Artificial intelligence (AI) is reshaping the way nonprofits operate. From automating routine tasks to unlocking insights from mountains of data, AI offers new ways to amplify impact. But let's not sugarcoat it: AI also introduces risks. Data privacy concerns, algorithmic bias and the potential for mission drift (when technology pulls an organization away from its core purpose) are very real challenges.
This is why every nonprofit experimenting with AI needs a comprehensive, mission-aligned AI policy.
AI Is Here and Transforming the Social Sector
Nonprofits are finding innovative ways to integrate AI into their work. But responsible adoption is just as crucial as the technology itself.
Take Objective Zero Foundation, which combats military and veteran suicide through peer support and access to mental health resources. Recognizing both the promise and risks of AI, the organization has put policies in place to ensure its AI initiatives prioritize transparency, fairness and accountability.
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Another example is CareerVillage, a tech nonprofit connecting learners to personalized career advice. The nonprofit recently launched an AI tool called Coach, which uses AI to instantly answer learners’ questions with helpful, accurate career guidance.
These are just two examples of how tech nonprofits are leveraging AI to better serve their beneficiaries. But adoption doesn’t come without challenges. Many nonprofits operate with lean budgets and small technical teams, making sophisticated AI implementation feel out of reach. And because nonprofits handle sensitive data, they must be especially vigilant about privacy and security.
Which brings us to the bigger question: How do nonprofits harness AI’s potential without compromising trust, ethics or their mission?
AI’s Impact Is Real so Thoughtful Use Matters
AI isn’t neutral. It mirrors the data it’s trained on. And that data, often scraped from the internet, is riddled with human bias. If a nonprofit relies on AI for hiring, grant distribution or community outreach, those biases can seep into decision-making. This has the potential to reinforce inequities instead of dismantling them. That’s why responsible AI development is just as important as the technology itself.
“Building an AI tool is the easy part,” Rebecca Gitomer, director of development at Career Village, said. “What’s difficult — and what is front and center for Coach — is developing and iterating on the infrastructure, safeguards and guardrails underpinning the tool.
“Responsible AI isn't just a consideration, it’s our largest investment and priority,” she continued. “We know that for Coach to serve all learners and jobseekers effectively, it requires strong policies, safeguards, and ethical frameworks. That's why we’ve built Coach on an 8-part responsible AI framework, are a member of EdSafeAI’s Industry Council, and are soon launching the AI for Career Development Coalition. This work isn't optional. It's essential."
But bias isn’t the only concern. Data privacy is another critical factor. A poorly secured AI system isn’t just a technical failure — it’s a breach of trust that can put vulnerable communities at risk.
And then there’s over-reliance. AI is not a replacement for human judgment. When used responsibly, it can streamline workflows and free up staff for higher-value tasks. But human oversight remains essential to ensure AI aligns with an organization’s mission and values.
Why Every Nonprofit Needs an AI Policy
An AI policy isn't just a nice-to-have. It's a commitment to keeping your tech aligned with your values. Without clear guidelines, nonprofits risk misusing AI, violating donor and beneficiary trust, or simply failing to harness the technology effectively.
A good AI policy should:
- Define the organization's objectives for using AI and how it supports the mission.
- Establish ethical guidelines around fairness, transparency, accountability and privacy.
- Outline how data is collected, stored and protected.
- Identify strategies for detecting and mitigating bias in AI systems.
- Assign structures or guidelines outlining responsibility for AI decision-making and compliance.
Building an AI Policy Doesn't Have to Be Overwhelming
If your nonprofit is starting to experiment with AI, now is the time to create a policy. The good news, however, is that you don't have to start from scratch.
To get started, here is a five-step process:
- Form a cross-functional team. Include representatives from various departments to ensure a holistic approach.
- Conduct an AI inventory. Identify existing AI tools and potential use cases within your organization.
- Define ethical principles. Align your policy with your organization’s core values and ethical standards.
- Address data privacy. Outline clear protocols for data handling and protection.
- Establish a review process. Implement regular reviews to ensure ongoing compliance and effectiveness.
There are plenty of free online resources designed to help nonprofits craft AI policies that make sense for their specific needs. Tools like NTEN's “Generative AI Use Policy” (opens as a pdf) offer templates and best practices to guide the process.
AI is a powerful tool, but it's only as effective as the policies that govern its use. Nonprofits eager to experiment with AI should be just as eager to establish clear guidelines that protect their stakeholders, data, and long-term mission. Thoughtful AI adoption isn't just about keeping up with technology. It's about ensuring that technology serves the greater good.
The preceding content was provided by a contributor unaffiliated with NonProfit PRO. The views expressed within may not directly reflect the thoughts or opinions of the staff of NonProfit PRO.
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- Accountability
- Artificial Intelligence (AI)

Kevin Barenblat co-founded Fast Forward to support builders of nonprofits deploying tech and AI to solve humanity's pressing challenges. As president of Fast Forward, he has supported hundreds of social entrepreneurs. Barenblat worked across tech — from startup to big tech and venture capital — before finding his calling supporting tech nonprofits. He earned a Bachelor of Science in engineering from Stanford University and an MBA from Harvard Business School.