The practical application of artificial intelligence (AI) in international development is swiftly transitioning from theory to reality. During the 2024 Australasian AID Conference, discussions centered on the development and testing of AI tools designed to enhance development policies and decision-making processes within aid organizations.

Key presentations were made by Dragonfly Thinking and the Development Intelligence Lab, both showcasing structured AI applications that complement human analysis while navigating common pitfalls associated with technology adoption. Miranda Forsyth, co-founder of Dragonfly Thinking and a professor at ANU’s School of Regulation and Global Governance, shared her transformation from an AI skeptic to an innovator. Together with Professor Anthea Roberts, she created an AI platform that aids users in tackling complex developmental issues.

Central to their methodology is the “Triple R Framework,” which examines risks, rewards, and resilience—differentiating it from standard analytical tools like SWOT or cost-benefit analysis. This framework emphasizes resilience, considering how systems evolve and change over time through absorptive, adaptive, and transformative capacities.

Forsyth illustrated the platform’s capabilities by analyzing sorcery accusation-related violence in Papua New Guinea, demonstrating how AI can aid in understanding the complexities surrounding social media’s influence on such violence.

The Development Intelligence Lab has also explored how AI can enhance policy analysis. CEO Bridi Rice reported promising results from an experiment in which inexperienced analysts used the Dragonfly platform to analyze economic issues under time constraints. Their conclusions, validated by development economists, provided richer insights than traditionally offered.

Despite intrinsic bias concerns related to AI—particularly regarding the dominance of Western viewpoints—Rice suggested that this technology could mitigate biases inherent in traditional policy discussions. The experience of these organizations provides valuable lessons for others considering AI adoption. While AI enhances efficiency in mundane tasks, its real value lies in improving analytical quality and decision-making processes.

Moreover, AI’s potential to elevate local perspectives in development decisions is noteworthy, especially with the rapidly improving translation capabilities. The Development Intelligence Lab’s “Southeast Asia Pulse Check” project exemplifies how AI can merge expert insights with local knowledge, addressing the concern that development programs often reflect donor biases instead of local realities.

The organizations are also planning for future initiatives in 2025 that will facilitate discussion on AI’s role in development and increase diverse knowledge integration into their systems.

Challenges, such as managing AI’s energy demands and ensuring the incorporation of indigenous knowledge, remain significant. Both presenters emphasized that AI should augment, not supplant, deep local engagement in program development. Furthermore, maintaining human oversight is crucial as AI tools evolve, underlining that such technologies are assistive rather than replacements for human intuition and experience.

The development sector, similar to other fields, faces questions regarding equitable access to AI technology across various organizations. It’s vital to consider how smaller entities and those in developing regions can leverage these advanced tools without falling behind due to limited resources.

Overall, the collaborative efforts of Dragonfly Thinking and the Development Intelligence Lab demonstrate that a mindful approach to AI adoption—focused on enhancing human capabilities—could empower development practitioners to navigate complex challenges more effectively. This positive trajectory reflects a hopeful evolution in how AI can support international development work, fostering greater inclusivity and better decision-making processes.