Implementing Adaptive AI Governance Frameworks for Real-Time Data Stream Management and Quality Assurance

• Author(s): Adedayo Hakeem Kukoyi
• Paper ID: 1712736
• Page: 1156-1161
• Published Date: 30-04-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 10 April-2023

Abstract

The horizon of artificial intelligence (AI) technologies is expanding, as is the need for effective governance structures that align with the real-time flow of data. This study provides a comprehensive examination of adaptive AI governance structures for managing and ensuring the quality of real-time data streams. A quantitative strategy was employed by circulating structured questionnaires to data scientists, IT managers, and AI policy makers in technology companies. The data were analyzed using basic descriptive statistics, including frequencies and percentages. The study identified adaptability, transparency, and accountability as fundamental cornerstones of dynamic data environments. This study advocates incorporating adaptive feedback systems into AI governance to promote compliance, ethical alignment, and data fidelity. It is recommended that organizations and policymakers design and operationalize flexible, context-sensitive governance frameworks that preserve data quality and promote trust in automated decisions.

Keywords

AI Governance, Data Quality, Real-Time Data Streams, Adaptive Framework, Accountability, Transparency.

Citations

IRE Journals:
Adedayo Hakeem Kukoyi "Implementing Adaptive AI Governance Frameworks for Real-Time Data Stream Management and Quality Assurance" Iconic Research And Engineering Journals Volume 6 Issue 10 2023 Page 1156-1161 https://doi.org/10.64388/IREV6I10-1712736

IEEE:
Adedayo Hakeem Kukoyi "Implementing Adaptive AI Governance Frameworks for Real-Time Data Stream Management and Quality Assurance" Iconic Research And Engineering Journals, 6(10) https://doi.org/10.64388/IREV6I10-1712736