This presentation detailed the integration of generative artificial intelligence (AI) within undergraduate economics courses at Morehouse College, specifically in basic statistics, microeconomics, and principles of macroeconomics. Grounded in the Arrighi Spectrum AIC2 Utilization (2023), the instructional design moved beyond passive consumption toward autonomous, ethical innovation. In these courses, AI was systematically utilized to reorganize and optimize syllabi for better alignment with student learning objectives. To enhance engagement and accessibility, traditional course materials—including textbooks and PowerPoint presentations—were repurposed into dynamic, anime-style videos for macro and microeconomics. Additionally, AI was leveraged to develop customized, realworld case studies across all three disciplines, fostering deeper conceptual application. By applying the Arrighi AI-C2 framework, this approach prioritized the development of AI competence, ensuring that students transitioned from basic users to critical evaluators of digital tools. The results indicated that these AI-driven pedagogical shifts fostered increased student interest, enhanced critical thinking, and provided a more immersive learning experience in complex economic theories and statistical interpretations. This case study served as a blueprint for faculty seeking to bridge the gap between traditional economic instruction and the demands of the digital landscape.
Implementation steps and strategic initiatives
Jerry Pender Jr.'s integration of generative AI into undergraduate economics courses at Morehouse College offers a replicable model for HBCU business and economics programs nationwide. The first action step is to formally document the Arrighi Spectrum AI-C2 Utilization framework as an institutional instructional design standard, creating a written guide that maps each of its competency levels to specific course activities, assessment tasks, and AI tool applications. This documentation should be co-authored with faculty across the Division of Business and Economics to ensure disciplinary relevance and buy-in.
The anime-style video production workflow should be systematized into a repeatable process that other faculty can adopt without specialized media production skills. This involves identifying two or three accessible AI video generation platforms (such as Synthesia, HeyGen, or Pictory), developing a storyboarding template for economics concepts, and creating a faculty guide that walks through the production process step by step. A small media production fund should be established to cover platform subscriptions and any associated costs, with priority given to courses serving the largest student populations.
Customized real-world case studies developed through AI should be organized into a shared case study library, tagged by discipline (statistics, microeconomics, macroeconomics), difficulty level, and industry context. Faculty should review and update these cases annually to ensure they reflect current economic conditions and remain relevant to students' career aspirations. Student teams should be invited to contribute to case study development as a capstone project, building both AI competency and disciplinary knowledge simultaneously.
To institutionalize the approach, the Division of Business and Economics should incorporate AI competency benchmarks into its program learning outcomes and accreditation documentation. Alignment with AACSB or ACBSP standards for technology integration will strengthen the program's accreditation standing and signal to prospective students and employers that graduates possess contemporary digital skills. An annual AI in Economics Showcase event, where students present AI-assisted projects to faculty, alumni, and industry partners, would celebrate student achievement and build program visibility.