A Comparative Analysis of Legal Transcription Speed and Accuracy: Manual Vs. AI-Assisted Methods in Pup Parañaque Campus

Abstract

The study aimed to determine the effectiveness of the implementation of Artificial Intelligence (AI)-assisted legal transcription and its comparison to the implementation of traditional manual methods among the Bachelor of Science in Office Administration (BSOA) student researchers. Data with a quantitative comparative design and 100 respondents showed that the implementation of the AI system was very effective with a composite mean score of 4.21 “Well Implemented”. In contrast, traditional manual benchmarks showed fundamental limitations, with students falling into the “Developing” stage for speed mean: 3.00 and accuracy mean: 2.95. Bivariate correlation showed strong positive correlation between technology implementation quality and transcription speed r = 0.62 and accuracy r = 0.58. There were no significant differences in age, sex and raw experience, but the educational track of a student had a significant ect on technology perception p = 0.02. The study finds that a move from manual typing to a “human-in-the-loop” model supported by AI maximizes operational workflows, but requires curriculum changes that prioritize document auditing over the stamina for mechanical typing.