opportunities for workflow efficiency, clinical documentation, education, and decision support across pediatric specialties, but they also present unique clinical and ethical challenges. The organization emphasized that patient privacy and security must remain paramount, urging technology developers to create tools tailored directly to pediatric care rather than adapting existing adult models.
“Artificial intelligence in healthcare offers extraordinary opportunities to improve workflow, offer clinical decision support, documentation and education across pediatric subspecialties,” said Srinivasan Suresh, MD, MBA, FAAP, lead author of the policy statement, in a news release. “Yet the AAP recognizes the need to step into this new world with thoughtfulness and intention. There will be a need for rigorous human oversight and accountability.”
Addressing Data Gaps and Healthcare Disparities
According to the release, children remain underrepresented in the datasets used to train most generative Ai applications, and few available tools have undergone specific pediatric evaluation. The policy guidance recommends that developers safely incorporate pediatric datasets that account for developmental differences, family-centered needs, and diverse patient demographics, including race, ethnicity, language, ability, and socioeconomic status, to avoid reinforcing health disparities.
The AAP noted that the guidance focuses exclusively on clinician-facing tools that support patient care and does not address direct Ai usage by children, adolescents, or families, which is being evaluated in separate guidance.
“Generative Ai is already providing real value to pediatricians, and it’s improving at an incredible pace,” said R Brandon Hunter, MD, FAAP, co-author of the statement, in a news release. “But what makes this moment in healthcare so interesting and unusual is that adoption is often moving faster than the evidence on how to use these tools effectively is being produced. We hope this statement gives pediatricians a framework for thinking about AI implementation as that evidence catches up.”
Interdisciplinary Collaboration and Clinical Support
The AAP indicated that an interdisciplinary approach involving clinicians, software developers, researchers, and patient families is necessary to align digital tools with real-world clinical needs.
“Ai will never be able to replace the trusting partnership between families and physician,” said Suresh. “This is an evolving tool that, when used properly as a support, will help pediatricians give more of their attention to their patients.”
