Consultant, Lead Writer​/Coordinator AI Preparedness Chapter “AI Early Warnings

Consultant, Lead Writer/Coordinator for the AI Preparedness Chapter for “AI for Early Warnings for All - A Resource for Action”

Apply for the role of Consultant, Lead Writer/Coordinator for the AI Preparedness Chapter for “AI for Early Warnings for All - A Resource for Action” at the International Federation of Red Cross and Red Crescent Societies (IFRC).

The Early Warnings for All (EW4

All) initiative is a global UN‑led effort to ensure that every person on Earth is protected by life‑saving early warning systems. Grounded in the four pillars of Risk Knowledge, Detection and Forecasting, Warning Dissemination and Communication, and Preparedness to Respond to Warnings, the initiative seeks data‑driven, inclusive, and scalable solutions.

Artificial Intelligence (AI) is a transformative enabler for early warning systems (EWS), processing vast data sources and enhancing forecasting, personalising communication, and optimising anticipatory and emergency response. Many vulnerable countries face barriers in applying AI effectively, from technical capacity to policy alignment.

The AI Sub‑Group of EW4

All is developing a Resource for Action – a practical, country‑focused publication that brings together AI opportunities, pilot case studies, tools, guidance, and country needs across all pillars.

The AI for Early Warnings for All – Resource for Action will serve as a resource for countries, practitioners, donors, and development partners seeking to deploy or scale AI‑enabled early warning systems. The target audience includes national governments, disaster risk management authorities, meteorological and hydrological agencies, international organisations, UN partners, donors, development banks, private sector AI providers, NGOs, civil society, and academic and research institutions.

The publication will support the integration of AI into multi‑hazard early warning systems by providing a practical, cross‑sectoral resource that aligns country needs with scalable, responsible AI solutions, enhances institutional and technical capacities, and fosters collaboration across the public‑private sector. It will clarify when AI offers an advantage over traditional approaches and when it may not be necessary, advancing the EW4

All vision of universal, timely, and technology‑enabled early warning coverage.

• Inception phase
  • Develop and submit an analysis plan.
  • Conduct a desk review of existing guidance, tools, and case studies relevant to AI for Preparedness to Respond to Warnings, covering preparedness, anticipatory action, and learning.
  • Coordinate with stakeholders, especially EW4
    
    All Pillar 4 partners, to call for submission of case studies and gather insights on relevant applications, tools, and guidance under development.
  • Propose a structure of the chapter, likely including:
  • Framework and principles for inclusion.
  • Conceptual diagram of how different tools can be used at different stages of the EWEA process.
  • Gap analysis.
• Drafting of chapter
  • Compile and/or review existing guidance, tools, and country examples.
  • Develop first full chapter draft to be submitted to ITU, as agreed with IFRC.
  • Coordinate inputs from any other staff or consultants, ensuring overall coherence and consistency.
• Validation and refinement
  • Facilitate a review and consultation process of the draft chapter with relevant stakeholders, including governments, Anticipatory Action Task Force (AATF), EW4
    
    All Pillar 4 group, Anticipation Hub and REAP Secretariat, and regional IFRC Anticipatory Action focal points.
  • Revise and refine the chapter contents based on consolidated feedback.
• Each Pillar chapter will follow a consistent structure, with an overall outline and case study template already developed:
  • Pillar overview and scope / potential for AI.
  • Case studies of AI country pilots in action.
  • Needs and gaps identified in countries.
  • Practical AI solutions (tools, technologies, and model examples).
  • Important considerations.

• Revised chapter outline based on desk review of literature and case studies.
• Methodology document, including detailed use of any AI applications.
• Summary of stakeholder consultations…