Small- and medium-sized enterprises (SMEs) in healthcare set out to create social impact, yet they operate under systemic resource constraints — financial, capacity, and capability limitations that shape what they can deliver for patients, professionals, and their wider service ecosystem. Generative AI (GenAI) sharpens a tension in this setting: the same technology that promises efficiency and well-being gains also carries technical, financial, regulatory, and ethical risks, and the organizations with the most to gain often have the least capacity to manage the downsides.
Drawing on a systematic review of academic literature and business and policy publications, combined with input from healthcare SME experts, the article develops a GenAI social impact framework. It guides SMEs through three stages: identifying social impact priority areas, exploring where GenAI applications can alleviate their resource constraints, and implementing GenAI responsibly at the level of the service ecosystem.
By offering a structured and practical roadmap, this work seeks to foster the responsible use of GenAI in healthcare SMEs and to help these organizations create meaningful social impact despite limited means.
The article is published in the Journal of Social Impact in Business Research and can be downloaded here.
