ABSTRACT
As technology advances, artificial intelligence (AI) is changing how nonprofit organizations fundraise and grantmaking organizations allocate their funds. Large Language Models (LLMs) are powerful where wording plays a significant part in the success – as is still the case to a large extent for fundraising and grant allocation organizations. However, the potential for improved efficiency and effectiveness of the grant application process can only be exploited if the technology is used in the near future. A fast-tracked technology adoption becomes the key.
In this chapter, we detail the inhibitors and accelerators of technology adoption and present a model for a meaningful positioning of organizations and their AI readiness. Based on empirical surveys, we locate fundraising and grantmaking organizations in the model and identify the essential factors for accelerated adoption.
Paving the way for a fast-tracking of AI use we develop blueprints for the most important and common use cases for AI in the grant application process. This includes identifying potential funders, personalizing and fine-tuning of proposals, and possibly the automated pre-selection of applications. Through a set of qualitative interviews, we learn to understand essential root causes of concerns, empirically specify the perceived opportunities and obstacles, identify key factors for a responsible use of AI, and develop strategies to overcome inhibitors and hurdles. On this basis, we lay out the guidelines for a learning journey that pioneering organizations aiming to use AI in everyday philanthropy can embark on.
