EU AI Act Underrepresented and Insufficient to Address the Risk and Vulnerabilities of Generative AI

This study conducts a systematic evaluation of the European Union Artificial Intelligence Act, assessing its regulatory alignment with the rapidly evolving risk landscape posed by Generative AI systems. Employing large language models within a governance-oriented analytical framework, the analysis critically examines the extent to which the Act addresses foundational concerns such as algorithmic fairness, model explainability, environmental sustainability, and financial stability. While the Act advances transparency and accountability, analysis reveals notable limitations in operational guidance and alignment with high-level ethical principles. Overall, the Act represents a positive foundation, yet targeted enhancements are essential for enabling responsible innovation and ensuring that Generative AI advances align with societal and economic values. The proposed framework also enables practical self-audits and supports future regulatory design, making it a valuable tool for both public and private stakeholders.

Authors

Institutions

Publication Details

Journal
International Journal of Business Analytics
Published
2025-09-23
DOI
https://doi.org/10.4018/ijban.388757
Primary Topic
Law, AI, and Intellectual Property
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

EU AI Act Underrepresented and Insufficient to Address the Risk and Vulnerabilities of Generative AI

Nisha Mary Thomas, Sridhar Jonnala, Pramod Kumar Parida
International Journal of Business Analytics
Law, AI, and Intellectual Property
article

EU AI Act Underrepresented and Insufficient to Address the Risk and Vulnerabilities of Generative AI

Nisha Mary Thomas, Sridhar Jonnala, Pramod Kumar Parida
article en

Abstract

This study conducts a systematic evaluation of the European Union Artificial Intelligence Act, assessing its regulatory alignment with the rapidly evolving risk landscape posed by Generative AI systems. Employing large language models within a governance-oriented analytical framework, the analysis critically examines the extent to which the Act addresses foundational concerns such as algorithmic fairness, model explainability, environmental sustainability, and financial stability. While the Act advances transparency and accountability, analysis reveals notable limitations in operational guidance and alignment with high-level ethical principles. Overall, the Act represents a positive foundation, yet targeted enhancements are essential for enabling responsible innovation and ensuring that Generative AI advances align with societal and economic values. The proposed framework also enables practical self-audits and supports future regulatory design, making it a valuable tool for both public and private stakeholders.

International Journal of Business AnalyticsVol. 12(1)
International Institute of Information Technology Bangalore (IN), IBM (India) (IN), International School of Management (FR)
Openalex Percentile: Top 86%
Law, AI, and Intellectual Property
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.