The rapid pace of technological innovation, globalization, and environmental change is generating a new class of emerging risks that are complex, uncertain, and cross-sectoral. These risks, ranging from climate–energy transitions and digital vulnerabilities to biosecurity and resource scarcity, cannot be understood through single-disciplinary lenses. Addressing them requires integrated and collaborative approaches that combine insights from science, engineering, data analytics, and social sciences. This paper explores how interdisciplinary frameworks enhance our ability to identify, assess, and manage emerging risks in dynamic systems. It highlights critical intersections such as the climate–energy–infrastructure nexus, artificial intelligence and ethics, and health environment interactions, where risks evolve through interlinked feedbacks. By connecting technical innovation with socio-economic and governance perspectives, interdisciplinary research promotes holistic understanding and more adaptive policy responses. We argue that resilience in modern societies depends on bridging disciplinary boundaries to anticipate systemic vulnerabilities before they escalate. Emerging tools such as machine learning, network modeling, and systems analysis can support this transition by revealing hidden dependencies and cascading effects. Strengthening cross-sectoral collaboration, transparent data exchange, and adaptive governance will be vital for transforming risk management from reactive control to proactive foresight. In summary, managing emerging risks demands a shift toward integrative, interdisciplinary thinking that transforms uncertainty into knowledge and builds sustainable, resilient futures.