AI-Based Technopreneurship for Speech Disorder Therapyin ADHD Children - Uki Hares Yulianti; Ida Zulaeha; Subyantoro; Yusro Edy Nugroho; Kgomotso Moyo (Pandawan Sejahtera Indonesia, 2025)
While existing literature explores AI in healthcare, this study uniquely high-lights technopreneurial approaches to address accessibility and affordability ofAI-based therapies. Focusing on Indonesia as a case study, the paper exam-ines how AI can support children with ADHD who often face delays in speechdevelopment and communication. ADHD affects attention, language process-ing, and social interaction, creating challenges for effective therapy. AI inte-grates machine learning to analyze speech patterns, detect phonological errors,and provide adaptive therapy exercises tailored to children’s developmental lev-els. Findings indicate that AI improves diagnostic accuracy and delivers engag-ing interventions through interactive and gamified tools, enhancing motivationand participation for children who struggle with conventional therapy. AI sys-tems can track progress and adjust feedback in real time, offering personalizedsupport. However, barriers remain regarding affordability, infrastructure, andthe need for human oversight to manage complex emotional and behavioral re-sponses. In this context, technopreneurship is essential to scale affordable AI-based therapies for schools, clinics, and homes. By bridging gaps in healthcaredelivery, this study contributes to SDG 3 (Good Health), SDG 4 (Quality Ed-ucation), and SDG 10 (Reduced Inequalities). It emphasizes the importance ofinterdisciplinary collaboration among AI developers, speech-language patholo-gists, medical professionals, and educators. Overall, AI-driven technopreneur-ship demonstrates strong potential to improve early detection, therapy person-alization, and language development for children with ADHD, while ensuringbroader accessibility and sustainability.