Created By: Terry CangelosiMay 23, 2024 I used AI on this article. I hope you enjoy reading it! You know what I mean when I say that, right? AI was used, by me, on this article. I went to AI, then used it, and now this article is done. Am I talking in circles and not giving you a straight answer? Yes, but let me ask you, what do you think I meant when I said, “I used AI on this?” Are you assuming I used it the same way that you most recently used it? What percentage of this article was original thought vs AI generated? Did I even come up with the idea or did AI literally write every word and I just copied and pasted the output here? Did I fact-check anything? Did I run any of the material through a plagiarism checker? The point is that if I don’t define the “how” when I say, “I used AI on this,” you would have no idea the steps I took, the considerations I made, or the way I used it. And while I might be able to answer the question when you ask, there are proactive steps that any organization can take right now (for little or no cost) to define the “how” both internally and externally. We’ve written in the past about the importance of an AI Usage Policy and AI Governance which can help define “how” your organization can mitigate biases and enhance transparency, while also addressing ethical considerations and privacy concerns in your staff’s AI usage. These practices ensure staff understand the parameters around when they can use AI in their work and increase their ability to explain their AI usage (read more on the essential concept of Explainable AI). Using those same implemented policies and governance (which should be curated to each organization’s specific preferences and needs), a third way to define the “how” is for those outside the organization, through a Disclosure of AI Usage. Why Consider Disclosing AI Usage? You may have seen some of the high-profile news stories involving disclosure, including Sports Illustrated admitting after the fact that they used AI to generate articles (and writers). Additionally, there appears to be some public support for this transparency – according to one recent study by Zetwork, 68% of respondents answered that companies should voluntarily disclose their AI use. There is also legislation in the works across the United States – the National Conference of State Legislatures (NCSL) tracks them – that could impact broader AI policies, and in many specific cases, the need for public disclosure (use Ctrl+F to search and find “disclosure” NCSL page to see what I mean). A disclosure on AI Usage is a way for your organization to take the already-defined internal policies, practices, and ethical considerations and make it publicly available to your donors, members, and visitors. It can show that your organization is AI Fluent and follows an explainable AI framework. As a bonus, when one of your members asks “how” you use AI, you can offer them peace of mind, while directing them to the steps your staff takes when using AI that align with the values of the organization. Clearing The Air on AI Usage In Nonprofit Work Finally, to answer the question of “how I used AI on this article” – perhaps coincidentally, none of the above is AI-generated. Rather, in alignment with our internal policies and public disclosure, I asked ChatGPT to come up with “nonprofit-specific examples of assumptions people might make about AI usage if the “how” isn’t defined.” Note – these are unedited but are human-reviewed to ensure they are appropriate for this example. AI in Donor Profiling: Without clear internal guidelines and transparent communication about how AI analyzes donor data, stakeholders might suspect invasive or unethical data practices, potentially leading to a loss of trust and donor support. AI Usage in Reporting: If a nonprofit does not clearly explain how AI contributes to creating impact reports, external parties might doubt the accuracy or integrity of the data presented, questioning the organization’s effectiveness and honesty. AI in Decision Making: Without defining the “how,” if AI is used in decision-making processes, stakeholders might assume that important decisions are made without human oversight or ethical consideration, leading to concerns over accountability. AI for Research & Development: Without transparently defining how AI aids in research within the nonprofit, there might be skepticism about the novelty or reliability of the research outcomes, possibly impacting funding and collaboration opportunities. Nonprofits that take the proactive approach to disclose their AI usage – and affirm that human oversight was maintained throughout – can position themselves as adaptive and transparent organizations seeking creative and forward-thinking solutions to further their impact. At Orr Group, we’re enthusiastic about the future of AI and hope to share that enthusiasm with our nonprofit partners. We are ready to assist your organization in brainstorming ways to seamlessly and safely integrate AI into your fundraising and other operational efforts. Contact us to learn how we can help elevate your organization to new heights. Contact Us Terry Cangelosi is a Senior Director and Head of Operations at Orr Group. Terry brings 10+ years of nonprofit operations experience to ensure the most efficient operations in Orr Group’s workflows, technology, and infrastructure. Terry is a member of Orr Group’s AI Taskforce.
How Nonprofits Can Use AI and Automation to Reclaim Time and Realize ROI AI Published Date 2025 How Nonprofits Can Use AI and Automation to Reclaim Time and Realize ROI When workflows are automated with AI, nonprofits can reinvest their time into more strategic and ROI-focused tasks. Explore real-life use cases of AI and automation to improve your effectiveness.
