The Last Normal Year - When AI Ends Normal
2026 The Last Normal Year - Week 1
By Rick Aman onWhen AI Ends Normal
"The best way to predict the future is to invent it." — Alan Kay
Two months ago I stood in an innovation and technology building in Idaho Falls and watched a ribbon cut. The Future Tech Building is the kind of facility a community dreams about for a generation. What stayed with me was not the building. It was the timeline. The voters who approved a new community college in our region in 2017 could not have described the technology that this building now houses. They were never asked to. They were asked to choose a direction, and the future filled in the details.
Institutions are always living inside decisions made years earlier. The only real question is whether the next set of decisions gets made as deliberately as that one was.
A Phrase Worth Borrowing
James Mullarney of InvestAnswers, in a recent conversation with Jo Bhakdi, called 2026 "the last normal year." I have borrowed his phrase for this series because it names something I have been watching from boardrooms and accreditation visits across the Northwest: the foundations under our institutions are beginning to move at a different pace.
Let me be clear about what I am claiming and what I am not. I am not predicting. Prediction is a claim about what will happen, and honest people should loosely hold such claims. I am interpreting. There is a difference. A pilot does not predict the weather over the North Pacific; they interpret it, respect it, and plan the route accordingly. Leaders owe their boards the same discipline with emerging technology: not prophecy, but careful reading of what is already in motion.
What I am seeing is this. In 2026, a governing board can still treat artificial intelligence as a side experiment, a trial in one department, a line item that can wait for next year's budget. Beginning in earnest in 2027, AI becomes an operating condition of the institution. We will begin to assume it in budgets, staffing plans, advising, programming, and the questions employers and reviewers ask of us. The AI experimental phase is ending, whether we believe in it or not, and whether we scheduled its end or not.
Over the next six weeks I will take what I believe to be five AI themes, one at a time, and interpret them for the future of nonprofit organizations. The five are these: 1. AI that stops answering questions and starts doing work, 2. intelligence that gets cheap, 3. change that arrives in every organizational sector at once, 4. the leadership and governance question of where the line between human and machine gets drawn, and 5. the premium that cheap answers place on human judgment. But first, boards and leaders need to understand the shape of the change itself, because the shape is what makes this moment different.
The S-Curves Are Colliding
Every technology follows an S-curve: a slow, flat beginning where change is easy to dismiss, a steep middle where improvement compounds quickly, and a plateau of maturity. The telephone took some seventy-five years to run that arc; the smartphone ran it in about a decade. Most of us who lead institutions built our instincts on the flat parts of those curves, where next year reliably resembled last year, with minor adjustments. Psychologists call the habit normalcy bias, the assumption that tomorrow will be like yesterday. It served us well on the flat parts. It misleads us on the bend.
Artificial intelligence is not riding one S-curve. It is riding several at once. Capability is still climbing the steep middle of its curve. Cost is falling just as steeply down its own: Stanford's 2025 AI Index reports that the cost of a given level of AI performance fell more than 280-fold between November 2022 and October 2024. Adoption is now entering its steep middle as these tools move from experiment to infrastructure. When S-curves collide, their effects do not add. They compound.
This is why the plateau of the old curve is the most dangerous place an institution can stand. On the plateau, enrollments look stable, budgets balance, and the strategic plan appears to be working. Everything in the board packet says normal. But the plateau of one curve is often just the flat bottom of the next one viewed from above, and institutions that mistake a plateau for permanence are usually the last to know the bend has already happened beneath them.
We have watched this movie before, at a slower speed. I spent part of my career in colleges that treated the internet as a side experiment: a computer lab here, a cautious online course there, a website maintained by whoever had time. Within a decade it was an operating condition. Registration, instruction, library services, advising, and the expectations of every student who walked in the door all assumed it. The colleges that read that curve early did not merely adopt technology sooner. They redesigned themselves while redesign was still cheap, and they set the terms their slower peers later had to meet. The difference this time is compression. That transition took the better part of fifteen years. The one now beginning will not grant us fifteen.
Winner Takes Most
The steep middle of an adoption curve rewards early adopters in a way the flat parts never did. Capability attracts talent, talent attracts resources, resources buy more capability. The technology world calls this dynamic winner takes most, and it is visible everywhere in the current build-out of computing power, data centers, and energy.
Colleges and nonprofits sometimes assume this dynamic belongs to someone else's sector. It does not. Students choose. Donors choose. Employers choose. The institution that learns fastest begins to set the expectations every other institution is measured against, in responsiveness, in personalization, in cost. Winner takes most does not mean one college or one organization takes everything. It means the rewards concentrate; the distinctive and the efficient pull away, applications and gifts and talent flow disproportionately toward them, and the comfortable middle, neither the least expensive nor the most distinctive, gets squeezed first. I do not offer that as a threat. I offer it as a planning fact. Capabilities built during the steep part of the curve are worth considerably more than the same capabilities built after the new plateau has reset everyone's expectations, because by then they are no longer an advantage. They are merely the price of staying open.
More Than AI Is Moving
It would be a mistake, though, to plan for AI alone, because AI is not the only force in motion. The demographics of college-going are shifting, with fewer traditional-age students in many of the regions we serve. Public funding and public trust are both under pressure. Workforce expectations are being rewritten in real time. Planning for AI alone is planning too narrowly, because these forces do not arrive one at a time. Cheap intelligence is landing on institutions already strained by demography and economics, and the interaction of the forces matters more than any one of them in isolation.
The Question Changes
So the board's question has to change. "What will happen to us?" is a spectator's question, and boards were not seated to spectate. The governing question of the next several years is "What future will we choose?"
That is not a slogan. It is the actual work. A Preferred Future is chosen deliberately or it is inherited by default; there is no third option in which the future politely waits for our planning cycle. The discipline I have used with boards for years still holds, and it matters more now: direction provides continuity while strategy provides adaptability. Mission stays steady. Plans flex. And one question belongs on every agenda, asked of every significant proposal that crosses the board table: Does this move us toward our Preferred Future?
Ask it of the small things as well as the large ones. A contract renewal, a new position, a program that has run the same way for a decade: each either carries the institution toward the future it says it wants or spends its scarcest resources, time and attention, on the future it is leaving. Leaders that ask the question consistently, in season and out, will find that it quietly reorganizes everything else on the agenda.
2026 is the last normal year. What we choose in it will be anything but normal in its consequences. Over the coming weeks we will look at each development in turn, and at what governing boards, presidents, and executive teams should do about them while choosing is still ours to do.
Communities don't drift toward greatness. They choose it.
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At Aman and Associates, we work with governing boards, CEOs, and executive teams to strengthen organizational focus and align resources with mission and impact. Through board retreats, strategic conversations, or a focused two-hour Zoom Futuring session, we help leaders step beyond traditional planning to define their Preferred Future and examine what should continue, what should change, and what may have completed its useful life.
Rick Aman, PhD | Aman and Associates
rick@rickaman.com | rickaman.com/articles