In most nonprofits, the person giving the update on "how AI is going" is also the person with the least in common with the staff who would actually use it day to day. A survey of 917 nonprofit professionals, published by NTEN and The Bridgespan Group in September 2026, found that 50% of executives use AI daily. Only 38% of staff do. Executives also report feeling more comfortable with the tools, 67% versus 55% for staff. If you lead a nonprofit, the AI picture in your head is probably your own picture, not your organization's. I hear this almost every time I talk with a nonprofit ED about AI. She can describe her own use of the tools in detail. She assumes her program staff use them about the same way, at about the same rate. In my experience, that's almost never true. What does the data actually show? It shows a usage gap and a comfort gap, and the usage gap is the bigger one. 98% of respondents in the survey use AI in some capacity, according to Nonprofit Quar...

Most nonprofits that get AI working don't stall on the pilot. They stall right after it, when the plan to scale needs a budget line and an owner, and neither shows up. A new survey of 119 AI-powered nonprofits found that 90% have a plan to scale their AI work. Only 24% say they have the resources to actually execute that plan, according to Fast Forward's 2026 AI for Humanity Report , accessed 2026-09-29. That's a gap of 66 percentage points between an intention written down and a plan an organization can actually run. I've seen this pattern before AI ever entered the conversation. A strategic plan gets built, everyone nods, and then Monday morning shows up and nothing in the plan tells anyone what to do differently. AI hasn't solved that gap. It's just showing up inside it now, wearing its own name. How many nonprofits already have a working AI pilot and a plan to expand it? A lot, and the number is growing. Fast Forward surveyed 119 nonprofits already using...

Most nonprofit AI projects never start with a decision. They start with a tool. A new report on AI operations at nonprofits makes that specific. Among nonprofits that already have at least one AI initiative running in production, just 12% say their most recent AI initiative began with a clearly defined problem. The rest started elsewhere: 37% adopted a vendor's recommended use case, another 37% chose a platform first, and 13% never settled on a scope at all ( Coastal / Oxford Economics, "The AI Operations Report 2026: Nonprofit," accessed September 23, 2026). That's not a story about slow adoption. Every organization in the sample already has AI live somewhere. It's a story about what happens when "live" arrives before "why." A note on the source before we go further: the report's page shows only a 2026 copyright, no month or day for when it was published or fielded. That's worth saying plainly rather than dressing it up with a date...

Because almost none of the AI your team uses ever touches a goal. Two independent surveys published this year, run by different organizations, using different methods, land on nearly the same number. Nonprofit AI adoption is close to universal. What it changed is not. I keep hearing versions of the same sentence from EDs. "Everyone on my staff uses ChatGPT now." Said with a kind of relief, like the AI problem is handled. Then I ask the next question. Has it changed what your team delivered this quarter? Most go quiet. How widespread is AI use at nonprofits right now? Nearly universal, and rising fast. Bridgespan Group and NTEN surveyed 917 nonprofit staff and executives between late April and mid June 2026, about 59.7% executives and 40.3% staff ( Bridgespan, "Choosing Your AI Path," published 2026-08-20, accessed 2026-09-15 ). Virtuous, in a separate survey of 346 nonprofits, found that 92% have adopted some form of AI ( Virtuous, 2026 Nonprofit AI Adoption Re...

What duty does a nonprofit board have to oversee AI? A board's existing fiduciary duties, care and loyalty, now explicitly cover AI. Gene Takagi, one of the most cited voices in nonprofit law, laid this out plainly in a piece published August 16, 2026. The duty of care means a board must actively understand how AI is being used inside the organization, not wait for staff to bring it up. The duty of loyalty means weighing AI's efficiency gains against any harm it could cause to the mission, to beneficiaries, to staff, or to donor trust. That is a real shift. Until recently, "we're experimenting with AI" was a staff-level update, mentioned in passing if at all. Takagi's argument makes it a governance matter. A board member who never asked how AI touches the organization is not neutral on the question. They are behind on a duty they already hold. Source: Gene Takagi, Governance and AI: Fiduciary Duties , Nonprofit Law Blog, published August 16, 2026. How big...

