<![CDATA[Artificial intelligence (AI)-supported telemedicine may extend clinical expertise to rural communities, yet its benefits can be offset by unequal connectivity, digital literacy, data representation, and institutional readiness. This study examined the efficacy and health-equity implications of AI-powered telemedicine in post-pandemic rural Indonesia. A qualitative-dominant, convergent mixed-methods secondary study integrated reflexive thematic analysis of peer-reviewed qualitative evidence and Indonesian policy documents with descriptive synthesis of verified national and clinical datasets. Evidence included 2023 national internet statistics, a 63,012-person chronic-disease survey, a 311-patient rheumatology survey, and a 15-interview qualitative study. Telemedicine was most effective for stable follow-up, medication management, specialist access, and travel-cost avoidance, but was less reliable for first diagnosis, unstable disease, and examination-dependent care. Rural internet use (59.33%) remained 17.47 percentage points below urban use (76.80%). Among people with hypertension and/or diabetes, 98.0% reported no telemedicine use, indicating a substantial implementation gap. Four integrated themes emerged: conditional clinical efficacy, redistributed rather than eliminated access burdens, algorithmic amplification of structural disadvantage, and the necessity of human-mediated hybrid care. Conclusion: AI-powered telemedicine is neither inherently equalizing nor intrinsically exclusionary. Its equity effect depends on assisted access, low-bandwidth design, representative validation, clinician oversight, interoperability, and disaggregated monitoring.]]>
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