AI for Nonprofits: 10 Tools and Best Practices to Know Published Date 2025 AI for Nonprofits: 10 Tools and Best Practices to Know Created by: CJ Orr May 19, 2025 In today’s technologically driven world, artificial intelligence (AI) has transformed various industries, including fundraising for nonprofit organizations. AI tools have proven to be significant game-changers, enhancing efficiency, creativity, and personalization in donor engagement. To capitalize on these opportunities, over 60% of nonprofits have started embracing AI in their operations. However, despite these high adoption rates, 92% of nonprofits feel unprepared for AI implementation. To prepare your team to fully leverage AI, let’s understand the landscape and discuss the benefits and challenges of using popular AI-powered tools in nonprofit work. Overview of AI for Nonprofits Leveraging AI: Best Practices for Nonprofits Top AI Tools for Nonprofits Overview of AI for Nonprofits What is AI? AI is any technology that can perform intricate tasks and mimic human intelligence. While AI has become a hot topic in recent years, it’s been around for a while, performing simpler duties like sorting emails or scheduling appointments. However, recent advancements in AI have allowed machines to better understand language, process more complex tasks, and generate original content. In the nonprofit world, organizations typically use AI to enhance and streamline: Prospecting and fundraising by analyzing existing donor data for trends, and identifying new prospects with high potential to give Donor communication by analyzing donors based on shared characteristics and tailoring outreach to them for increased engagement Grant writing by quickly reading applications and generating drafts responses, based on previous applications and organizational materials Human resources by automating interview scheduling, onboarding, training, performance management, and more Graphic design by creating visually appealing infographics or mockups Administrative functions by automating repetitive tasks like data entry, timekeeping, and record maintenance Data insights and reporting by analyzing large datasets to forecast trends and enable better decision-making Types of AI Tools for Nonprofits The library of AI tools is vast and ever-growing. While each organization may have its own needs and goals that AI can support, below are several common types of AI tools you may encounter: Generative AI: consists of machines that create new content based on user prompts and training data. Nonprofit applications: Content creation for grant proposals, social media posts, and impact reports. Large Language Models (LLMs): systems designed to understand and generate human language by learning from vast datasets. LLMs are a subset of generative AI focused primarily on creating and understanding text. Nonprofit applications: Automatically answering routine questions via chatbots or summarizing content. Predictive AI uses statistical models and machine learning to identify patterns in large datasets to forecast future outcomes. Nonprofit applications: Prospecting for fundraising and future financial growth. Advantages and Challenges of Using AI Advantages Increased efficiency. With AI handling mundane tasks, nonprofits can focus on more pressing mission-critical work. Easy data reporting. Humans are more prone to making errors when reporting on and analyzing data. AI can easily—and accurately—report on important data. Better decision-making. AI can provide context and information that allows nonprofits to make more informed choices faster. Scalability. Advanced AI solutions can easily adapt to a growing nonprofit’s needs, enabling organizations to handle increased workloads without overburdening staff. Proactive growth. Most nonprofits have adopted AI, and it’s only getting more prevalent. Your nonprofit should leverage similar technology to keep up with others in the field. Challenges Data privacy/security. Nonprofits must confirm that their chosen solution complies with relevant data privacy laws, like GDPR and CCPA, to keep supporter data safe and maintain their trust. Research which regulations apply to your constituents based on their location, and ensure that AI usage is transparently communicated when necessary. Requires human oversight. AI can make mistakes in researching and synthesizing information, so nonprofit teams need to actively maintain their solutions (more on that later). Initial and ongoing costs. Like any other software solution, AI solutions have costs associated with them, both financial and in time to implement and onboard staff. Ethical concerns. AI can reinforce biases based on the datasets it's trained on. There are also concerns about Generative AI solutions trained on user data, which can plagiarize information from other sources. Loss of human touch. Nonprofit outreach relies on forging deep personal connections with supporters. While AI can emulate human thought, it lacks the emotional depth needed to reinforce relationships, so it still requires staff to ensure the final product aligns with an organization’s values. Leveraging AI: Best Practices for Nonprofits Establish parameters for AI privacy and ethics. Your entire team should be aligned on ethical best practices while using AI. Adopt an AI usage policy and supporting AI governance infrastructure to ensure you’re fulfilling promises to stakeholders and protecting their sensitive information. Identify areas for AI application. While AI has many different