Ethical AI Integration in Salesforce: A Framework for Privacy, Fairness, and Accountable Implementation
Year: 2025
Type: article
Abstract: This article examines the multifaceted ethical challenges emerging from the integration of artificial intelligence within Salesforce platforms and proposes a comprehensive framework for addressing these concerns. As organizations increasingly deploy AI-powered solutions for customer relationship management, questions regarding data privacy, algorithmic bias, transparency, and accountability have become paramount. Through analysis of current implementation practices and regulatory landscapes, the article identifies critical vulnerabilities in existing approaches and demonstrates how these issues can undermine both customer trust and business outcomes. The article introduces structured governance mechanisms and technical safeguards that Salesforce architects and administrators can implement to ensure AI systems operate fairly and transparently while maintaining robust privacy protections. By synthesizing insights from both technical and ethical perspectives, this article contributes to the evolving discourse on responsible AI deployment in enterprise environments and offers actionable guidance for practitioners seeking to balance innovation with ethical considerations in Salesforce implementations.
Author: Ketankumar Hasmukhbhai Patel
Institution: University of Florida
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410535174