Special Issue on Next-Generation AI and Intelligent Technologies in Engineering: Risks, Opportunities and Responsible Integration

Introduction:

Rapid advances in next-generation artificial intelligence (AI) and intelligent technologies, including generative AI, large language models, agentic AI, autonomous and multi-agent systems, quantum AI, intelligent digital twins and robotics, are reshaping engineering systems, processes and decision-making. These technologies offer new opportunities to enhance risk assessment, safety, reliability and resilience while introducing complex uncertainties and emerging risks associated with autonomy, interconnectedness, model limitations and technological integration.

As intelligent technologies become increasingly embedded in engineering applications, particularly safety-critical and high-consequence environments, conventional approaches to risk identification, analysis, assessment and management face new challenges. Understanding the risks introduced by these technologies, alongside their potential to strengthen risk science methodologies, is essential for their safe and responsible integration.

This special issue presents theoretical, methodological, computational and empirical advances addressing the opportunities, challenges and risk implications of next-generation AI and intelligent technologies in engineering. It brings together interdisciplinary research on emerging technological risks, advanced risk analysis, uncertainty quantification, safety assurance, resilience and risk-informed governance. Contributions supporting trustworthy, reliable and responsible integration throughout the engineering lifecycle are particularly encouraged.

Topics covered:

• Generative AI and large language models in engineering risk assessment and management.
• Agentic AI and autonomous engineering workflows: risks, safety, reliability, and governance.
• Multi-agent AI systems, autonomous interactions, and systemic or cascading risks.
• AI hallucinations, model uncertainty, and reliability in engineering decision-making.
• Advanced AI for hazard identification, risk modelling, uncertainty quantification, and prediction.
• Quantum computing and quantum AI: opportunities, uncertainties, and engineering risks.
• Intelligent digital twins, robotics, and cyber-physical systems for engineering risk management.
• Cybersecurity, privacy, data protection, and interconnected risks in intelligent engineering systems.
• Human-AI interaction, trust, risk perception, and human oversight in engineering.
• Verification, validation, monitoring, and safety assurance of AI-enabled engineering systems.

Important deadlines:

• Submission deadline: 1 June 2027

Submission instructions:

Please read the Guide for Authors before submitting. All articles should be submitted online, please select SI: AI and engineering risk on submission.

Guest editors:

• Dr M.K.S. Al-Mhdawi, Trinity College Dublin, Ireland. Email:(almhdawm@tcd.ie).
• Professor Bilal M. Ayyub, University of Maryland, United States. Email: (ba@umd.edu).
• Dr Charf Mahammedi, Teesside University, United Kingdom. Email: (C.Mahammedi@tees.ac.uk).
• Dr Udechukwu Ojiako, Indiana State University, United States. Email: (Udechukwu.Ojiako@indstate.edu).