Evaluate an AI tool against a specific mission-related task—not by its novelty or a vendor’s general promises. First ask whether AI is needed, then examine the information it will handle, test its outputs for accuracy and harm, and assign a person who remains accountable for decisions. No single tool is best for every church or nonprofit: fit depends on the task, affected people, jurisdiction, provider terms, and the organization’s ability to oversee it.
Start with the task, not the tool
Write down the problem the organization wants to solve, who will use the system, who may be affected, and what a useful outcome would look like. Consider what could happen if the output is wrong or incomplete. Then ask whether a non-AI process could meet the need with less risk or effort.
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The UK Charity Commission advises charities to assess options and risks against their objectives and trustee duties; Australia’s ACNC similarly asks whether AI is strategically the best solution. These are jurisdiction-specific governance resources, not interchangeable legal rules. See the Charity Commission guidance and ACNC guidance.
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Begin with low-stakes assistance
Google for Nonprofits recommends starting with repetitive, low-stakes work. Examples might include drafting a first pass at a routine internal summary or organizing non-sensitive material, provided a person checks the result. Be cautious where the work involves confidential information, high-stakes empathy, or final decisions. AI should assist people, not quietly replace them. Google’s responsible AI guidance for nonprofits frames the decision plainly: ask whether the task is appropriate for AI.
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Map the information the tool will receive
List what could enter prompts, uploaded files, connected services, or automated workflows. Include information staff may not think of as sensitive at first: donor records, beneficiary details, employee information, confidential correspondence, and sacred or pastoral material. Minimize or remove identifying details when they are not needed for the task.
Review the privacy policy, terms, retention practices, any use of submitted data for model improvement, access controls, and security documentation for the exact product, account, and subscription tier being considered. These conditions can vary by plan and change over time, so a provider’s broad description is not a substitute for checking the terms that apply to your account. Match the review to the laws and obligations relevant to your jurisdiction.
Take extra care when information concerns children or includes medical details; the Charity Commission specifically flags these contexts. A church-specific example, the Church of Jesus Christ of Latter-day Saints’ AI principles, calls for safeguarding sacred and personal information. That is an institutional example, not a rule binding every denomination.
Test outputs for accuracy, bias, and mission fit
Before using a tool in real work, test it with representative scenarios that reflect the people, language, accessibility needs, and edge cases involved. Have knowledgeable reviewers check factual claims against reliable sources and look for errors, omissions, stereotypes, discriminatory results, inaccessible formats, and a tone that misrepresents the organization.
Ask whether the output reflects the organization’s values and whether affected people could be harmed even if the answer sounds polished. Google advises checking accuracy, fairness, representativeness, and authentic organizational voice. The ACNC identifies risks including biased or discriminatory decisions, poor security, reduced human connection, and accessibility barriers. Google’s concise rule is: “Check AI-generated outputs before using them.”
Keep responsibility with people
Name the person or group responsible for approving the use, reviewing outputs, verifying important claims, responding to complaints, and stopping the tool if material errors or harm appear. Do not treat generated output as the decision-maker, especially when a decision affects an individual’s access to services, support, employment, or other significant interests.
For charities in England and Wales, the Charity Commission says: “Trustees remain responsible for decision making so given the consequences if incorrect advice is relied upon, it is vital this process is not delegated to AI or based on AI generated content alone.” Canada’s privacy commissioner likewise emphasizes that accountability for decisions rests with the organization, not the automated system. Applicable duties differ by jurisdiction; seek local legal or privacy advice when the stakes warrant it.
Compare tools against the same criteria
Use one task and one organizational context when comparing options. A feature list or general vendor claim cannot establish that a tool is suitable for your use case. Product terms and capabilities should be checked directly before deployment.
| Evaluation area | Questions to ask |
|---|---|
| Mission and task fit | Does the tool address a defined need? Is AI necessary, and who benefits? |
| Data and privacy | What information enters the system? What do the applicable terms say about retention, reuse, access controls, and security for this product and tier? |
| Quality and auditability | How will staff verify outputs? Can they check sources, reproduce a result, or review what happened? |
| Fairness and accessibility | How does it perform for the people affected? Could bias, exclusion, or inaccessible output cause harm? |
| Human oversight and recourse | Who approves and monitors use? Can a person challenge an outcome and reach a human reviewer? |
| Transparency | When should members, donors, beneficiaries, users, or staff be told that AI is involved? |
| Organizational capacity | Can the organization train staff, support the tool, monitor it over time, and manage the ongoing review effort? |
| Wider obligations | What legal, copyright, reputational, and jurisdiction-specific requirements apply? |
These criteria synthesize guidance from Google for Nonprofits, the UK Charity Commission, the ACNC, and Canada’s privacy commissioner; they are not a ranked vendor scorecard.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Set policy, disclosure, and review expectations
A practical internal policy can state:
- Which purposes and tools are approved, restricted, or prohibited.
- Which categories of information must not be entered into AI systems.
- Who approves use and how risk is classified.
- What testing, verification, and human review are required before outputs are used.
- When to disclose AI involvement, and how people can seek human help or challenge consequential decisions.
- What use records to keep, how to report incidents, and who handles escalation.
- What staff training is required and when the policy will be reviewed.
The Charity Commission suggests considering a policy to clarify AI use in governance, staff work, or service delivery. Google points nonprofits to Fast Forward’s no-cost Nonprofit AI Policy Builder; the existence of that resource does not make a particular commercial policy product necessary.
For decisions about individuals, Canadian privacy principles recommend explaining whether and how generative AI contributes, describing safeguards and recourse, and providing an effective challenge mechanism and opportunity for human review. Their application, and the legal duties that may apply, depend on jurisdiction.
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Keep a record of the tool and task, the categories of data involved, the reviewer, known limitations, incidents, and the decision to continue or stop. Set a review date and reassess when the provider changes its product or terms, the use case changes, or relevant rules change.
Bring church-specific values into the evaluation
For churches, ordinary procurement questions sit alongside spiritual formation, pastoral care, authenticity, and human connection. The Church of Jesus Christ of Latter-day Saints’ principles say AI should support rather than replace connection between God and people, protect sacred and personal information, and be used deliberately with regular testing and review. Elder Brent H. Nielson Pingree said the principles are “intended to support the responsible use of AI by the Church workforce.” Elder Gong said he was optimistic about using the technologies wisely while protecting Church members and friends from falsehoods.
Those statements describe that church’s institutional approach; they do not establish universal doctrine or policy for other faith communities. For any church, generated text should not be treated as pastoral discernment or as a substitute for trusted religious leadership. That follows from the importance of human connection and truth in the cited church principles, rather than from a technical guarantee about AI.
What nonprofit adoption figures do—and do not—show
NTEN and The Bridgespan Group’s 2026 report page presents survey responses from 404 executive respondents: 30.42% said a process to approve AI tools and vendors was in place, and 38.56% said written guidance on safe and responsible AI use was in place. Among 264 staff respondents, 21.64% said staff training on safe and responsible AI use was in place. These figures describe respondents to that survey, not all nonprofits. See the 2026 NTEN report.
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