Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond

Source

• Source name: arXiv
• Source kind: paper
• Authors / organization: Javier Irigoyen, Roberto Daza, Aythami Morales, Julian Fierrez, Ruben Tolosana, Ruben Vera-Rodriguez, Francisco Jurado, Alvaro Ortigosa
• Venue: arXiv: cs.CY
• Published: 2026-07-02
• Collected: 2026-07-03
• URL: http://arxiv.org/abs/2607.02197v1
• PDF: https://arxiv.org/pdf/2607.02197v1
• DOI: UNKNOWN

Plain-Language Brief

This paper provides an overview of methods for assessing and managing risks associated with intelligent systems, as required by emerging regulatory frameworks. It reviews various types of AI-related risks, existing methodologies for assessment, best practices, and areas needing further research.

What the Document Says

• The need for rigorous risk assessment in AI systems is emphasized due to societal concerns and emerging regulations.
• The paper discusses the global regulatory landscape that necessitates systematic AI risk assessment.
• AI-related risks are categorized, including technical failures and ethical/social impacts.
• Key risk assessment methodologies for AI systems are reviewed, focusing on general frameworks.
• Best practices in AI risk assessment are highlighted.
• Methodological gaps are pointed out, suggesting opportunities for further research.

Key Concepts Mentioned

• Risk Assessment
• AI Systems
• Regulatory Frameworks
• AI-related Risks
• Technical Failures
• Ethical and Social Impacts
• Methodologies

Claims Made by the Document

• Rigorous risk assessment is needed for safe and reliable AI systems.
• Existing methodologies can be applied to AI risk assessment.
• Best practices exist in AI risk assessment.

Evidence Used

• Discussion of the need for rigorous risk assessment.
• Review of existing methodologies for AI risk assessment.
• Highlighting of best practices in the paper.

Methods / Approach

UNKNOWN

Limitations Stated by the Authors

UNKNOWN

Limitations Noted by the Agent

Agent interpretation — not from the source.

UNKNOWN

Open Questions

• What are the specific regulatory frameworks mentioned in the text?
• What is the scope and application of the reviewed methodologies for AI risk assessment?

Notes for Future Q&A

May include interpretation. Labeled where it does.

• The paper does not specify which specific regulatory frameworks are being referred to.
• Details about the scope and application of methodologies discussed in the paper are not provided.

Raw Abstract / Excerpt

The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this imperative, this paper presents an overview of AI risk assessment (identification and analysis) and management methodologies. It begins by reviewing the worldwide regulatory landscape that drives the need for systematic AI risk assessment. Then we characterize the spectrum of AI-related risks identified in the literature, from technical failures to ethical and social impacts. Subsequently, it reviews key risk assessment methodologies proposed for AI systems, focusing on general frameworks. The paper highlights best practices and illuminates methodological gaps, highlighting areas for further research on AI risk assessment.