Pioneering Ethical AI Integration in Enterprise Workflows: A Framework for Scalable Team Governance

Authors

  • Venkatraman Viswanathan

Keywords:

Ethical AI, Workflow Efficiency, Enterprise AI Governance, ANOVA, Team Performance, Confidence Intervals, Scalable AI Integration, Fairness in AI Systems

Abstract

As generative AI systems become embedded across enterprise functions, the need for ethical oversight at the workflow level is more critical than ever. This paper presents a practical and scalable framework for integrating ethical principles directly into AI-assisted enterprise workflows, with a focus on project-driven teams in sectors such as IT services, HR-tech, and digital transformation. The study illustrates how organizations can operationalize fairness, transparency, accountability, and explainability using modular AI governance components. The framework enables project teams to map ethical checkpoints to assigned resources, decision automation, or AI-generated recommendations. Supported by qualitative insights and simulated enterprise use cases, the model demonstrates how responsible AI deployment can reduce onboarding bias, improve accuracy in team orchestration, and increase stakeholder trust in AI-generated outcomes. This research contributes to the emerging domain of AI governance by bridging the gap between high-level ethical principles and daily enterprise implementation, offering a repeatable and actionable model for organizations seeking to future-proof their AI practices.

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Published

29.09.2024

How to Cite

Venkatraman Viswanathan. (2024). Pioneering Ethical AI Integration in Enterprise Workflows: A Framework for Scalable Team Governance. International Journal of Intelligent Systems and Applications in Engineering, 12(23s), 3544 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7772

Issue

Vol. 12 No. 23s (2024)

Section

Research Article

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