TRANSPARENCY IN PRACTICE
My AI Approach
As a consultant who helps nonprofits build AI governance, I apply the same framework to my own practice that I bring to clients. Here is what that looks like.
Sarah Downey Consulting — Version 1.0 · February 2026 · Reviewed twice yearly
"A culture of secrecy has crept into how people and organizations use AI ~ and that culture needs to change."
Many professionals keep their AI use quiet. There is an unspoken sense that using AI means something is being hidden, that it is doing the work for you in ways that feel different from how things have always been done. That culture needs to change.
AI is changing how we relate to knowledge. When that happens, critical thinking and transparency do not become less important, they become the whole point. Getting clear about how we use AI, what we use it for, and what values guide those choices is one of the most important things professionals can do right now.
One of the core things I teach nonprofit organizations is to map their AI use directly to their values, to show concretely how their values shape the choices they make. What follows is that same exercise, applied to this practice.
Five Values. Five Commitments.
01 COLLABORATION.
Every engagement is a partnership. We build together.
Collaboration means AI functions as a genuine working partner, not a replacement for human thinking, and not something work gets handed off to. There are specific tasks AI does well: synthesizing large volumes of text, surfacing patterns across a long transcript, connecting threads when a clear goal is in view. That is where it earns its place.
What no AI tool can bring to the partnership is sector knowledge, ethical judgment, relational intelligence, or the capacity to read what is actually happening beneath the surface of an organization. The collaboration only works because both sides contribute something the other doesn't have.
IN PRACTICE
When I conduct a client interview, AI may help synthesize the raw transcript, identifying themes and surfacing patterns. The analysis, interpretation, and recommendations that follow are mine.
02 PRACTICAL WISDOM
Real-world experience. Solutions that work, not just look good on paper.
Practical wisdom is the knowledge that comes from working inside the nonprofit sector across many roles, from frontline work to executive leadership, over more than two decades. It lives in experience, not in datasets. It is the kind of knowing that understands what a struggling organization actually sounds like, and what it needs.
This value shapes the limits of AI use more than any other. There are things that will not be delegated to AI. Because sector discernment is what clients are engaging this practice for. That discernment is not something a model can replicate.
IN PRACTICE
When a client is ready to build an AI policy, the starting question is never which tools to use. It is what kind of organization do you want to be. Technology follows values.
03 COMPASSIONATE LEADERSHIP
Foster safety and inclusion while asking honest questions that move things forward.
Compassionate leadership means making space for all voices, showing up to each engagement with genuine care for how people are arriving, what they carry, and what they need to participate fully. Safety and inclusion are the conditions for good work.
In an AI context, this value points in two directions. First, AI can be a genuine accessibility tool, something that reduces barriers, supports different ways of processing, and frees cognitive load so people can bring more of themselves to what matters. Second, it demands vigilance. AI tools reflect the biases in the data they were trained on, and those biases can show up in outputs. Using AI responsibly means actively checking for where it may be introducing inequity, and not letting it shape recommendations that affect real people.
IN PRACTICE
AI outputs are never used directly to inform client recommendations without human review for bias, fairness, and contextual fit.
04 BOLDNESS
Challenge old assumptions and reimagine what's possible, with care.
Boldness means seeing where current systems are not serving people well, where habits and patterns are being replicated simply because they are familiar, and being willing to suggest a different path. It means keeping one eye on what is possible and having the conviction to name it.
Most AI adoption accelerates what already exists. The work here asks a different question: what if this moment were used to build something better? The framework this practice is built on, values-first, human-centered, governance as a living practice, is a direct expression of that belief.
IN PRACTICE
The first question in any engagement is never which AI tools to adopt. It is what is actually working in this organization, and what isn't. AI applied to a broken system just accelerates the break. That clarity comes first, and sometimes it leads somewhere unexpected.
05 INTEGRITY
Transparent, grounded, values-aligned. You'll always know where I stand.
Integrity means being transparent in practice, not just in principle. It means naming the tools, describing the protocols, and being clear about what AI touches and what it does not.
AI is a tool in the process. The judgment, the responsibility, and the accountability for every deliverable that leaves this practice belong to a person. That standard does not shift depending on which tools were involved.
IN PRACTICE
This practice uses AI tools only at the paid, business-tier level with formal data protection agreements. Client information does not enter AI tools without consent. Indigenous community data does not enter AI tools, period. These are the standard this practice is held to so clients always know where things stand.
Questions about this approach?
I welcome conversations about how AI is used in any engagement ~ with current clients, prospective clients, or anyone in the sector working through their own approach. Transparency is the point.
Formal AI use policy available to clients on request · Last reviewed February 2026