Keywords
Artificial intelligence
Curriculum integration
Teaching mode
Innovative paths
Interdisciplinary talents
Submitted : 2026-03-08
Accepted : 2026-03-23
Published : 2026-04-07
Abstract
Amid the rapid evolution of the digital economy, the convergence of business intelligence (BI) and artificial intelligence (AI) has become a key driver of enterprise digital transformation, intensifying the demand for interdisciplinary professionals who possess both business acumen and technical expertise in intelligent systems. As an emerging interdisciplinary course that integrates computer science, management science, and statistics, Business Intelligence and Artificial Intelligence faces several pedagogical challenges. These include a disconnect between technical instruction and real-world business contexts, superficial integration of AI content into the curriculum, and a misalignment between practical training and current industry needs. Drawing on existing teaching reform literature and emphasizing the integrated nature of BI and AI education, this paper proposes a comprehensive teaching framework centered on content, methodology, practice, and assessment. Specifically, it outlines innovative pathways across four dimensions: redesigning curriculum content, transforming instructional approaches, constructing a multi-tiered practical training system, and refining evaluation mechanisms. Each pathway is discussed in terms of implementation strategies and necessary resource support, with a focus on applied instruction that embeds AI technologies within authentic business scenarios. The proposed model aims to enhance teaching quality and cultivate applied, interdisciplinary talent equipped to meet evolving industry demands.
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