This glossary defines key AI terms and explains their relevance to your nonprofit's mission and operations.
Algorithm: A set of rules or calculations that a computer follows to solve problems or make decisions. For your organization, algorithms are the engine behind AI tools that can automate donor outreach, analyze impact data, or personalize communications.
Artificial Intelligence (AI): A broad field of technology that enables machines to perform tasks that typically require human intelligence. In the nonprofit space, AI can help you automate routine tasks, analyze large datasets, predict trends, and improve fundraising strategies.
Chatbot: An AI-powered program that simulates human conversation. You can use a chatbot on your website or social media to answer supporter FAQs, engage donors, or guide your community to the right resources 24/7.
Data Privacy: The ethical and secure protection of personal data that you collect. When using AI tools, you must ensure that sensitive donor and beneficiary data is handled with the utmost care to maintain trust and comply with regulations.
Donor Segmentation: The process of categorizing your donors based on their behaviors, giving history, or characteristics. AI can automate segmentation to help you create more personalized and effective fundraising campaigns.
Generative AI: A type of AI that can create new content, such as text, images, or audio. You can use tools like ChatGPT or Gemini to draft grant proposals, write social media posts, or create personalized email campaigns for your supporters.
Machine Learning (ML): A subset of AI where systems automatically learn and improve from data over time without being explicitly programmed. For your nonprofit, ML can help you predict donor behavior, optimize your outreach, and identify patterns in your impact data.
Natural Language Processing (NLP): An AI field that gives computers the ability to understand, interpret, and generate human language. You can use NLP for sentiment analysis to gauge public opinion from social media, get assistance with grant writing, or analyze open-ended survey responses.
Predictive Analytics: The use of data and AI to forecast future outcomes based on historical data. You can use this to identify high-value donors, optimize volunteer engagement, or anticipate community needs before they arise.
Responsible AI: The practice of designing and using AI systems in a way that is ethical, transparent, and inclusive. This is especially important for you as a nonprofit working with vulnerable populations, as it ensures your AI use aligns with your mission and values.
Social Impact Measurement: The process of evaluating the outcomes and effectiveness of your programs. AI can assist you in analyzing qualitative and quantitative data to demonstrate your impact more efficiently and with greater detail.