Leveraging AI Features in Oracle APEX for Smart Application Development

Oracle Application Express (APEX), traditionally known for its low-code capabilities and rapid application development model, is undergoing a transformative shift with the integration of Artificial Intelligence (AI) features. This review has explored how Oracle APEX now supports smart application development through built-in and external AI integrations, including predictive analytics, sentiment analysis, recommendation engines, and NLP-driven interfaces. Drawing on academic studies, industry implementations, and experimental results, this paper highlighted the measurable improvements in performance, usability, and business outcomes enabled by AI. It also addressed current challenges in model integration, explainability, and scalability. The article concludes by proposing future directions for research and practice aimed at enhancing AI adoption in APEX through modular architectures, governance frameworks, and responsible AI use.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-07-30
DOI
https://doi.org/10.30574/wjaets.2025.16.1.1239
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging AI Features in Oracle APEX for Smart Application Development

Sravana Kumar Yeruva
World Journal of Advanced Engineering Technology and Sciences
Big Data and Business Intelligence
article

Leveraging AI Features in Oracle APEX for Smart Application Development

Sravana Kumar Yeruva
article en

Abstract

Oracle Application Express (APEX), traditionally known for its low-code capabilities and rapid application development model, is undergoing a transformative shift with the integration of Artificial Intelligence (AI) features. This review has explored how Oracle APEX now supports smart application development through built-in and external AI integrations, including predictive analytics, sentiment analysis, recommendation engines, and NLP-driven interfaces. Drawing on academic studies, industry implementations, and experimental results, this paper highlighted the measurable improvements in performance, usability, and business outcomes enabled by AI. It also addressed current challenges in model integration, explainability, and scalability. The article concludes by proposing future directions for research and practice aimed at enhancing AI adoption in APEX through modular architectures, governance frameworks, and responsible AI use.

World Journal of Advanced Engineering Technology and SciencesVol. 16(1)
Openalex Percentile: Top 68%
Big Data and Business Intelligence
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