Closing the AI Assurance Divide

https://partnershiponai.org/resource/closing-the-ai-assurance-divide/

Publish Date: 2026-02-18 21:10:57

Summary

AI assurance, essential for balancing innovation with safety and fairness across the global AI markets, has predominantly evolved in advanced economies, thereby creating an assurance divide that puts developing countries at risk despite their significant contribution to the AI market. These developing countries often face amplified AI risks, where the trust in AI ranges from over-reliance to skepticism. Developing robust AI assurance ecosystems in these regions can advance sustainable development, fulfill human rights obligations, and ensure justified trust in AI technologies. However, such efforts confront substantial obstacles, encompassing a vast diversity of languages, cultural values, and risk profiles; resource constraints; and legal and political barriers like regulatory gaps and limited international representation. To bridge the assurance divide, five key strategies are proposed: selecting and understanding the appropriate elements for assurance, building capacity through development in skills and infrastructure, setting adaptable assurance criteria, and fostering international cooperation through multi-directional partnerships.

Key Points:

AI assurance primarily developed in advanced economies, creating a division that puts developing countries—big contributors to the global AI market—at risk.
Building effective AI assurance ecosystems in developing countries helps in achieving sustainable development, human rights obligations, and warranted AI trust.
Challenges in creating these assurance ecosystems include cultural and linguistic diversity, resource constraints, and political and legal hurdles.
Proposing five strategies: selection and understanding of elements, capacity building, setting flexible criteria, and international cooperation.
Strategies emphasize socio-technical sensitivity, cost-effectiveness, and adaptation, rather than a universal approach.