Why I Should Stop Talking About AI. And Why I'm Not Going To.

Same lines, two faces. So does competition. -“My Wife and My Mother-in-Law,” W. E. Hill, Puck, 1915. Public domain.

I have an unfair advantage, and the smartest thing I could do is keep quiet about it.

For the better part of a decade I have spent most of my waking hours trying to understand artificial intelligence. Where it came from. What it can do. Where it is going, and how fast. I started before the acronym meant much to anyone in my world, and somewhere along the way the understanding compounded into something that functions, in a strictly economic sense, like a moat. I can see a few steps ahead. In rooms full of capable people, that turns out to be worth a great deal.

I assumed the moat would be gone by now.

It is 2026, and it is not.

That is the part I keep turning over. I genuinely believed that by the middle of this decade the advantage would have dissolved. The tools are free or nearly so. The frontier models sit one tab away. The most capable intelligence ever built is available to anyone who can type a sentence.

Take agentic AI, the systems that do not just answer but act, that can carry out a multi-step task on your behalf while you go do something else. It has been commercially available for a while now. I work in the nonprofit sector, and I informally poll nearly every audience I speak to about it. The share who tell me they understand it well enough to have actually built or used something with it is still under two in a hundred. The capability is everywhere. The fluency is almost nowhere.

So the gap between the people who understand what is happening and the people who do not has not closed. In many rooms it has widened. And that gap is a good part of why I am writing this.

I want to be honest about the incentives here. Every instinct sharpened by a career in a competitive field should urge me to protect the gap, not narrow it. Advantage is something you guard. You do not hand the map to the people you are racing.

So then, why have I dedicated the past nine years talking about the possibilities and opportunities that exist if we harness AI to scale generosity collectively? Not because I am noble. Because I cannot make the math of staying quiet agree with the values I hold closely.

To explain why, I have to take you back to a classroom.

I studied international economics at Cambridge, and later wrote my graduate capstone at Notre Dame on the economic theory of competition. If you want to understand a person, find out what they were obsessed with at twenty-two. I was obsessed with why some societies generate astonishing prosperity and others do not, and the answer I kept arriving at had competition at its center. Competition is the engine. It is the thing that turns ordinary self-interest into roads and medicine and light.

My favorite period in history is the Industrial Revolution, and not for tidy reasons. It was brutal. It was unequal. It ran on labor and lungs it had no right to spend. But it was also the last time the human imagination seemed to operate without a ceiling, when an ordinary person with a workshop and an idea could look at a need and simply decide to fill it. Something in that entrepreneurial nerve still moves me.

Here is the detail most people skip. The same century that built modern competitive capitalism also built modern philanthropy. They were not enemies.

They were twins, born in the same room.

Andrew Carnegie crushed his rivals in steel and then wrote the essay that founded modern American giving. The Rockefeller fortune, assembled with a ruthlessness that became legend, funded the foundation that helped eradicate hookworm and yellow fever and seeded the science that later fed a planet. The men who embodied competition at its most unsentimental turned around and built the institutions we now hold up as competition’s opposite.

We spent the next hundred years forgetting this. We sorted the world into two bins. Competition over here, generosity over there. Markets that take, charity that gives. We told ourselves that one cancels the other, that you are either building wealth or building good, and that the honest word for trying to do both is naive.

That story is not a law of nature. It is an interpretation. And we assigned it.

I was reminded of this listening to Mo Gawdat, the former Google executive, working through the future of AI on a podcast recently. Buried inside a long and sometimes bleak conversation on the future of humanity was a single idea I have not been able to put down. Competition, he argued, does not have to serve only capital. That is not what competition is. That is an interpretation we layered onto it over the past century, and there is no reason the next century has to inherit it. The real prize, he said, is to marry the success of humanity with the success of the entrepreneur.

I do not agree with Mo about everything. But on this he is exactly right, and he is describing something I have watched up close for years.

This week I was talking with Woodrow Rosenbaum, and we admitted something slightly embarrassing to each other. We are still surprised by AI. We still catch ourselves startled when a model does something intuitive, or creative, or simply better than we could have done it ourselves.

Which makes no sense from a logical perspective. If anyone should have stopped being surprised, it is the two of us. We know exactly what these systems are being built to do. The entire point of the AI arms race is to build AGI (Artificial General Intelligence) — an intelligence that surpasses our own. Surprise, at this stage, is irrational.

So why does it persist? I think it is because we are running old software in our own heads. I grew up with the computers of the 1990s, machines that could barely manage one fragile task at a time. Some part of me still expects technology to be that brittle. The distance between that beige box and a system that can reason across a thousand domains is about thirty years. Thirty years is nothing. We never had time to update our intuitions, so we kept the old ones.

And here is what I have come to believe. The same outdated software that makes us underestimate AI is the software that makes us assume competition must mean extraction. We are reasoning about a 2026 world with mental models built for a different century. We are surprised by what intelligence can do, and we are equally surprised by the suggestion that competition could do anything but enrich a few. Both are failures of imagination. Both can be corrected.

Which brings me to the sector I have spent my life inside.

For all its frustrations, the nonprofit world has been running the other operating system the entire time. It is fiercely competitive. Anyone who tells you otherwise has never watched two organizations chase the same grant, or two leaders fight for the same donor’s attention and trust. But the competition is pointed somewhere different. It is aimed, structurally and by design, at the greatest social benefit it can produce. The scoreboard is not shareholder return. The scoreboard is human good.

