Is North America ready for the Race of the Century?
The last piece of this 4 part series explores the possibilities for North America inside or out of the Space and AI race.
This is paper 4 of 4 focused on a thesis and assessment on what the AI & Space Race could mean for North America. This is the closing argument:
Picture North America as it actually is right now.
Three countries with three separate foreign policies, tariff fights, border frictions, water disputes & political winds blowing in different directions in all three capitals.
Trust at its lowest point in a generation — while the defining race of this century is already underway, and the United States’ greatest economic rival, China, is running it with a plan measured in decades.
That is the actual picture.
This series spent three papers laying out why this race favors a united and coordinated North America:
Part 1 pictured the finish line: one team, three cars — three nations, three flags, three sets of laws, sharing a strategy, not a chassis.
Part 2 showed what the race is made of: the biggest physical build since the railroads.
Part 3 mapped everything it takes to win and found that no single nation holds the complete list. Only this continent does.
This last paper makes the argument the whole series has been walking toward, and it is simple:
First, let’s be clear that North America can lose this race.
The first way I believe we can lose it is by remaining divided as a continent in relation to competing to win this specific race that could impact everyone in the world.
The second is the risk of leaving North Americans outside of the race of the century.
The first loses the race. The second loses the consumers and the builders of the future.
So this paper has two focuses:
show what going alone costs each country.
show what the deal must look like for the people doing the building.
Start with the United States alone. It spends the decisive years rebuilding, at enormous cost, what already exists next door — because it does not have enough domestic capacity in mineral processing, manufacturing, power generation, and skilled labor to move at the speed this race requires.
All of the committed investments from companies like OpenAI, Oracle, TSMC, Micron, SpaceX, NVIDIA, Microsoft, Google, Meta, Anthropic and more will need to be diversified in their customer base. We are already seeing financial crunches and fears from companies like Meta on their AI strategies. The investments have been massive but the results are still to be seen. Through leveraging these investments through a full support from Mexico & Canada as partners in this race, these historic investments could be protected from downturns.
As part 2 already signaled, it showed what happens to the ground the US leaves unattended: someone else moves in, port by port, station by station.
Mexico is today a nation to be transformed: Historically it has had low-cost tier of someone else’s supply chain. Through AI, the Mexican labor force could deliver never before seen productivity & growth.
The great opportunity lies in the country’s youngest large population of the continent — 130 million people, more than 110,000 new engineers a year — they should be part of a North American AI strategy to assure they are future builders and consumers in the AI Age.
An AI-ready Mexico is not a favor anyone grants. It is a load-bearing wall in North America’s own economy.
Canada alone may well succeed — and that is the trap.
Look closely at how a solo Canadian success ends: the research gets commercialized by companies elsewhere, the minerals ship out raw, and the talent drifts south. A stronger Canada inside a weaker continent. Good for Canada. Not enough for North America.
Three countries, three partial hands. More and more, scale belongs to coordinated blocs, not isolated countries.
And the clock is not neutral: Fertility is below replacement in all three nations. The demographic window is narrowing. We should not waste the workforce we have while waiting for another generation to solve the problem.
Suppose we build it all — the plants, the grids, the data centers, the launch sites — and most people end up outside the deal.
The worker replaced by AI was also a customer. Every person automated out of an income is a buyer subtracted from the market. Economists have begun to measure this risk: a 2025 study of European regions found that where AI innovation doubled, labor’s share of income fell.¹ That is not yet a settled law of economics. It is a warning we would be foolish to ignore.
A continent that automates its people out of the market is a factory canceling its own orders.
This is something that needs to be addressed by all nations of the world but specifically in North America. We share so much together that we cannot ignore the risks of not preparing for the AI age.
Beginning with skills to prepare people to work through AI, not only next to it.
Then we need to really give some thought to new ownership models that can protect labor from being deployed so far from the value that will be created in the AI age.
By this I mean that we need to think about giving the workforce a piece of the pie; a real financial share in the value they help create.
Training makes the worker more capable. Ownership gives the worker a claim on the future.
