ABSTRACT
For companies that practice philanthropy, there is a wide range of models: on the most basic end, some give cash grants, while on the more complex end, others give a combination of their assets – whether physical, human, or organizational. Given that emerging artificial intelligence capabilities are asset-specific and difficult for NGOs to replicate, NGOs will often benefit more from in-kind technology donations than cash. This chapter offers guidance to transnational philanthropic arms for when to give financial grants and when to provide resources like machine learning and data science trainings, specialized software, and others. This question warrants scrutiny as the opportunity cost is high – companies are giving more year over year – and the people impacted by better giving models will be NGOs’ clients and beneficiaries most in need of aid. Drawing from management literature on the resource-based view (RBV) of the firm, this chapter proposes that offering a diverse range of AI assets is more effective than cash under the conditions that (a) the AI fulfills a specific NGO need that cannot otherwise be easily met, (b) the donor is well-equipped to manage NGO relationships, and (c) the staff responsible for facilitating donations do not compromise core business objectives.
