This study aimed to analyze the impact of Artificial Intelligence (AI) on Inquiry-based learning (IBL) and personalized problem-solving in engineering education. While existing studies focus either only on IBL or on personalized problem-solving, there are not many studies that focus particularly on the integration of these three concepts. To bridge the gap, we conducted a survey involving 101 students to understand students’ perceptions and awareness of AI-enhanced IBL and personalized problem-solving. The survey questions were divided into 4 attributes and sub-attributes, such as IBL knowledge, IBL perception, Motivation and Career Relevance, and AI support/Tools. Statistical analysis was performed to understand the responses. The findings concluded that a positive attitude from students were observed on utilizing AI tools and IBL techniques. The paper also examines students’ opinions on structuring content based on their respective career goals. With the integration of AI, tailoring content and problem scenarios to individual learning styles can be made less complicated. In conclusion, AI-enhanced IBL enables the same concept to be approached in multiple ways. This enables breaking fixed learning patterns and connecting students to real-world technologies.