Generative artificial intelligence has reshaped how learners access information, prompting a fundamental re-examination of what constitutes meaningful education. This study investigates whether analytical and application-oriented learning retains — or amplifies — its pedagogical value when conceptual knowledge is instantly accessible through AI tools. Based on primary data collected from 78 students participating in post-graduate management and commerce programs and 25 faculty members, the study finds a strong and convergent preference for applied learning in both groups. Students rate real-world examples as their highest engagement trigger (4.64/5), but faculty observations based on responses show that student engagement in application-based sessions (mean score 4.44/5) significantly exceeds engagement in concept-delivery sessions (3.92/5). Crucially, compared to written theoretical exams, 94% of students favor practical, case-based, or hybrid grading methods. In contrast to the notion that AI encourages cognitive passivity, 69% of students actively participate in comprehending explanations after receiving prompt responses. Together, these results bolster a key claim: analytical learning is not just adaptable to the AI era but also the most sustainable approach to education. A number of evidence-based recommendations for curriculum redesign and assessment reform are made in this study
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