The challenges of conducting educational assessments in low- and middle-income environments during the pandemic can be eased by AI-powered speech recognition technology that offers a promising solution to enhance assessments. By utilizing advanced algorithms and machine learning techniques, this technology accurately transcribes spoken language into written text. Reading fluency and comprehension can be efficiently measured by integrating AI speech recognition into assessments, without the need for physical presence. From the safety of their homes, students can perform the assessments using their smartphones or computers, assisting schools in organizing complex logistics. AI speech recognition technology has a great edge in providing instant feedback, which is one of its main benefits. While students are speaking out loud, the AI system can swiftly assess their intonation, pronunciation, and tempo, rendering quick guidance and identifying areas for refinement. This personalized feedback effortlessly assists students in boosting their reading abilities, even in the absence of in-person teacher interactions. Moreover, AI-backed evaluations can be carried out on a wider scale, enabling educators to collect extensive data on reading patterns and tackle specific issues that are commonly seen among students. The objective of this presentation is to feature the self-administered AI Speech recognition Computer-based reading assessment that RTI developed at the request of the Philippines Department of Education (DepEd), under the USAID All Children Reading (ACR). Throughout the school years of 2020-2022, the COVID-19 pandemic posed significant challenges to conducting face-to-face assessments, particularly in remote learning environments. As a result, teachers faced constraints in terms of time and resources to individually assess learners' reading skills against crucial learning competencies. The proposed automated assessment technology offered a potential solution to alleviate this burden and streamline the evaluation process, allowing educators to efficiently gauge students' reading abilities remotely. In February 2022, ACR-Philippines initiated discussions with USAID and the Philippines Department of Education (DepEd) to produce a ‘proof of concept’ that explores the feasibility of a self-administered computer-based reading assessment (CoBRA) in English and Filipino for students in the Philippines. The concept found resonance with the DepEd leadership as the adoption of a computer-based format for assessments aligns with international practices and provides an excellent opportunity to ascertain students' preparedness to take computer-based tests, such as the Program for International Student Assessment (PISA). The result of this intervention generated a prototype solution piloted and tailored to fit DepED's existing platforms for supporting remote learning and delivery. The pilot provided insights on the feasibility of a computer-based assessment in the context of the Philippines for students in grades 4 -6. The research findings examined the performance, reliability, and results of the AI Speech recognition technology reading assessment, compared to the assessor-administered approach of the assessment. The research generated key design considerations, feedback from end users, recommendations regarding implementing similar approaches, and the future development of similar technology for other languages within and outside the Philippines.