I have used ChatGPT to create a series of case studies to help illustrate my ideas recorded in my article ‘The promise and perils of AI in shaping tomorrow’s think tanks and foundations’.
Introduction
John, a programme officer at the Global Justice Foundation (GJF) in New York, is tasked with launching a new international portfolio focusing on tax justice. With the majority of his grantees expected to be from the global south, John seeks the assistance of AI technologies to optimise the development, monitoring, and impact assessment of this crucial initiative.
Challenges faced
- Diverse geographical focus: Identifying and evaluating potential grantees from different countries, each with its own set of challenges and priorities.
- Effective monitoring: Ensuring that the funds are utilised effectively and that projects are on track in real-time.
- Impact assessment: Quantifying the tangible and intangible impacts of funded projects on tax justice.
AI-driven solutions
1.Grantee identification & evaluation
- AI-powered research: John employs AI algorithms to scan databases, publications, and local news sources from the global south to identify organisations already working on tax justice.
- Relevance scoring: The AI categorises and scores these organisations based on their historical impact, relevance to GJF’s goals, and credibility, narrowing down potential grantees for John’s review.
2. Real-time monitoring
- AI-integrated reporting: Grantees are provided with AI-integrated platforms where they input project updates. The AI analyses progress against predefined benchmarks and sends real-time alerts to John if any project veers off track.
- Sentiment analysis: The system also scans local news and social media to gauge public sentiment regarding grantee initiatives, offering an external perspective on project reception.
3. Impact assessment
- Predictive analysis: Using historical data, the AI forecasts the potential long-term impact of each project, allowing John to prioritise funding accordingly.
- Quantitative & qualitative metrics: The AI evaluates both quantitative metrics (like the number of people educated on tax rights) and qualitative aspects (like the improvement in local trust toward taxation systems) to provide a holistic view of the initiative’s impact.
4. Resource allocation & support
- Needs-based analysis: AI algorithms assess the unique needs of each grantee, proposing customised packages of financial support, training, and resources.
- Dynamic re-allocation: The AI periodically re-evaluates project performance and reallocates resources to ensure maximum overall impact.
Outcomes enabled by AI
- Efficient focus: John can dedicate more time to building relationships with grantees, understanding their unique challenges, and offering strategic guidance, as the AI handles the bulk of administrative and analytical tasks.
- Data-driven decisions: John can make funding decisions based on comprehensive data, ensuring resources are utilised most effectively.
- Proactive intervention: Real-time monitoring allows John to intervene and offer support promptly when projects face challenges.
Reflection
Leveraging AI, the Global Justice Foundation not only optimises its grant-making process but also ensures a more profound, data-backed impact on tax justice in the global south. This holistic approach, combining technology with human insight, sets a gold standard for modern philanthropy.