A Comparative Analysis of AI-Powered Financial Literacy Platforms vs. Traditional Methods in Improving Financial Knowledge Retention among Young Adults

This study examines how well young adults (18–25 years old) retain financial knowledge while using AI-powered financial literacy platforms against conventional teaching techniques. Young adults need to be financially literate in order to make complicated financial decisions about their independent living, work, and education. In contrast to more conventional approaches like lectures, workshops, and printed materials, this study examines whether AI-driven platforms—which feature personalized learning routes, interactive exercises, and adaptive feedback—produce better knowledge retention. Participants are randomized to either a regular learning group or an AI-powered platform as part of the study's quasi-experimental approach. Pre- and post-tests measuring both immediate knowledge growth and retention over a specified period (e.g., three months) are used to evaluate financial knowledge. Machine learning algorithms are incorporated into the AI platform used in this study to tailor the learning process according to each learner's progress and preferred method of learning. Financial professionals conduct a series of interactive workshops to train the traditional learning group. The study examines how the two groups differed in their acquisition and retention of knowledge while taking engagement levels, learning preferences, and past financial knowledge into account. The study also investigates user happiness and perceived user experience with both learning approaches. The results will provide light on how AI-powered platforms could improve young adults' financial literacy instruction and guide the creation of more potent educational initiatives. The ultimate goal of this research is to help this crucial group become more financially competent and make wise financial decisions.