Enhancing Business Model Validation Using Artificial Intelligence: Insights from Student Business Model Canvas Analysis

Dimas Setiawan (Universitas PGRI Madiun)
Ridho Pamungkas (Universitas PGRI Madiun)
Mei Lenawati (Universitas PGRI Madiun)
Noordin Asnawi (Universitas PGRI Madiun)

Formosa Journal of Computer and Information Science
Vol. 5 No. 1 (2026): March 2026

This study aims to identify common weaknesses in students’ Business Model Canvas (BMC) and examine the role of Artificial Intelligence (AI) in improving early-stage business validation. A qualitative descriptive approach was employed using aggregated and anonymized data from 30 student business models. Data were analyzed using thematic coding to identify recurring patterns. The findings reveal that 70% of students struggle with unclear value propositions, 63% define overly broad customer segments, and 57% lack structured revenue models. AI-assisted analysis improves clarity, focus, and logical consistency of business models. This study proposes an AI-BMC conceptual framework as a decision-support approach for entrepreneurship learning. The findings contribute to bridging intuitive business ideation with AI-assisted validation.