What's actually happening I have sat in enough of these conversations to recognize the pattern. A director gets a demo from a vendor at a conference, or a peer organization mentions a tool that "changed everything," and the instinct is to move fast. Fast feels like leadership. So the organization buys the platform, or signs up for the pilot, and only then does anyone ask what it's for. This is the same mistake I see nonprofits make with strategic plans. A forty-page document gets written, approved by the board, and filed. Nobody translates it into what changes on a Tuesday. The plan is real. The connection to daily work is not. AI tools are landing on top of that same disconnect, except now the artifact isn't a binder, it's a subscription. I'm starting to hear a version of this at the board level too. Funders are asking nonprofits how they use AI, and a board wants an answer that sounds current. That pressure creates the same shortcut: adopt somethi...

What actually got taken Ask what AI absorbed first in a small nonprofit, and the list is consistent. First drafts of donor letters. Grant report boilerplate. Meeting notes. Volunteer scheduling emails. Social copy. The intake summary nobody wanted to write. Look at what those have in common. Every one of them is a task with an edge. You start it, you finish it, and you can point at the thing you made. The letter exists. The report is submitted. The notes are in the folder. Those tasks were tedious. They were also, for a lot of people, the only proof they had that they did anything that day. A program coordinator does not go home holding an outcome. Outcomes take months and belong to the whole organization. What she goes home holding is the twelve things she finished. When AI takes the twelve things, the tedium leaves and the proof leaves with it. Nobody planned that. It is a side effect, and side effects are the hardest thing to notice because no line item shows them. Why it la...

Florida nonprofits are reviewing their bylaws because of HB 797.  That's the right move. But while boards are opening the governance binder, there's another document they should review at the same time. The one that tells them whether the organization is actually making progress . Those are not the same thing. HB 797, which took effect on July 1, updates how Florida nonprofits are governed. Boards are reviewing conflict-of-interest policies, meeting procedures, officer responsibilities, and other governance documents to make sure everything reflects the new law. That's important work. Good governance protects the organization. But governance and execution are different conversations. Your bylaws tell you who can make decisions. They don't tell you whether the organization made the right ones last month. That's the gap I see in many nonprofits. Ask an executive director where the strategic plan is, and they'll usually point to a document. Ask five staff members w...

McKinsey just published one of the most honest things about AI adoption in years. Nearly 8 in 10 companies report using AI, and nearly the same number report no significant impact on earnings. They called it the "gen AI paradox." Companies are everywhere on AI. And almost nowhere on results. Here's what the data actually shows (McKinsey State of AI, 2025): → 88% of companies deploy AI in at least one function → Only 6% of companies see more than 5% of EBIT directly attributed to AI → Nearly two-thirds have not begun scaling AI across the enterprise → Fewer than 30% of CEOs personally sponsor their company's AI agenda The technology is not the problem. The leadership approach is. The real diagnosis Most companies bolted AI onto existing processes. Copilots on top of old workflows. Chatbots next to manual work. Assistant tools that assist nothing at scale. McKinsey calls this "horizontal" adoption. Wide, visible, and nearly impossible to connect to reven...

High employee turnover drains resources and damages morale. This article provides actionable strategies to understand your turnover rate, identify its root causes, and implement effective retention strategies. Whether you have five minutes or an hour, you'll find valuable insights to build a more stable and engaged workforce. The High Cost of Employee Churn: Why Turnover Matters Employee turnover, the rate at which employees leave an organization, is more than just a statistic; it's a vital sign of workplace health. High turnover can cripple a company's bottom line and create a toxic work environment. While some turnover is inevitable (and even desirable in certain cases – more on that later), excessive turnover can signal serious underlying issues. The financial impact alone is staggering. Replacing an employee can cost anywhere from six to nine months of their salary, according to SHRM . These costs include recruitment fees, lost productivity during the vacancy, onboa...