Teaching Economical Writing in the Age of AI: A Process-Based Framework

The growing presence of generative artificial intelligence (AI) in undergraduate economics writing courses presents both opportunities and challenges. Instructors face concerns about academic integrity and assessing student effort, yet a process-based approach to writing offers a viable solution. This paper advocates for teaching economics writing as a structured, iterative process—encompassing brainstorming, outlining, researching, drafting, analyzing, revising, and reflecting—rather than as a singular final product. At each stage, AI can be strategically integrated to enhance, rather than replace, essential skills in economic reasoning, analysis, and communication. We introduce a framework grounded in two core principles: aligning AI tools with analog skills defined by course objectives and designing assessments that are observable and highly correlated with these skills. Additionally, we present practical classroom strategies and address concerns surrounding originality, equity, and evaluation. The paper also explores broader implications for scholarly production, including AI’s role in reshaping comparative advantages between human and artificial intelligence in academic work and their evolving intersection. Ultimately, this approach reimagines writing pedagogy to align with both disciplinary thinking and the realities of an AI-enhanced educational landscape.