uses, your nonprofit doesn’t have to rely on it for everything. To start, identify a few pressing areas where AI could help your operations, like content creation, data analysis, or task automation. Work with an expert to implement AI effectively. The stakes are high when implementing AI, so it’s worth consulting with a professional to cover all of your bases. Double-check AI’s work. While AI can generate human-like text, it’s not flawless. You must review and edit the generated content to ensure it aligns with your organization’s voice, mission, and fundraising goals. Properly train your team. AI can present a learning curve for teams, especially those less technologically advanced. Align everyone with comprehensive AI training and educational resources. Don’t completely replace human interaction with AI. As previously mentioned, AI can’t perfectly emulate your connections with supporters. Use AI to brainstorm ideas for communication (like an outline) and fill in the details yourself. Choosing the right AI systems, developing policies, and training your team are essential, but they take time and expert knowledge to get right. By working with a professional team like Orr Group, you can get up and running with new insights and ideal tools by your side. Top AI Tools for Nonprofits General Use/LLM: ChatGPT Use: ChatGPT is an advanced language model that has significantly influenced the nonprofit sector’s fundraising strategies. It utilizes machine learning algorithms to generate human-like text based on the input it receives. Best features: Live web search, DALL-E image generation, and access to a growing dataset. Cost: Limited free tier $20 Plus tier $200 Pro tier $25/user Team tier Pro-tip: Eligible nonprofits can receive a 20% discount on ChatGPT Team and a 50% discount on ChatGPT Enterprise through OpenAI for Nonprofits. AI Chatbot: Cody Use: Cody is a chatbot that uses organizational content to answer HR-related queries for employees based on defined knowledge sources. Best features: Easy user interface, customizable knowledge base, task automation, and specific features for IT support, business consulting, marketing, HR, and more. Cost: $29/month for the Basic tier, $249/month for the Advanced tier Writing: Grammarly Use: Grammarly is a browser extension that enhances grammar and generates written content. Best features: Tone suggestions, auto-completion of writing, and extensive user-supplemented knowledge base. Cost: Free tier, $12/month, $15/month Prospecting: Apollo Use: Apollo is a sourcing tool that collects contact information for prospective supporters. Best features: Automated outreach, meeting scheduler, and CRM enrichment tools. Cost: Free-$119/month Grantwriting: Grantable Use: Grantable is an LLM that automates aspects of the grantwriting and submission processes. Best features: Ability to train the system from writing samples, reference user-uploaded materials from a library, and include educational resources. Cost: Free-$89/month Graphic Design: Gamma Use: Gamma is a graphic design platform that facilitates the creation of presentations, documents, webpages, infographics, and more. Best features: AI-generated designs, customization options, and user-friendly interface. Cost: Free-$15/seat/month Administrative: Zapier Use: Zapier automates repetitive administrative tasks while connecting various apps and services. Best features: Configurable workflows, app integrations, and a large integration ecosystem. Cost: Free-$69/month Data Management: Microsoft Power BI Use: Microsoft Power BI is a Microsoft add-on tool that allows users to create reports, visualize data, and share insights. Can be combined with Microsoft Copilot 365 for AI data insights. Best features: User-friendly integrations with Microsoft Suite, interactive dashboards, and customizable reports. Cost: Free-$10/user/month Meeting Management: Zoom AI Companion Use: Zoom AI Companion simplifies meeting management by automatically completing tasks during the meeting. Best features: Real-time meeting transcriptions, agenda generation, and ability to assign next actions with a meeting summary. Cost: Free with paid Zoom account Now that you have a solid understanding of AI in the nonprofit world, it’s time to create and execute your own strategy! Developing policies, training your team, and staying updated on the newest best practices can be draining—but it doesn’t have to be. Having an expert team by your side allows you to play around with these tools, test them out, and see what works for you without compromising mission-critical activities. We suggest working with a team with a business-oriented mindset, embedded partnership approach, and AI-specific expertise, like Orr Group. Our well-rounded nonprofit experience and hands-on strategy can help your nonprofit become more comfortable with AI and develop a sustainable use policy in the long term. That way, you can adapt to the rapidly-changing world of AI with ease! CJ Orr is President and Partner of Orr Group. As an expert project and relationship manager with 10+ years of experience in the sector, CJ utilizes data and technology to execute on the development of strategies and tactics to drive effective fundraising plans that meet or exceed targets.
How to Drive Transformation with Strategic AI Implementation AI Published Date 2025 How to Drive Transformation with Strategic AI Implementation Learn how to strategize around effective AI implementation at your organization to responsibly address problems and create lasting results.