Improving risk management processes through the integration of advanced technologies
DOI:
https://doi.org/10.55873/rad.v4i1.369Keywords:
adoption, capacity building, infrastructure, mitigation, predictionAbstract
Risk management in processes has made significant advancements with the integration of advanced technologies, such as artificial intelligence (AI) and machine learning (ML), which enable greater accuracy and efficiency in decision-making. This article reviews the impact of these technologies on improving risk management, analyzing various studies on their implementation in sectors such as healthcare, energy, logistics, and finance. It explores how the use of these tools has optimized risk assessment and mitigation, enhancing predictive capabilities and reducing exposure to adverse events. However, it also identifies challenges in their adoption, such as data quality, integration with existing systems, and the need for skilled personnel. The findings indicate that, while advanced technologies have great potential to improve risk management processes, their effective implementation requires appropriate infrastructure and specialized technical training. This study contributes to understanding the benefits and limitations of these technologies in enhancing risk management.
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Copyright (c) 2025 Zamora-Pastor, Antonio, Brisa Gabriela Llanos-Atachahua, Nikolai Lance Cauper-Acuña, Yngue Elizabeth Ramírez-Pezo
This work is licensed under a Creative Commons Attribution 4.0 International License.
