Machine Learning Enabled Governance Framework for Autonomous Enterprise Platforms and Intelligent Data Ecosystems
DOI:
https://doi.org/10.15680/IJCTECE.2024.0706024Keywords:
Machine Learning Governance, Autonomous Enterprise Platforms, Intelligent Data Ecosystems, AI Governance Framework, Data Governance, Responsible AI, Enterprise Automation, Explainable AI, Compliance Management, Intelligent Decision SystemsAbstract
The rapid expansion of digital technologies has led to the emergence of autonomous enterprise platforms and intelligent data ecosystems that rely heavily on advanced analytics, automation, and artificial intelligence. As organizations increasingly adopt data-driven decision-making processes, the need for robust governance frameworks that ensure transparency, accountability, security, and ethical use of machine learning systems has become critical. This research proposes a Machine Learning Enabled Governance Framework designed to manage and regulate autonomous enterprise platforms and intelligent data ecosystems effectively. The framework integrates machine learning models with governance mechanisms such as policy enforcement, compliance monitoring, data quality management, and risk assessment to support responsible data utilization and automated decision-making.
The proposed governance architecture enables enterprises to monitor AI-driven systems continuously, detect anomalies in data operations, and ensure regulatory compliance across complex digital infrastructures. By incorporating automated auditing, explainable AI mechanisms, and policy-based access controls, the framework promotes transparency and trust in enterprise-level machine learning applications. The research methodology combines conceptual modeling, comparative analysis of existing governance frameworks, and simulation-based evaluation to validate the effectiveness of the proposed model. The findings indicate that machine learning-enabled governance frameworks can significantly enhance operational efficiency, reduce compliance risks, and improve the reliability of autonomous enterprise systems while ensuring responsible data management within intelligent data ecosystems.
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