AI Glossary for nonprofits
Clear, practical, and jargon-free for nonprofits.
At RADIAITE, we believe AI should be explained without technical jargon. But sometimes, certain terms still come up. This glossary gives nonprofits clear, simple explanations of common AI words, so you can understand what matters, what does not, and where AI can genuinely help.
curated by RADIAITE – Microsoft Certified AI Engineers
reviewed by Christopher Mierbach
A
AI Assistant
Explanation
An AI assistant is a tool that helps people complete tasks, answer questions, summarize information, or draft content.
Why it matters for nonprofits
It can save time across everyday work, from internal support to donor communication and knowledge access.
Example
An AI assistant helps staff quickly find answers in internal policies, past reports, or program information.
AI Readiness
Explanation
AI readiness means how prepared an organization is to use AI in a practical, responsible, and useful way.
Why it matters for nonprofits
Before adopting AI, it helps to know whether your goals, processes, data, and team are ready for it.
Example
A nonprofit may be interested in AI, but first needs to clarify where it would bring real value and who would use it.
AI Strategy
Explanation
An AI strategy is a clear plan for where AI can help, what to prioritize, and how to move forward step by step.
Why it matters for nonprofits
Without a strategy, AI efforts can become scattered, expensive, or disconnected from real needs.
Example
A nonprofit defines three priority areas for AI: internal efficiency, multilingual support, and better access to knowledge.
Artificial Intelligence (AI)
Explanation
Artificial intelligence, or AI, refers to systems that can perform tasks that usually require human intelligence, such as understanding language, finding patterns, or generating content.
Why it matters for nonprofits
AI can help organizations reduce repetitive work, improve access to information, and offer better support at scale.
Example
A nonprofit uses AI to summarize meeting notes, translate content, or answer common questions from service users.
Automation
Explanation
Automation means using technology to handle repeatable tasks with less manual effort.
Why it matters for nonprofits
It helps teams save time, reduce admin work, and focus more on mission-critical activities.
Example
Incoming inquiries are automatically sorted and routed to the right team instead of being handled manually.
Azure AI
Explanation
Azure AI is Microsoft’s set of AI services and tools for building and running AI solutions.
Why it matters for nonprofits
It can be useful for organizations already working in the Microsoft ecosystem and looking for secure, scalable AI options.
Example
A nonprofit builds an internal AI tool on Azure that answers questions based on approved internal documents.
B
Bias
Explanation
Bias in AI means that a system may produce unfair, unbalanced, or misleading results.
Why it matters for nonprofits
Nonprofits often work with sensitive topics and diverse communities, so fairness and responsibility matter.
Example
An AI tool gives better answers for one group of users than another because the underlying data was not balanced.
C
Chatbot
Explanation
A chatbot is a tool that communicates with users through text or voice, often to answer questions or guide them.
Why it matters for nonprofits
It can provide support outside office hours and help people get basic information quickly.
Example
A chatbot on a nonprofit website answers common questions about services, events, or application steps.
D
Data Privacy
Explanation
Data privacy means handling personal or sensitive information in a careful, lawful, and responsible way.
Why it matters for nonprofits
Many nonprofits work with sensitive data, so privacy must be considered before using AI.
Example
Before using AI for case-related documents, a nonprofit checks what data is included and whether it should be processed at all.
Data Security
Explanation
Data security means protecting information from unauthorized access, loss, or misuse.
Why it matters for nonprofits
Organizations need to make sure that data stays secure when introducing new tools and workflows.
Example
A nonprofit chooses an AI solution that includes access controls and works within its existing secure environment.
G
Generative AI
Explanation
Generative AI is a type of AI that can create new content, such as text, images, summaries, or drafts.
Why it matters for nonprofits
It can support teams with communication, research, documentation, and other time-consuming tasks.
Example
A communications team uses generative AI to draft a first version of a newsletter or event invitation.
H
Hallucination
Explanation
A hallucination happens when an AI system gives an answer that sounds convincing but is incorrect, invented, or not grounded in reliable information.
Why it matters for nonprofits
Organizations should not assume AI output is always accurate, especially in sensitive contexts.
Example
An AI assistant invents a policy detail that does not exist in the original document.
Human in the Loop
Explanation
Human in the loop means that people stay involved in reviewing, approving, or correcting AI outputs.
Why it matters for nonprofits
This helps reduce risk and keeps important decisions under human control.
Example
AI drafts a response to a beneficiary request, but a staff member reviews it before it is sent.
I
Integration
Explanation
Integration means connecting AI tools with the systems and workflows an organization already uses.
Why it matters for nonprofits
The more naturally AI fits into existing tools, the easier it is to use and the more value it can create.
Example
An AI assistant is connected to Microsoft Teams and SharePoint so staff can use it in their normal work environment.
K
Knowledge Base
Explanation
A knowledge base is a structured collection of information, such as policies, FAQs, guides, or internal documents.
Why it matters for nonprofits
AI systems often need reliable source material in order to give useful and trustworthy answers.
Example
A nonprofit uses its internal handbook and service documentation as the basis for an AI support assistant.
L
Large Language Model (LLM)
Explanation
A large language model, or LLM, is an AI model trained to understand and generate human language.
Why it matters for nonprofits
Many AI tools that write, summarize, translate, or answer questions are based on LLMs.
Example
An LLM helps turn long meeting notes into a short summary with key actions.
M
Machine Learning
Explanation
Machine learning is a way of building systems that learn patterns from data instead of following only fixed rules.
Why it matters for nonprofits
It helps explain how some AI systems make predictions, classifications, or recommendations.
Example
A system learns to identify common types of incoming requests based on past examples.
Microsoft Copilot
Explanation
Microsoft Copilot is Microsoft’s AI assistant built into tools such as Word, Excel, Outlook, Teams, and other Microsoft products.
Why it matters for nonprofits
For organizations already using Microsoft 365, it can bring AI support directly into familiar workflows.
Example
A staff member uses Copilot in Outlook to draft an email reply or in Teams to summarize a meeting.
P
Prompt
Explanation
A prompt is the instruction or question you give to an AI system.
Why it matters for nonprofits
Clear prompts usually lead to more useful results and save time.
Example
Instead of asking “Write something about our event,” a better prompt is “Draft a short, friendly event invitation for volunteers.”
Proof of Concept (PoC)
Explanation
A proof of concept is a small test to check whether an idea works in practice before investing more time or budget.
Why it matters for nonprofits
It allows organizations to start small, learn quickly, and reduce risk.
Example
A nonprofit first tests an internal AI assistant with one team before rolling it out more broadly.
R
Retrieval-Augmented Generation (RAG)
Explanation
Retrieval-augmented generation, or RAG, is a method where an AI system first looks up relevant information from trusted sources and then uses that information to generate an answer.
Why it matters for nonprofits
It can make AI answers more reliable when they need to be based on internal documents or approved information.
Example
An AI assistant answers staff questions using content from internal guidelines, rather than relying only on general model knowledge.
U
Use Case
Explanation
A use case is a specific situation where AI can solve a real problem or support a concrete task.
Why it matters for nonprofits
Good AI projects start with a clear use case, not with technology for its own sake.
Example
A nonprofit identifies one use case: answering recurring internal questions about processes and templates.
W
Workflow
Explanation
A workflow is the sequence of steps involved in completing a task or process.
Why it matters for nonprofits
AI creates the most value when it supports a workflow that already matters to the organization.
Example
Instead of only generating text, AI helps across a full workflow: receiving a request, classifying it, drafting a response, and routing it for review.