Document details

Reinventing Humanitarian Aid Procurement for the Age of AI

Access Now (2026), 59 pp.
"Our research reveals that the organisational use of AI and algorithmic systems often happens through a process of unstructured integration rather than formal adoption. More precisely, cloud-based, algorithmic-enhanced functionalities and processes are making their way into humanitarian entitiesʼ tech stack through updates and add-ons to preexisting products, slowly but inexorably seeping into most internal systems. A price-based procurement process designed around the static idea of digital asset purchase is inadequate to ensure adequate protection from hyperdynamic tech product development. This is especially evident looking at the growing power imbalances between private actors and nonprofits, and among nonprofits themselves. Digital technology is often heralded as key to democratise and equalise the playing field between humanitarian actors, by finally unlocking local actorsʼ access to resources traditionally reserved for international entities. But emerging trends seem to disprove such claims. The lack of adequate legal frameworks and safeguards, lagging investments in humanitarian funding for information and communication technology (ICT) resources and connectivity, and inadequate dedicated funding for digital programmes are thwarting these opportunities. More broadly, virtuous and responsible procurement practices are proving inadequate for protecting human rights alone, as tech companiesʼ commitments to human rights are replaced by defence-oriented pitches and the size of their human rights teams keeps shrinking.
Preexisting digital divides are enhanced by several deep and subtle changes in traditional tech business models, resulting from the gradual cloudification of most common digital systems and the fast-paced, distributed nature of modern digital development. Even more worryingly, we are seeing new forms of digital divide well beyond the traditional gaps in digital capacity between local and small non-governmental organisations (NGOs) and international non-governmental organisations (INGOs) or UN entities. Cloud-based companiesʼ takeover of generic coordination platforms creates a constantly broadening chasm between the few organisations that are digitally mature, those who are barely retrofitting their processes to fit the new reality, and the broad majority forced to access the promised land of digital humanitarianism through the predatory gates of algorithmic and cloud servicesʼ free tech licensing.
Our findings highlight how organisation-led digital development, building on open-source systems (despite some “openwashing” practices) and trusted external providers, remains the best option for risk reduction when it comes to algorithmic systems. However, in the short to medium term, this might not be financially and technically feasible for the majority of humanitarian actors, especially considering the catastrophic funding environment. To fill this gap, we propose a toolkit in an appendix to this report. This is a foundational governance model for transforming digital procurement from a transactional into a strategic business function, integrated across key organisational departments. By doing so, protection-mandated aid groups could move from running purchase-centred processes, to adopting a dynamic, proactive, and rights-based approach to tech management. This report also contains a set of recommendations for states and donors, the humanitarian community, tech companies, local aid actors and communities, research centres, and cyber experts." (Executive summary, pages 2-3)
1. INTRODUCTION, 5
Current implementations of algorithmic tools in humanitarian programming
Case study 1: Signpost AI, a platform to de-risk humanitarian AI
Humanitarian procurement in the digital era
Case study 2: OpenAI and the nonprofit-to-defence contractor journey
Case study 3: Microsoft and heightened human rights due diligence for business in conflict-affected contexts (hHRDD+)
Why does this matter for human rights and humanitarian actors
Case study 4: The hidden geopolitics of generative AI
Case study 5: Wikimedia Foundation human rights impact assessment on AI and machine learning
Main trends in humanitarian procurement of algorithmic systems
Taxonomy of emerging practices in the integration of algorithmic systems
2. CONCLUSIONS, 32
Money cannot buy human rights compliance -- Algorithmic capture: The AI-poisoned gift for local actors and communities -- Procurement is becoming heavier, not smarter nor safer
Case study 6: Erin, Tara, and Copilot enter the Irish Department of Justice
Beyond bells and whistles: from product price-based selection to continuous environmental scanning
Case study 7: Clearview AI
Bringing the zero trust environment in procurement
3. SUGGESTED FOUNDATIONS FOR A DIGITAL SERVICE FRAMEWORK IN THE ALGORITHMIC AGE (SEE APPENDIX), 50
4. RECOMMENDATIONS, 53