This study explores the transformative potential of Artificial Intelligence (AI) in university-level education, focusing on STEM disciplines and language acquisition. Conducted by a multidisciplinary team of five educators from physics and applied linguistics, the project investigates how AI tools, including ChatGPT, enhance student learning outcomes through innovative classroom strategies. By integrating AI into active learning scenarios, we analyze the effectiveness of personalized feedback, real-time data processing, and linguistic refinement tools in improving both STEM problem-solving skills and language proficiency.

The project is designed around evidence-based practices, gathering quantitative and qualitative data from six courses across five degree programs. Emphasis is placed on student engagement and adaptability to AI tools, fostering creativity, critical analysis, and collaborative learning. The findings highlight the integration of AI in processing STEM datasets, generating lab reports, and refining written expression in native and foreign languages.

Through systematic analysis, we aim to present successful practices that can inspire broader adoption of AI in higher education. Special attention is given to the collaborative insights and coordinated implementation strategies developed by the teaching team. This work contributes to the "Technology in Teaching and Learning" theme by showcasing AI as a driver for personalized, effective, and future-ready education.

Keywords: Artificial Intelligence, STEM education, language learning, multidisciplinary approach, critical analysis, collaborative learning, evidence-based practices.