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

The Early Warnings for All (EW4All) initiative is a global UN-led effort to ensure that every person on Earth is protected by life-saving early warning systems. Grounded in four pillars - Risk Knowledge (UNDRR), Detection and Forecasting (WMO), Warning Dissemination and Communication (ITU), and Preparedness to Respond to Warnings (IFRC) - this initiative requires data-driven, inclusive, and scalable solutions.

Artificial Intelligence (AI) has emerged as a transformative enabler for early warning systems (EWS), helping to process vast data sources including risk-related data sources, enhance forecasting, personalise communication, and optimise anticipatory and emergency response efforts. However, many countries, especially those most vulnerable to climate and disaster risk, face barriers in applying AI effectively, ranging from technical capacity and data access to policy alignment and implementation support.

To bridge this gap, the AI Sub-Group of the EW4All initiative is developing a Resource for Action - a practical, country-focused, and solutions-oriented publication that brings together AI opportunities, pilot case studies, tools, guidance, and country needs across all four EW4All pillars.

The IFRC has been tasked to lead the coordination and write up on the chapter related to Pillar 4 of Early Warning Systems on ‘AI for Preparedness to Respond to Warnings’ which covers areas of preparedness for response and early action, including the funding, activation and operational implementation and learning of anticipatory humanitarian action.

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

The publication aims to 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. Importantly, it not only illustrates how AI can be used, but also clarifies when AI offers a real advantage over traditional approaches and when it may not be necessary. This will help advance the EW4All vision of universal, timely, and technology-enabled early warning coverage. The publication will be co-developed and co-published by the four EW4All pillar leads (UNDRR, WMO, ITU, IFRC), with chapters organised by pillar and led by the respective organisations. ITU will lead overall coordination, in close cooperation with a designated focal point from each Pillar. This Resource will be published as an interactive, PDF-based digital resource, hosted on the EW4All AI Sub-Group and co-author websites.

This consultancy will support IFRC with the coordination to gather inputs and case studies from partner organization for the assigned chapter on pillar 4 and will lead the drafting of the chapter including incorporating review comments.

Inception phase

• Develop and submit an analysis plan
• Conduct a desk review of existing guidance and tools and case studies relevant to the application of AI for Preparedness to Respond to Warnings, covering preparedness, anticipatory action and learning.
• Coordinate with stakeholders especially EW4All Pillar 4 partners to call for submission of case studies and gather insights on relevant applications, tools, guidance under development and/or tested.
• Based on the above, propose a structure of the chapter, to likely include:
  • 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), EW4All 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, and overall outline and case study template has already been 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

Key deliverables

• 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 presented in compelling format
• Draft Chapter on AI for Pillar 4 – Preparedness to Respond to Warnings
• Framework for future inclusion of AI applications for Preparedness to Respond
• Revised final chapter addressing comments from peer review

Timeframe

The consultancy is expected to last approximately 2 months from January to February, with the possibility of completion in a shorter timeframe.

• Literature desk review and stakeholder consultation: 31 January 2026
• Partner case studies submission: 31 January 2026
• First Chapter draft: 12 February 2026
• Revised chapter draft: 28 February 2026

Outside the consultancy timeframe a peer review will take place from 14-30 March 2026 with the final full toolkit to be finalized by ITU by 10 April.

We are particularly interested in candidates who can dedicate substantial time to the assignment and work full-time whenever possible to ensure timely delivery of outputs. Flexibility in scheduling will be appreciated, but responsiveness and availability during key periods will be critical.

Reporting and communication

The consultant will report to IFRC IM Lead and work closely with IFRC DRR Resilience Lead and IFRC EW4All Coordinator as well as the focal point at ITU coordinating the overall toolkit development and liaison with relevant experts from EW4All Pillar 4 partners such as Anticipation Hub/German RC, Red Cross Red Crescent Climate Centre, REAP, and partners such as WFP, FAO and OCHA, Start Network.

If additional staff or consultants are brought on to support the development of chapter, the consultant will ensure integration and coherence across the deliverables.

Regular meetings will be held to discuss progress, plans and challenges, and for any strategic decision-making. The consultant will also be expected to share progress updates in a proactive and timely manner outside of these meetings.

Location

This consultancy is home-based/remote.

Budget and payment

Estimate number of days for the assignment are 20 days.

The consultancy fee will be negotiated based on the scope of work, estimated level of effort, consultant’s qualifications, relevant experience and alignment with IFRC’s remuneration policies. Payments will be made in accordance with agreed-upon milestones and deliverables outlined above.

Required

• Demonstrated experience and expertise in disaster risk management and anticipatory action.

Preferred

• Preferably within the context of the international humanitarian organizations, the Red Cross and Red Crescent Movement and/or within the context of government systems.

Required

• Fluency in English.
• Demonstrated expertise in application of Artificial Intelligence tools.
• Excellent writing and communication skills.
• Proven track record in developing guidance, tools, toolkits or frameworks for governments or international organizations.
• Strong skills in stakeholder engagement across diverse actors.
• Familiarity with international standards and best practices in anticipatory action and disaster risk management.
• Familiarity with national disaster risk management systems, social protection mechanisms and/or financing models.

Preferred

• Fluency in French and/or Spanish are strong assets.

Application Instructions

• Please submit your application in English only.
• Please include the following documents in your application:
  • Cover letter or short proposal (max 3 pages) in accordance with the requirements of this TOR. The proposal should clearly explain the consultant’s approach to the delivering the assignment, methodology and proposed budget.
  • CV highlighting relevant experience and including references from at least two previous clients/employers.
  • Portfolio of relevant work.