Development cooperation is overdue for a tech upgrade. How can development cooperation reform its organizational structure and programming on the ground? The new technological disruption is more than just an efficiency plug-in; the sector needs a complete transformation. Throughout this portfolio, I discuss how.
In collaboration with Deutsche Welle (DW) Akademie and UNDP, we are developing an open, AI-powered assistant that supports development practitioners, consultants, and policy advisors in their programming, advisory, and policy-design work on mitigating political polarization. Rising polarization erodes institutional trust and, as the UNDP Human Development Report documents, slows progress across development goals. Yet the guidance practitioners rely on still lives in static, 100-page PDFs that are rarely updated, hard to navigate, and impossible to adapt to fast-moving, low-resource settings. Our tool replaces that model with a conversational interface: users describe their situation and receive context-specific guidance, a draft action plan, a risk assessment, and a stakeholder map, each grounded in vetted evidence. The tool builds on a multi-agent architecture: a retrieval agent runs optimized search; a context agent adapts outputs to the user's role, sector, and country; a scenario agent generates branching decision simulations; a structured-output agent drafts action plans and risk matrices; a quality-assurance agent fact-checks every output against the repository; and a translation agent delivers multilingual access. Each agent is independently testable and upgradable.
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Advocating for social inclusion in the design of smart cities, on our digital platform, we documented the work of Canadian cities as they went through the process of developing applications for the Smart Cities Challenge Canada.
Link here →The sector can no longer rely on outdated static PDFs for its advisory and programming work. But more than plug-in efficiency tools, the technological disruption requires a complete rethinking of how the sector operates and offers democracy support.
Two features of AI stand out among technological innovations: It is exceptionally powerful, and its (computing) power is increasing faster than any previous technology in human history. AI is not a tool that can simply be added to the existing arsenal just for the sake of task automation and increased efficiency (Sinanoglu, 2025a). Its consequences are so profound that using it to advance broader development objectives requires changes to some of the ways development cooperation works. In this chapter, we go beyond more general assessments (OECD, 2025) of the use of AI by governments (OECD, 2026) and of the global development risks posed by AI (United Nations Independent International Scientific Panel on Artificial Intelligence, 2026). We argue that successful development cooperation for sustainable futures depends on collaboration with others in iterative and adaptive ways to exploit opportunities for positive change more effectively in challenging contexts. To this end, current development-cooperation structures and processes should be reformed to facilitate and encourage organisational learning (Brandi & Büge, 2026) and adopt a more iterative approach to cooperation. To what extent does development cooperation currently deploy AI tools for such organisational learning? By "AI", we mean generative and agentic artificial intelligence. We also distinguish between "AI in development" and "AI for development". Whereas the former refers to how AI is used in middle- and low-income countries, the latter refers to how the development sector can use AI. We catalogued how the supply side of development cooperation (donors, ministries, agencies, development banks, United Nations (UN) entities, humanitarian implementers and funders) uses AI in its own operations, programming, advisory work and evaluations. The database comprises 172 AI deployments and, while not exhaustive, provides a comprehensive primary-source snapshot that lets us answer three questions empirically: Who is deploying AI? What for? And how far has it matured?
Agentic AI is arriving in development cooperation before the sector can govern it. Germany should play a leadership role in the sector's technological transformation.
Knowledge and toolkits are still often published as PDFs and downloads. But where are the voice assistants, interactive models, and intelligent early-warning systems?
AI can transform media development programming by enabling smarter early warning systems to protect journalists, especially against fast-moving threats.
Today's public policy schools need to engage with citizens, understand technological change, and look at problems horizontally.
Digitizing small and medium enterprises in Turkey amid crisis.
Fostering youth employment across the MENA region in a socially inclusive industrial transition.
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