Across the Indo-Pacific, local NGOs are being asked to do more with less. Aid funding is shrinking, and compliance and performance requirements are growing. AI is being held up as the answer, but its benefits are not reaching local organisations equitably.
AI needs a clear operating model and structured context to perform well. Well-structured and well-resourced organisations are capturing its dividends, while unstructured use is leaving under-resourced NGOs with frameworks that are uninformed, unlinked, unused and at times unsafe.
A wave of sector-specific AI tools is coming, but their impact will be limited by the capacity of the organisations using them. We need to make sure local partners are equipped to make the most of these opportunities.
The challenge
The Outrigger Project believes there are three essential components for organisational AI readiness:
Capability: staff who combine AI literacy with sectoral judgement to know whether an output is accurate
Defined operating model: staff and AI understand how the organisation operates
Structured context base: knowledge exists in a form AI can easily interpret
Organisational AI readiness
Literacy is only half of what makes up capability, and capability is only one component of readiness. Even a well-resourced organisation with capable, AI-literate staff can still be unready because it has never made its operating model explicit or put its institutional knowledge into a form an AI can use.
Most AI-in-development initiatives focus on AI literacy alone. Very little attention is being paid to the second and third components. These components compound because every AI tool an organisation adopts performs against the operating model and context base that organisation has built.