Related papers: The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review

The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review

URL: http://arxiv.org/abs/2606.12423v1
Date: Sat, 09 May 2026 02:40:28 GMT
Title: The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review
Abstract summary: This paper presents a systematic literature review to examine the challenges of balancing AI compliance and technological innovation across critical infrastructure sectors.<n>The study identifies three interrelated challenges: fragmented regulations, excessive compliance burdens for smaller to medium enterprises (SMEs), and misaligned governance models.<n>To address these challenges, the study highlights practical governance strategies, including risk-tiered regulation, compliance by design, and explainable AI, to support scalable and trustworthy AI deployment in critical sectors.
Score: 0.0
License: http://creativecommons.org/licenses/by/4.0/
Abstract: The rapid integration of artificial intelligence (AI) into critical infrastructure including healthcare, finance, energy, and defense, offers transformative benefits but also conflicts with evolving regulatory and governance frameworks. This paper presents a systematic literature review (SLR) to examine the challenges of balancing AI compliance and technological innovation across critical infrastructure sectors. The review follows established SLR guidelines to extract and synthesize insights from peer-reviewed articles, report, and institutional sources published between 2020-2025. The study identifies three interrelated challenges: fragmented regulations, excessive compliance burdens for smaller to medium enterprises (SMEs), and misaligned governance models. To address these challenges, the study highlights practical governance strategies, including risk-tiered regulation, compliance by design, and explainable AI, to support scalable and trustworthy AI deployment in critical sectors. Key contributions include a concise mapping of core AI-governance challenges and a conceptual diagram illustrating their overlap, as well as actionable strategies for policymakers and practitioner to harmonize oversight with innovation.

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