Designing an AI-Enhanced Systems Analysis and Design Curriculum Framework to Develop Systems Analysts’ Competencies for the AI Era
DOI:
https://doi.org/10.57125/ELIJ.2026.09.25.07Keywords:
systems analysis and design, AI-integrated curriculum, systems analyst competencies, industry requirements, skills gap.Abstract
The rapid integration of artificial intelligence (AI) into software development has reshaped the competencies that systems analysts and designers require. At the same time, a persistent gap remains between the Systems Analysis and Design (SAD) curriculum and current industry needs. This study proposes a framework for an AI-integrated SAD curriculum that better meets modern labour-market demands without neglecting the discipline's fundamentals. This study adopted a qualitative conceptual research methodology, drawing on a structured analysis of recent literature on AI applications across the software development life cycle (SDLC), AI-enhanced workforce competencies, and challenges in computing curriculum development. The analysis identifies specific ways in which AI is reshaping analyst and designer work across SDLC phases — including AI-supported requirements elicitation and analysis, AI-assisted modelling and design, and AI-enabled testing and validation — and the corresponding competencies graduates need to work effectively in AI-based software development environments, such as the ability to direct, evaluate, and critically validate AI-generated outputs. These findings informed the proposed framework, which rests on three interconnected pillars: maintaining core SAD foundations, incorporating AI applications throughout the SDLC phases, and developing industry-oriented competencies. On this basis, the study advances an AI-Enhanced Systems Analysis and Design Curriculum that offers an evidence-based reference for curriculum developers and educators. Because the framework and the proposed curriculum have not yet undergone expert validation or educational implementation, they are presented as a preliminary, theoretically grounded proposal. Future research should evaluate and refine the framework through expert consensus and empirical assessment in academic settings.
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