Donors, Volunteers and AI: The New Power Triangle Behind Crisis Response

Disasters are becoming more complex, needs are expanding, and aid systems are being asked to do more with tighter resources, more fragmented operating environments, and higher expectations for accountability. Apart from simply moving food, medicine, water, shelter, and emergency equipment from one place to another, the challenge is about building supply chains that can anticipate disruption, coordinate multiple actors, and still reach communities when roads fail, communications break down, or funding rules slow decisions.

A new study on the future of humanitarian logistics argues that the next phase of crisis response will depend on how well donors, volunteers, humanitarian organizations, public authorities, and digital systems work together. Published in Logistics, the study examines how humanitarian supply chain cooperation may evolve toward 2030, using Morocco as a case to explore wider questions facing many developing and emerging economies. The research combines interviews and focus groups with 57 humanitarian actors and survey data from 1,183 logistics professionals, making it both field-informed and statistically grounded.

The paper notes that more than 300 million people required humanitarian assistance and protection worldwide in 2024, while global humanitarian funding requirements exceeded USD 45 billion. Those numbers point to a system under strain, but the deeper warning is that even when resources exist, poor coordination can delay delivery, duplicate effort, weaken accountability, and leave vulnerable communities underserved.

Donors must fund flexibility, not just compliance

Donors increasingly shape how humanitarian logistics systems plan, report, digitize, and adapt. Donor engagement can improve coordination and delivery performance, but it can also create rigidity if funding rules and reporting requirements leave little room for field-level judgment.

Donor reporting requirements scored the highest among donor engagement variables, with a mean of 4.35, while donor communication also scored strongly at 4.12. But flexibility of donor funding scored lower, at 3.41. Put simply, humanitarian organizations are receiving structured donor engagement, but not always enough room to adjust when crises evolve quickly.

Effective logistics depends on speed and discretion. A rural delivery team facing blocked roads, damaged storage, sudden displacement, or local security concerns may need to redirect resources immediately. If funding rules are too strict, accountability can become a bottleneck rather than a safeguard.

The study finds that differences in donor engagement are significantly associated with delivery timeliness, suggesting that structured donor participation can improve operational outcomes. But it also cautions that excessive oversight can create pressure in fast-changing settings, especially where rapid decision-making is essential.

Donor systems should reward preparedness, adaptability, and local capacity, not only clean reporting. The future donor model should fund predictive planning, decentralized storage, volunteer training, digital coordination tools, and flexible contingency mechanisms. The study itself notes that donor institutions should move beyond short-term funding and invest in long-term logistics capacity, volunteer development, and digital infrastructure.

Volunteers are the last-mile intelligence system

If donors influence the architecture of humanitarian response, volunteers often determine whether it works on the ground. The study shows that volunteers remain critical to logistics performance, especially in rural and remote areas where formal infrastructure is weak and local knowledge can be decisive. This is one of the most important development-policy insights from the research. Volunteers are not merely extra hands; they are community connectors, interpreters of local conditions, informal risk monitors, and last-mile problem-solvers. In the Morocco case, rural actors emphasized adaptive problem-solving, local knowledge, and decentralized practices, while urban participants highlighted structured coordination, donor oversight, and digital integration.

The quantitative results reinforce the point. Volunteer effectiveness in operations scored 3.76, while adequacy of volunteer training scored 3.58. Retention of skilled volunteers scored 3.44, showing that keeping experienced volunteers remains a challenge. The study also finds that volunteer training significantly affects coordination efficiency, with organizations providing structured training reporting fewer failures.

The finding should matter to policymakers and NGOs because many humanitarian systems still treat volunteer mobilization as temporary, informal, or secondary. The approach may be increasingly inadequate. As crises become more frequent and digital tools become more common, volunteers will need to navigate dashboards, messaging platforms, routing systems, and reporting protocols while still using local judgment.

The future of volunteer management, therefore, is not casual mobilization. It is semi-professionalized community capacity, which means training, retention systems, safety protocols, digital literacy, insurance or protection mechanisms where appropriate, and clear integration with professional logistics teams. For developing countries, this may be one of the most cost-effective resilience investments available.

AI can sharpen relief logistics, but people must stay in charge

The study argues that digital tools can strengthen humanitarian logistics when they amplify human coordination rather than replace it. Technology adoption was the strongest predictor of operational performance in the regression analysis, ahead of donor engagement and volunteer involvement. Together, donor engagement, volunteer involvement, and technology adoption explained 56% of the variance in operational performance. The study also finds strong positive correlations between technology adoption and operational performance, with technology emerging as a coordination amplifier that improves visibility, responsiveness, and efficiency.

However, the adoption pattern remains uneven. Inventory tracking systems were more widely used, with a mean usage score of 4.01, while routing and transport planning software scored 3.74. AI-based decision-support tools were less prevalent, at 3.12. It suggests that many humanitarian organizations are in a transitional phase: basic digital logistics tools are becoming more familiar, but advanced AI-enabled systems remain constrained by infrastructure, cost, skills, and trust.

Digital systems can help forecast needs, monitor supplies, optimize routes, coordinate volunteers, and improve transparency. But if they are deployed without local capacity, reliable connectivity, inclusive design, and human oversight, they may deepen the very divides they are meant to solve. Rural and remote communities could be left behind if humanitarian digitization assumes infrastructure that does not exist.

The study calls for hybrid socio-technical systems. In other words, future-ready humanitarian logistics will require AI-supported planning, predictive analytics, cloud coordination, and real-time communication, but also trust, field experience, local leadership, flexible governance, and volunteer knowledge.

Resilient supply chains are more likely to emerge from systems that combine digital innovation with human expertise, local knowledge, and collaborative decision-making. For the Global South, the same principle applies across public health, food security, climate adaptation, disaster risk reduction, and social protection: technology improves outcomes when it is embedded in institutions that understand people, geography, incentives, and inequality. The road to 2030 will test whether humanitarian systems can move from reactive aid delivery to anticipatory, locally grounded, digitally enabled response.