Digital Transformation of Risk Management Through Cloud Computing and Large Language Models

Abstract

Risk management in many organizations still depends on spreadsheets, email approvals, periodic reviews, and manual reporting. These practices cannot keep pace with the volume and speed of modern operational, financial, compliance, and cyber risks. Cloud computing and large language models (LLMs) together offer a path to transformation. Cloud platforms provide scalable, event-driven infrastructure for capturing and processing risk signals in real time, while LLMs can read, summarize, and reason over the large body of unstructured text on which risk decisions depend. Both technologies also introduce new risks: concentration on cloud providers, exposure of sensitive data, and LLM outputs that are fluent but wrong. This article proposes a framework for digitally transforming risk management using cloud computing and LLMs. Using a design-oriented approach grounded in ten studies published between 2016 and 2024, it combines configurable risk workflows, event-driven processing, privacy-preserving access control, retrieval-augmented LLM assistance, validated user interfaces, and AI governance. It maps the framework to each stage of the ISO 31000 risk management process and illustrates it with an insurance case involving a surge in claims after a regional flood. It argues that transformation succeeds when LLMs work within governed workflows and permission-aware data access, rather than as standalone tools.