The role of Generative AI in advancing community engagement to address health inequities: a scoping review

Purpose: As generative artificial intelligence (GenAI) becomes increasingly embedded in healthcare, it is essential to characterize how AI-enabled approaches can advance community engagement within academic-community partnerships.The purpose of this scoping review was to map and synthesize literature describing GenAI-enabled approaches that support community engagement within health-related academic-community partnerships involving populations disproportionately affected by health inequities.Methods: We reviewed English-language records published between 2015 and 2025 describing academic-community partnerships involving populations disproportionately affected by health inequities.Structured searches were conducted, supplemented by gray literature and hand-searching.We included records describing the use or proposed use of GenAI to support community engagement.Included records were mapped to the US Centers for Disease Control and Prevention (CDC) Principles of Community Engagement.Results: Seven of 765 records screened met eligibility criteria.Four of the records included completed investigations.Three records highlighted planned approaches to use GenAI in community-engaged research to address health inequities.Among included records, Principle 2 (understanding community context) and Principle 7 (mobilizing community assets) appeared in more records than any other principles.None addressed Principle 1 (clarify goals), Principle 4 (accept community self-determination), Principle 8 (release control), or Principle 9 (foster collaboration).Conclusion: Within the limited literature identified, GenAI may support community engagement by enhancing understanding of community context and mobilizing community assets.Future research should evaluate broader applications across the CDC Principles of Community Engagement.