Leveraging AI for Enhanced Salesforce Development : A Comprehensive Study of LWC, Apex, and AI Tools
Saini, Vanshika; Rawat, Anu (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051311463
https://urn.fi/URN:NBN:fi:amk-2025051311463
Tiivistelmä
This study was carried out to examine and explore the optimization of the Salesforce platform using Artificial Intelligence, by comparing code generated by AI tools like ChatGPT with the code manually written code. Salesforce is one of the most well-known and widely used Customer Relationship Management (CRM) platforms. It offers the development tools like Apex and Lightning web components (LWC), which are used to build the applications. Traditionally used development methods used to require a lot of time and effort from developers, which posed greater challenges, especially for those developers who are new to the platform.
We built a Lightning Web Runtime (LWR) Rental shop website to study the impact of AI assisted coding. The component was first manually developed, and then the same functionality was generated with AI-assistance, by giving specific prompts to ChatGPT. The effectiveness of the AI tool was evaluated based on specific metrics, development time, the code accuracy, maintainability code, and its capability to resolve errors.
The findings revealed that AI-assisted development significantly reduced coding time and improved error detection. AI-generated code, however, required manual refinement to align with best practices and specific project requirements. While AI tools enhanced efficiency and served as a valuable learning aid, human oversight remained necessary to ensure security, contextual accuracy, and compliance with development standards. These insights contribute to understanding AI’s potential in Salesforce development and provide recommendations for integrating AI-driven coding approaches into professional workflows.
We built a Lightning Web Runtime (LWR) Rental shop website to study the impact of AI assisted coding. The component was first manually developed, and then the same functionality was generated with AI-assistance, by giving specific prompts to ChatGPT. The effectiveness of the AI tool was evaluated based on specific metrics, development time, the code accuracy, maintainability code, and its capability to resolve errors.
The findings revealed that AI-assisted development significantly reduced coding time and improved error detection. AI-generated code, however, required manual refinement to align with best practices and specific project requirements. While AI tools enhanced efficiency and served as a valuable learning aid, human oversight remained necessary to ensure security, contextual accuracy, and compliance with development standards. These insights contribute to understanding AI’s potential in Salesforce development and provide recommendations for integrating AI-driven coding approaches into professional workflows.