Self Governing Artificial Intelligence Framework for Enterprise Operations Compliance Monitoring and Predictive Risk Analytics
DOI:
https://doi.org/10.15680/IJCTECE.2022.0506027Keywords:
Self-Governing Artificial Intelligence, Enterprise Operations, Compliance Monitoring, Predictive Risk Analytics, Machine Learning, Intelligent Automation, Business Intelligence, Enterprise Governance, Cloud Computing, Digital Transformation, Regulatory Compliance, Risk Management, Decision Intelligence, Data AnalyticsAbstract
The increasing complexity of enterprise operations and regulatory requirements has accelerated the adoption of Artificial Intelligence (AI) as a strategic tool for governance, compliance monitoring, and predictive risk management. A self-governing Artificial Intelligence framework integrates intelligent automation, machine learning, predictive analytics, and real-time monitoring to enable autonomous decision support while ensuring regulatory compliance and operational efficiency. Unlike conventional enterprise systems that depend heavily on manual intervention, self-governing AI continuously learns from organizational data, detects anomalies, predicts potential risks, and recommends corrective actions with minimal human supervision. Such frameworks combine advanced data analytics, business intelligence, cloud computing, and governance mechanisms to create adaptive systems capable of responding dynamically to evolving business environments. Compliance monitoring is strengthened through automated policy enforcement, continuous auditing, and intelligent reporting, while predictive risk analytics enhances organizational resilience by identifying financial, operational, cybersecurity, and regulatory risks before they materialize. This study explores the design and significance of self-governing AI frameworks for modern enterprises, emphasizing their role in improving decision-making, operational transparency, and business sustainability. Furthermore, the paper discusses technological components, governance principles, implementation strategies, and challenges associated with autonomous AI systems. The integration of intelligent governance and predictive analytics is expected to transform enterprise management by promoting efficiency, accountability, innovation, and long-term competitive advantage in digitally driven organizations.
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