Authors:
Gayane Sedrakyan
1
;
Stephan Braams
1
;
2
;
Cosmin Ghiauru
1
;
Anton Tsankov
1
;
Stijn Schuurman
1
;
Matthijs Jansen op de Haar
1
;
Valeri Andreev
1
and
Jos van Hillegersberg
1
Affiliations:
1
Department High-Tech Business and Entrepreneurship (HBE) Section, Industrial Engineering and Business Information Systems (IEBIS), University of Twente, Enschede, Overijssel, Netherlands
;
2
Cape Groep, Enschede, Overijssel, Netherlands
Keyword(s):
Low-Code, Model-Based System Development, Business Models, Business Model Canvas, AI-Enabled Modeling, Requirements Engineering for Low-Code, Citizen Development.
Abstract:
Low-code development platforms (LCDPs) are transforming business practices by shifting the focus from traditional, code-intensive approaches to business-centered modeling. These platforms enable citizen developers - non-technical employees within organizations - to build and manage applications that address specific business needs. This democratization accelerates time-to-market and encourages agile, co-participatory development. However, the rise of citizen development also introduces challenges, such as risks to quality, security, and governance, due to limited technical expertise among some users. This paper investigates ways to enhance current low-code practices by integrating AI-based support for text-to-model generation and established business frameworks, such as the Business Model Canvas (BMC). Incorporating BMC into low-code platforms reinforces their core strengths - minimizing code dependency while grounding development in business models. This integration can offer a stru
ctured pathway for citizen developers to engage in meaningful learning while ensuring their projects align with organizational objectives. This approach positions low-code not only as a productivity tool aiming faster time to market, but as platforms for continuous learning and strategic alignment with business. The proposed integrations build on a novel feedback-inclusive approach, which received the innovative feedback nomination at the University of Leuven, Belgium1, and was informed by evidence-based learning experiences at the University of Twente, Netherlands.
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