A development director at a regional foundation told us recently that she'd started asking grantee applicants a new question in the first call: "Can you describe your data governance practices?" Two years ago, she said, the question didn't exist. Now it's standard.
She's not alone. Across the foundation landscape, funders are beginning to connect data infrastructure to impact credibility — and organizations that can answer the question clearly are advancing in competitive funding cycles. Organizations that can't are quietly scoring lower on dimensions they didn't know were being evaluated.
Why Funders Are Starting to Care
The shift has two drivers. The first is the rise of AI. As AI tools spread across the nonprofit sector, foundations are beginning to ask the same question regulators are asking of corporations: what is the data foundation underneath the AI, and is it governed responsibly? MacArthur Foundation's AI policy now extends explicitly to grantees. McGovern Foundation's 2025 grantmaking explicitly requires community AI governance as a funding condition. This is not a trend — it is a policy shift.
The second driver is impact reporting. Foundations have always asked grantees for outcome data. What's changing is the follow-up: not just "what are your outcomes?" but "how are you producing this number, and how would someone else reproduce it?" The question beneath the question is about data governance — about whether the organization's data systems are reliable enough to make the impact claims defensible.
The Problem With Existing Signals
The tools funders currently use to evaluate grantees were not designed to assess data maturity. The Form 990 is a tax compliance document. Candid's Seal of Transparency evaluates organizational transparency — not data infrastructure. Charity Navigator rates financial health, accountability, and impact reporting — but a nonprofit can earn a high Charity Navigator rating while operating entirely on manual spreadsheets.
The information asymmetry is significant. A funder sees a polished dashboard in a grant report and has no way to assess whether that number comes from a governed data process or a one-time manual calculation that someone will struggle to reproduce six months from now. The dashboard looks the same either way.
Funders are beginning to solve this problem by asking directly. Organizations that have documented governance practices are able to answer. Organizations that haven't can't — and that silence is starting to register.
What "Data Maturity" Actually Means
Data maturity is not about having sophisticated technology. It is about having clear, shared practices around how data is collected, defined, owned, used, and protected — regardless of what tools are involved. A nonprofit with Google Sheets and a well-documented business glossary has more data maturity than a nonprofit with Salesforce and undefined donor categories.
Maturity frameworks typically evaluate organizations across several domains: strategy and leadership (does the organization treat data as a strategic asset?), governance and definitions (are key terms agreed upon and documented?), data quality (are quality problems identified and addressed?), infrastructure (do systems support reliable, repeatable reporting?), and analytics capability (can the organization use data for internal decisions, not just external reporting?).
The majority of nonprofit organizations, when formally assessed, score in the lower-middle stages of maturity — what Data Orchard calls the Learning and early Developing stages. Very few organizations reach the top. The organizations that do tend to have one thing in common: they invested in data governance infrastructure before they were required to by funders, not in response to a grant deadline.
The Credentialing Gap
There is currently no standardized, verifiable data maturity credential that a nonprofit can earn and a funder can reference. Funders are improvising — each foundation developing its own rubric, or more commonly, relying on informal judgment during conversations. This creates an evaluation problem on both sides: nonprofits don't know what to demonstrate, and funders don't have a consistent standard to apply.
The market gap: No tool currently serves as a trusted, shared bridge between how nonprofits assess their data maturity and how foundations evaluate it. There is no standardized data maturity credentialing system that a nonprofit can earn and a funder can reference in due diligence. This is the defining inefficiency of the nonprofit data landscape in mid-2026.
What funders are looking for — even when they don't use the word "governance" — is evidence that the organization's data practices are documented, repeatable, and owned by someone. Three questions funders are beginning to ask, in various forms:
Can you describe your data governance practices? (The baseline question — do you have a conscious practice, or is it ad hoc?)
How do you ensure the accuracy of the outcome data you report to funders? (The quality question — is there a process, or is there one careful person?)
Who is responsible for your organization's data systems and decisions? (The ownership question — is there a named person or role, or is it shared/unclear?)
How to Get Ahead of the Question
The organizations best positioned for this shift are those that have started without being asked. Specifically:
Complete a formal assessment. An honest, scored evaluation of your current data practices — across strategy, governance, quality, infrastructure, and analytics — gives you a baseline that is both internally useful and externally communicable. It also gives you a prioritized list of what to address first.
Document your definitions. A business glossary — shared definitions of your key terms — is the single most high-leverage governance document an organization can maintain. If Finance, Development, and Programs are using the same word to mean different things, you will produce conflicting data and you will not be able to explain the discrepancy to a funder.
Establish data ownership. Someone should be responsible for your data governance decisions. That person does not need to be a data engineer. They need to be empowered, documented, and known to the rest of the organization.
Earn a verifiable credential. The Steward Certified: Data Governance & Quality credential is specifically designed for this moment — a structured, independently reviewed assessment result that a nonprofit can share with funders and boards as verifiable evidence of data governance commitment. It is not a self-report. It is reviewed and issued by SSA after independent evaluation.
The assessment is the starting point.
46 questions. 7 domains. An honest score and a clear map of what to address first. Free for all organizations — and the first step toward a credential your funders can reference.
Take the Free Assessment →