Better Match: How AI can be used for funding organizations – Key Take-Aways from the 3rd session of the Learning Journey “AI in Everyday Philanthropy”

30. April 2024

The 3rd session of the six-month hands-on programme and Learning Journey “AI in Everyday Philanthropy”, organized together with our partners StiftungSchweiz and the University of Geneva, focused on how AI can be turned into a humanizing force, so that we can achieve greater impact.

The session started with a provocative question: Can (all) some business processes of a funding organization be (replaced) supported by agentic networks? Together with Siddhartha Jha, AI and Digital Innovation Lead at Fondation Botnar, the participants explored this question from two perspectives: 1) The impact of AI on business operations (internal) and 2) the impact for supported projects (strategic level). In the realm of philanthropy, AI is no longer a distant concept but could potentially become an integral part of everyday operations, from contracting and grantmaking processes to communications and asset management. In the end, AI should serve to automatize tasks that are draining or unpleasant and free time for other things, such as talks with grantees. Today, some of the most frequently used AI tools within organizations are for translations and spellchecking, e.g. DeepL and Grammarly. But this could change in the future. In the Learning Journey, Fabio Duo from our tech-partner Freihandlabor, demonstrated how a fully automated grantmaking workflow could look like – a worldwide first experiment. Even though we are just at the beginning and the model is far from perfect, it showed the possible potential of an automated philanthropic process.

Where to start with your organization’s AI journey: By not talking about AI

As the philanthropic landscape evolves, staying informed about AI becomes imperative for funders to remain relevant and to make decisions based on knowledge and with a nuanced perspective, not driven by fear, or alternatively, by jumping on the train of a hype. Yet, embracing AI isn’t merely about adopting cutting-edge technology; it’s about fostering a culture of learning and collaboration within funding organizations. But where to start?

Siddhartha Jha suggested the following steps, emphasizing a rights-based digital transformation, putting responsible AI in the center:

Understanding your organization and workflows better: Although it sounds counterintuitive at first glance, the first step is not about technology at all, but about a deeper understanding of the tasks and workflows of your organization. This allows for conversations about which tasks are essential, where human intervention adds value, and how AI can complement rather than replace human capabilities. By understanding which tasks are ripe for automation, which ones require human expertise, and which ones could benefit from a hybrid approach, companies can better prepare themselves for the evolving technological landscape.
Alignment and education: A very crucial step in your AI journey involve ensuring that everyone within the organization, from the office administration to the CEO and the Foundation Board, have a shared understanding of AI. This involves training for all team members to deepen the knowledge and the conversations. An additional step could be creating a network of internal champions or resources that can serve as a reference. Literature, articles and lectures or collaborations with a university could serve as a starting point, see for example the FT Explainer Series on AI, Elements of AI Online Course etc.
Communications and collaboration: Given the complexity of AI, communications, community, and collaboration are key factors. Collaborations with other peers, for example from academia, or learning from the grantees themselves, can deepen the knowledge and the practical application within the organization. The transformation process does not need to be done alone.
Policy development: In addition, policies related to AI that allow or enable safe experimentation and opportunities to innovate and iterate with AI applications should be developed (guidelines for internal and external use). Following and monitoring the space of Swiss regulations can help to stay informed about relevant legal and ethical developments.

Embracing Responsible AI

Just as the cockpits of modern aircraft differ vastly from those of the past decades, AI in philanthropy introduces new dimensions, empowering funders to navigate challenges and opportunities with enhanced precision. In the end, AI is a means to always achieving an end-goal: Achieving more impact with less. By making funding organizations and NPOs more efficient, AI can help achieve more with less budget and free up time for the human aspects of philanthropy. This increased efficiency can lead to higher returns on investment and enable foundations to reach a larger number of beneficiaries.

Despite the great potential of AI, Luciano Floridi, Founding Director of the Yale Digital Ethics Center, highlighted in his keynote at the Geneva conference on Artificial Intelligence and Philanthropy the importance of Responsible AI. This means not only harnessing its potential to enhance efficiency and impact but also safeguarding against ethical risks. A first step towards this objective is to create transparency: What kind of data are used to which end-goal, where is an automated process involved? The topic of Responsible AI will be explored in-depth in the next sessions of our learning journey.

Do you have questions, or would you like to discuss the implications of AI in Everyday Philanthropy? Discuss with us in the StiftungSchweiz Network