Overview of Risk Assessment and Management for Intelligent Systems under the AI Act and Beyond
arXiv:2607.02197v1 Announce Type: cross Abstract: 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 impact
The paper is published as regulatory frameworks like the AI Act are solidifying, necessitating practical applications for risk assessment and management regarding emergent AI systems.
This publication provides a critical overview for understanding and navigating the regulatory landscape and practical requirements for developing and deploying AI systems, impacting industries and governance.
The focus is shifting from general AI development to a more disciplined, risk-aware approach, integrating regulatory compliance and ethical considerations as foundational elements from the outset.
- · AI Governance & Compliance Software
- · Legal & Consulting Firms (AI Focus)
- · AI Developers (Risk-Aware)
- · Regulatory Bodies
- · AI Developers (Non-Compliant)
- · Companies with Legacy AI Systems
- · Unregulated AI Applications
Companies will increase investment in AI risk assessment tools and compliance departments.
A new ecosystem of specialized AI risk management and assurance services will emerge to support compliance.
Stricter regulatory environments may lead to a consolidation of AI development among larger, more compliant entities or a fragmentation of high-risk AI innovation in less regulated regions.
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Read at arXiv cs.AI