Digital Frontline: An AI Role-Play Simulation of IT Support Crises in the Implementation of Agile-Blended Learning

The global shift to remote instruction has accelerated the adoption of frameworks like Agile-blended learning (ABL), yet the operational challenges of these technology-intensive models remain largely unexplored. This study addresses this “operational foresight gap” by examining the often-overlooked perspective of university IT support staff. Since ABL is a nascent framework lacking a large population of IT professionals to survey, we employed an exploratory artificial intelligence (AI) role-play methodology to generate simulated heuristics anticipating IT staff’s professional responses to five common ABL implementation scenarios. Data were generated using four distinct large language models: GPT-4.1, Gemini 2.5 Pro, Claude Sonnet 4, and DeepSeek R1. We analyzed the results through a structured thematic analysis. The simulations identified potential operational crises, including ecosystem fragmentation, unsustainable support workloads, and systemic instability caused by unvetted tools. Cross-model analysis revealed that while Western models focused on ecosystem integration, the non-Western model (DeepSeek R1) uniquely highlighted regional access barriers and low-cost open-source solutions. To mitigate these risks, the AI persona proposed unifying the technology ecosystem and adopting phased implementation strategies. However, successful execution requires specific resources, most notably increased specialized staffing, dedicated infrastructure funding, and the inclusion of IT leadership in strategic academic planning. The findings suggest that pedagogical innovation cannot succeed without a corresponding evolution in operational support. These AI-generated hypotheses indicate that universities need to help IT departments transition from reactive service providers to proactive strategic partners to ensure the sustainable implementation of flexible learning models.