Low-Code and No-Code Development in the Era of Artificial Intelligence: A Systematic Review

Abstract

Low-code, no-code has transformed software development by enabling non-programmers to build applications through visual interfaces. With the growing integration of artificial intelligence (AI), these platforms are evolving into intelligent environments that accelerate innovation and bridge the global shortage of skilled developers. This significance of this research is it clarifies how AI enhances LCNC development, a field increasingly central to digital transformation and automation. Using the systematic literature review method, the study gathered 1,582 initial records from Scopus, EBSCO, and AISeL, applying inclusion and exclusion criteria with PRISMA to arrive at 60 peer-reviewed journals published between 2020 and 2025. Each article was analyzed in terms of theoretical framework, industry context, development phase AI was integrated, challenges, and opportunities, with data thematically synthesized to trace emerging trends. The research found out that AI’s role in LCNC development is expanding and acting as co-developer increasing software reliability and adaptability. Results show that AI is primarily utilized in the development and maintenance phases of LCNC, functioning as a co-developer that automates code generation, debugging, and optimization. Most studies focus on applications in healthcare, manufacturing, logistics, and education, and finance, while theoretical engagement and diversity across industries remain limited. The study concluded that the convergence of LCNC and AI marks a shift toward intelligent, citizen-driven software development, underscoring the need for future research on theory, governance, and sector-specific best practices.

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