The rapid advancement of Artificial Intelligence is transforming diverse fields of knowledge, including education. In engineering education, foundational science courses such as general chemistry often pose significant conceptual and procedural challenges for students, particularly in connecting theoretical principles with practical applications. This study examines the potential of AI-driven tools to improve students' comprehension, analytical reasoning, and engagement in an introductory chemistry course for undergraduate engineering students.

The research employed a quasi-experimental design, comparing an experimental group (n = 31) with a control group (n = 30). The experimental group participated in a blended learning model integrating AI-assisted autonomous tasks with in-class discussions. Students utilized tools such as ChatGPT, Consensus, DeepSeek, Notion, and Wolfram Alpha to acquire core concepts, solve standard problems, and design laboratory experiments. These tools provided natural-language explanations, computational solutions, evidence-based scientific insights, and personalized support, thereby enriching the learning experience. In contrast, the control group followed a traditional instructional approach, consisting of lectures, textbook-based exercises, and conventional laboratory manuals. Both groups completed a pre-test to assess baseline knowledge and a post-test to measure learning gains. A final quiz and perception survey were administered to evaluate knowledge retention and student attitudes toward the subject and AI integration.

Preliminary findings suggest that AI-assisted learning positively influenced the experimental group's performance. Students exhibited enhanced conceptual understanding, improved application of chemical reasoning, and greater motivation. This study supports the strategic incorporation of AI in chemistry education and advocates for its role in evidence-based, interactive, and student-centered pedagogical frameworks. The results contribute to the ongoing discourse on the integration of intelligent technologies to foster meaningful learning in science and engineering education.

Keywords: Higher education, Tec21 model, IA Technology, Chemistry experimental.