The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review
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Abstract (arXiv)
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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References · 9
- 2020Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditingcited by 380
- 2023A Pathway Towards Responsible AI Generated Contentcited by 38
- 2022UX Research on Conversational Human-AI Interaction: A Literature Review of the ACM Digital Librarycited by 20
- 2023Responsible AI Governance: A Systematic Literature Reviewcited by 4
- 2023Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature Reviewcited by 3
- 2021Symbiotic System of Systems Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farmscited by 2
- 2025Between Innovation and Oversight: A Cross-Regional Study of AI Risk Management Frameworks in the EU, U.S., UK, and Chinacited by 2
- 2023Assessing the impact of regulations and standards on innovation in the field of AIcited by 1
- 2023Applications and Societal Implications of Artificial Intelligence in Manufacturing: A Systematic Reviewcited by 1
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