The community reporting system in Hutadaa Village, West Limboto District, remains dependent on manual mechanisms, leading to delayed responses, unstructured documentation, and difficulty for village officials in prioritizing issues. This community service activity aims to design a prototype of an AI-based smart village service application integrated with the WhatsApp platform, enabling automated classification of community reports and assessment of urgency levels. The design was carried out through four stages: field interview-based needs identification, system architecture design, workflow simulation, and limited testing with village officials. The system was designed by integrating WhatsApp Business API, an AI-based image processing module, and a report management interface for village officials. Simulations demonstrated that the system can classify reports into categories (infrastructure, sanitation, social, emergency) and assign urgency levels (low, medium, high) based on analysis of photo and text content, achieving a category classification accuracy of 82.5% and urgency assessment accuracy of 77.5% under good image quality conditions. Interface testing by village officials yielded positive responses regarding ease of use and feature relevance. The designed system has the potential to improve the efficiency of public services at the village level. Full implementation and long-term impact evaluation are required in subsequent service activities. Sistem pelaporan masyarakat di Desa Hutadaa, Kecamatan Limboto Barat, masih bergantung pada mekanisme manual yang menyebabkan keterlambatan penanganan, dokumen laporan yang tidak terstruktur, dan kesulitan bagi aparat desa dalam menetapkan prioritas penanganan. Kegiatan pengabdian ini bertujuan merancang prototipe aplikasi layanan desa cerdas berbasis kecerdasan buatan (AI) yang terintegrasi dengan platform WhatsApp, yang memungkinkan klasifikasi otomatis laporan warga beserta penilaian tingkat urgensinya. Perancangan dilaksanakan melalui empat tahap: identifikasi kebutuhan berbasis wawancara lapangan, desain arsitektur sistem, simulasi alur kerja, dan uji coba terbatas bersama perangkat desa. Sistem dirancang dengan mengintegrasikan WhatsApp Business API, modul pemrosesan gambar berbasis AI, dan antarmuka manajemen laporan untuk aparat desa. Simulasi menunjukkan bahwa sistem mampu mengklasifikasikan laporan ke dalam kategori (infrastruktur, kebersihan, sosial, darurat) dan menetapkan tingkat urgensi (rendah, sedang, tinggi) berdasarkan analisis konten foto dan teks, dengan akurasi klasifikasi kategori sebesar 82,5% dan akurasi penilaian urgensi sebesar 77,5% pada kondisi gambar berkualitas baik. Pengujian antarmuka oleh perangkat desa menghasilkan respons positif terhadap kemudahan penggunaan dan relevansi fitur. Sistem yang dirancang berpotensi meningkatkan efisiensi layanan publik di tingkat desa. Diperlukan implementasi penuh dan evaluasi dampak jangka panjang pada tahap pengabdian berikutnya.