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An Empirical Study on Enterprise-Wide Governance Practices for Artificial Intelligence and Machine Learning

Year: 2024

Type: article

Abstract: This study examines the current state of enterprise-wide governance practices for artificial intelligence (AI) and machine learning (ML) across various industries. A survey of 60 participants reveals insights into how organizations define, manage, and govern AI/ML technologies. Key findings highlight significant progress in establishing governance frameworks while identifying critical gaps that require attention. This paper discusses these findings and provides recommendations for enhancing AI/ML governance practices to ensure ethical, transparent, and effective deployment of AI/ML technologies.

Source: European Journal of Applied Science Engineering and Technology

DOI: 10.59324/ejaset.2024.2(6).16

Authors: John Giordani, Renato Zeko

Institutions: University of Fairfax, United Nations

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W4405944697

FWCI: 0.824

Cites: 20

Cited by: 2

Related to: 10