A Future-Ready Framework for Digital Risk Management and Configurable Cloud-Based Enterprise Workflows

Abstract

Digital risk management systems are usually designed for the risks, regulations, and technologies of the moment. Within a few years, new risks appear, regulations such as the European Union's Artificial Intelligence Act impose new obligations, AI models age, cloud costs and energy use rise, and the platform itself becomes hard to change. This article asks what makes a risk management platform future-ready and proposes a framework to achieve it. The framework defines six readiness dimensions: evolvability, continuous AI improvement, resilience, regulatory readiness, sustainability, and portability. It realizes them through a layered architecture. A metadata and configuration layer holds risk definitions, workflow rules, and model settings so they can change without code. Configurable workflows and AI risk services deliver risk decisions. An AI operations layer updates models without downtime and recovers from failures automatically. A governance layer maps regulatory requirements to evidence the platform produces. A portable, energy-aware cloud layer hosts everything. Using a design-oriented approach grounded in eleven studies published between 2004 and 2024, the article maps the evidence base, defines the readiness dimensions, describes the architecture, maps AI regulation to platform mechanisms, and sets out an evolution loop. It illustrates the design with a tax administration managing taxpayer compliance risk. It argues that future-readiness is not a prediction of the future but a capacity to change safely, cheaply, and with evidence.