For a long time this looked quaint to the rest of the economy. Lately it has started to look like foresight.

Listen to the language coming out of the for-profit world now. Flourishing. Humanity. Social benefit. Stakeholders. In 2019, the Business Roundtable, the assembled chief executives of America’s largest companies, formally announced that the purpose of a corporation was no longer only to serve its shareholders. The words arrived as if freshly minted. They were not. The nonprofit sector has been speaking that language, and living it, for centuries. The market is discovering the antidote, and it does not yet realize the nonprofit sector has been holding the bottle the whole time.

I want to be careful here, because this is where the argument usually goes wrong. The point is not that competition is the disease and charity is the cure. The point is the opposite. The nonprofit sector is the living proof that competition was always capable of serving the public good. It is not competition’s antidote. It is competition’s other half, the half we agreed to forget.

I will give you the example I know best, and I will tell you plainly that I am not a neutral party to it.

I am the Chief AI Officer at Virtuous. Virtuous is a for-profit company. It is backed by investors who expect returns, run by people who think hard about growth, and entirely comfortable with the word competition. And it was built, deliberately, around a double bottom line. The second number is not revenue. It is a net increase in global generosity, with a stated goal of ten billion dollars, and it is something we measure and report on, internally and externally, not as a slogan but as a result we hold ourselves accountable for.

That is what drew me. Not the mission statement. The accounting. A company that decided the success of the enterprise and the success of humanity were not in tension, and then put the second one on the books where it could be counted.

This is the synthesis I keep trying to describe. Not entrepreneurship with the ambition sanded off. Not charity dressed up in a business plan. A genuinely competitive enterprise that refuses the false choice between winning and doing good, because the choice was never real. The entrepreneur can win and humanity can win, in the same ledger, at the same time. The framework that says otherwise is not economics. It is a habit.

There is a final detail I find almost too neat to be true.

In 1956, a small group of researchers gathered at Dartmouth to ask a simple question: could a machine be made to think? The gathering needed money, and much of it came from the Rockefeller Foundation. That summer, they gave the field its name. They called it artificial intelligence . And the foundation that paid for the room sat on a fortune built in oil, through some of the most ruthless competition American business has ever seen.

Competition made the wealth. Generosity aimed it. And what it aimed at, eventually, was the very intelligence we are now arguing about. The thread has been running through the whole story, and almost no one stops to notice it.

Now connect that thread to the tool open on your screen.

For the first time in history, an instrument that knows something about nearly everything, and can seemingly do almost anything, sits within reach of almost every nonprofit professional. Not behind a guild. Not reserved for the organizations that could afford the consultants and the headcount. For anyone with a connection and a question, the price of admission has collapsed to almost nothing. Sit with who that lands on. A sector that has run on scarcity for its entire existence, perpetually asked to do more with less, has just been handed something close to abundance. The capacity to build, to analyze, to create, to attempt what was always out of reach, has been opened in a way the Industrial Revolution could only dream of.

The honest worry is that the benefits will not be shared. They are already concentrating, pooling at the top among those best positioned to capture them. And the most basic form of that inequity is access itself. Much of the world still lives without reliable electricity or a connection, which means the most powerful tool ever built reaches those people last, if it reaches them at all. That gap is not a footnote to this story. For the nonprofit sector, closing gaps exactly like it is the whole job. The technology is inevitable. Its fair distribution is not. That is the default trajectory, and defaults are powerful.

But a default is not a destiny. It is an invitation to do otherwise. If the tools that can do almost anything are now within reach of so many who were locked out before, the circle of people who can build has widened beyond anything we have seen. More of us have real agency now, whether that agency is large or small. And for those of us inside a sector built to aim competition at human good, and to carry it to the people technology reaches last, that agency is not only an opportunity. It is close to a moral imperative.

So here is my actual hope, the one underneath all the theory. I want to see the most intense, most profound entrepreneurialism this sector has ever known. I want nonprofit leaders to look at problems that were structurally impossible to solve a decade ago and decide to solve them now, because the constraint that made them impossible has just dissolved. I want the people who already know how to point competition at the right target to pick up the most powerful tool ever built and aim it.

That is the competition I want to win. Not the race to extract the most value before everyone else catches on. The race to prove, at scale, that the entrepreneur and humanity can flourish in the same motion.

Which is the long answer to where I started.

The advantage was never the point. A moat is only worth guarding if the thing inside it is worth keeping to yourself, and the thing I understand about AI is not. It is worth more handed out than hoarded, because the future I want is one where the gap I have been describing finally closes, where the understanding stops being an edge and becomes a baseline.

There is a tidy logic that says I should stop talking about this. Protect the lead. Let the surprise keep working in my favor.

I am not going to. I cannot make that math agree with anything I believe about what this technology is for, or about the people I want to spend the rest of my life building alongside. The map is not worth more in my pocket than it is in yours.

So I will keep talking about AI and keep competing for social good. And I hope you will too.

About the Author

Nathan Chappell, MBA, MNA, CFRE, AIGP is Chief AI Officer at Virtuous Software and co-author of Nonprofit AI and The Generosity Crisis . He writes about responsible innovation, the future of generosity, and the power of radical connection in the age of AI.