AI-Driven Risk Prediction for Humanitarian Operations

Use Case:

Integration of predictive analytics scenario simulation and multi-source data fusion to support NGOs and international agencies in anticipating crises optimizing project monitoring.

Outcome:

Structured feasibility plan and business model for AI adoption; Defined technical architecture for an AI-driven Minimum Viable Product (MVP); Validation roadmap for real-world implementation via business experiments; Decision-support functionalities aligned with NGO operational needs.

Ecosystem Support:

StairwAI mentoring (technical and business); guidance for feasibility planning and AI strategy formulation; structured support for MVP design and TRL development.

AI Relevance:

This success story demonstrates the value of AI for social good and digital transformation in humanitarian contexts through: I) accessible decision-support platforms built on AI components; II) AI-assisted risk forecasting combining structured and unstructured data; III) integration of predictive models into user-friendly interfaces for crisis management; IV) iterative business experimentation to ensure alignment with stakeholder needs.

Summary:

CMC, a Norwegian consultancy firm specializing in innovation for humanitarian operations, addressed the pressing need for predictive tools in crisis-prone environments. Within the StairwAI support framework, the team developed AICAPS—a proactive, AI-driven platform aimed at helping NGOs, development agencies, and public bodies anticipate risks, monitor projects in unstable regions, and take data-informed decisions. The system is designed to merge diverse data streams, run scenario simulations, and deliver forecasts through an intuitive interface tailored to field operators. The team produced a comprehensive feasibility plan outlining technical components such as data integration, model adaptability, and automated workflows. Parallelly, a robust business model was formulated, targeting scalable adoption through subscriptions, consultancy, and licensing. Post-program activities include the development of a Minimum Viable Product (MVP), pilot testing with end-users, and refinement based on feedback. AICAPS aspires to bridge the gap between high-level predictive analytics and real-world humanitarian decision-making, evolving into a critical asset for risk-informed operations globally.