One of your board asked last night whether the organization is being responsible about AI. One of your staff members has been using it to clean up case notes. Another quietly wonders whether their job is at risk. The people you serve expect you to protect their information. Somewhere in the middle of all of that, you are trying to figure out what AI actually is, whether your organization is ready, and how to move forward without making a mistake.
The pressure to either ignore it or just pick something and move forward is real.
This is the second in a four-part series on what a People-First approach to AI means across nonprofit organizations. Part 1 addressed the board’s governance role. This post focuses on what the philosophy means for executive directors, CEOs, and senior leadership teams.
Start With Your People, Not the Technology
The biggest mistake nonprofit leaders make when approaching AI is starting with the tool. They see a demo or hear what a peer organization is doing, and the conversation immediately becomes about whether to adopt that specific platform. It happens with technology decisions constantly.
The better starting point is your team’s reality. Where are staff spending time on work that isn’t mission-critical? What administrative tasks are eating hours that could go toward direct service? What roadblocks have frustrated your team for years?
Those questions change the technology conversation entirely. You stop asking “should we use AI?” and start asking “what problem are we actually trying to solve, and is AI the right tool for it?” The difference between those two questions is the difference between a system your staff will use and one that quietly frustrates them.
Your Staff Will Be Watching How You Do This
People-First AI is more than an approach to technology. It is a philosophy about leadership. Your staff will draw conclusions about what kind of leader you are based on how you handle this.
Are they being consulted before decisions are made, or informed after? Are they getting real training and time to learn, or a single walkthrough and a user manual? Do they feel like this is being built with them or handed down to them?
Those distinctions matter more than the technology itself. Organizations that bring staff in early, create space for honest concerns, and invest in training see stronger adoption. They also come out of transitions with their team’s trust intact, which is far harder to rebuild than any system.
The Decisions That Belong at Your Level
There is a set of decisions that belong squarely with executive leadership.
Where does our data live, and who controls it? This is not a question to delegate entirely to your technology staff or a vendor. You need to understand what platforms your organization’s data passes through, whether client information is being retained or used by third parties, and whether your tools comply with any funder or regulatory requirements. If you cannot answer those questions today, that is where to start.
Are we building on infrastructure we already own? Building on platforms your organization already uses, your Google or Microsoft environment for example, rather than introducing new vendors keeps costs down, reduces risk, and means you still own everything you built if a vendor relationship ends.
What does a responsible rollout actually look like? A thoughtful rollout with proper planning, staff input, and real training will outperform a rushed one every time. Build the implementation timeline around your team’s capacity, not a product launch date.
The organizations that benefit most from AI use it to protect and expand the capacity of their people. More time for program staff to focus on relationships. Better data for leadership to demonstrate impact. Sustainable workloads that help you retain the people you worked hard to hire.
Part 3 explores what People-First AI means for the frontline staff doing the daily work of your organization.