Abstract:

Modern management and technical leadership courses increasingly emphasize the ability to apply frameworks, evaluate trade-offs, and make decisions under uncertainty. Yet students often have limited opportunities to practice these skills in a structured way. At the same time, freely available generative AI tools tend to provide unstructured answers that can shortcut learning. Engent Labs was developed to address this challenge by offering an instructor-aligned, reasoning-first AI platform specifically designed for management and decision-making education.

Engent Labs organizes every response into three pedagogical layers: a strategic-thinking lens grounded in course frameworks, targeted follow-up prompts that encourage deeper reflection, and a curated set of concepts extracted directly from instructor-provided materials. This structure keeps students anchored in the logic of the course while giving them space to explore cases, scenarios, and judgment calls. The platform’s design explicitly avoids over-reliance on numerical or computational tasks, recognizing current limitations of large language models and focusing instead on areas where AI can meaningfully strengthen managerial reasoning.

Across multiple deployments in a graduate-level decision-making course, students highlighted two consistent benefits: “helped me apply decision-making frameworks” and “good for connecting ideas.” They also viewed follow-up prompts as supportive tools that “encourage deeper thinking” and help integrate concepts across modules. Early pilots additionally surfaced practical insights—such as the need for smoother technical access, guided onboarding, and dedicated in-class demonstration time—which have led to targeted updates improving the first-time user experience and reliability.

This presentation will share Engent Labs’ design principles, backend architecture, and measurable classroom outcomes. It will also discuss responsible AI considerations, including transparency, boundaries for numerical tasks, and course-level strategies for integrating AI without eroding academic integrity. Taken together, the findings illustrate a practical, scalable pathway for adopting human-centered AI tools that enhance strategic reasoning, support instructor goals, and foster deeper understanding in management education.

Keywords:

AI-supported learning, management education, active learning, decision-making, responsible AI, higher education innovation, learning technologies, GPT-based tutoring, pedagogical design, strategic reasoning.