And before anyone reaches for a political label, look at who is already doing this. KKR — private equity, not a charity — has granted equity to hourly workers across dozens of the companies it owns, because businesses where workers hold a piece perform better and sell for more. When it sold one Midwestern door manufacturer, the truck drivers walked away with six-figure checks.
Ronald Reagan called employee ownership “a path that befits a free people.” In the United States today, roughly fifteen million workers participate in employee stock ownership plans, holding about two trillion dollars in plan assets.² Young employee-owners show far higher household net worth than their peers.³ Manufacturing plants that adopt these plans measure productivity gains, not losses.⁴ This is not redistribution. It is the most capitalist idea there is: more capitalists.
Imagine a new data center in Querétaro. The technicians are trained to run AI-assisted systems and paid well for the work. But the deal does not end with the paycheck. A small portion of the project sits in an employee ownership or profit-sharing structure. If the facility grows in value, their stake grows too. They are not only maintaining the future. They own part of it.
Now let’s be honest about the terrain, because I know it firsthand. Employee ownership is common in the United States — and it stops at the border. A worker in Ohio gets a stock plan; the worker at the same company’s plant in Querétaro, doing similar work, gets a paycheck.
Mexico is closer to this idea than most people think — Mexican law already requires companies to share profits with employees, ten percent, every year, by statute. The habit of sharing results is not foreign there but it’s definitely not the same.
What’s missing is the stake that compounds: Mexico has no equivalent of the ESOP, and most global stock plans were simply never extended south. That is not a reason to drop the idea. It is the challenge that we would like to throw out there.
We believe that the first companies to carry real ownership across the border will get the best engineers, the lowest turnover, and a loyalty no wage can buy. How to build it — the legal structures, the tax treatment, the first movers — deserves its own paper, and NA77 will write it.
We are not asking the Americans to adopt a new idea; We are asking them to export their best one. The only reason this idea is on the table is because of AI’s transformative effects on inequality, which is already a serious problem today.
Here is why this matters strategically, not only morally. China’s advantage is command & control: it can concentrate capital and direct construction from the top, and it has proven it can build at staggering scale.
Our advantage should be participation: combining scale with broad ownership from below. That is not an advantage we hold by default. It is one we are uniquely positioned to develop — if we choose to. This is why open AI models should be something to assess for the West. Something that China began with and has had tremendous success with.
We must not wait for the grand North American treaty; governments will end up being involved whether they want to or not — energy, minerals, borders, labor and orbits run through them. But action does not have to wait for perfect political alignment.
North America was built from below long before any agreement was signed — by families, companies, and border cities that never asked permission to belong to both worlds.
Companies, cities, investors, universities, and workers can start now: plant by plant, project by project.
Now go back to the finish line where this series began.
One team, three cars.
An AI model funded and trained in the United States, running on Canadian power and minerals, operating in plants Mexican engineers help design and run — launched on rockets whose components crossed two borders — and built by people who hold a piece of it: technicians in Querétaro, linemen in Alberta, founders in Austin.
Every part of that picture already exists somewhere on this continent.
The only thing that has never existed is the decision to run it as one team.
The race is real. The pieces are here. The team is possible. And the prize was never the machine — it was the kind of people we become while building it.
Scale is engineered. Freedom is chosen.
What comes next. The next build is not starting from a blank slate. Space already carries more than a million pieces of debris, and our continent still carries the damage of earlier industrial eras. But there is still time to avoid repeating the old pattern at a much larger scale. How North America builds clean — on the ground and above it — is the next series. This publication will take it on by name.
Sources
Antonio Minniti, Klaus Prettner & Francesco Venturini, “AI innovation and the labor share in European regions,” European Economic Review (2025) — https://doi.org/10.1016/j.euroecorev.2025.105043
NCEO (National Center for Employee Ownership) — ~15.1M total ESOP participants (~11M active); ~$2.06T in plan assets. https://www.nceo.org/research/research-findings-on-employee-ownership
NCEO / Aspen Institute — national observational study of workers ages 28–34: employee-owners showed 92% higher median household net worth and 33% higher median wage income than peers. Observational, not causal. https://www.aspeninstitute.org/publications/employee-ownership-and-esops-what-we-know-from-recent-research-2025/
2026 study of U.S. manufacturing establishments — ESOP adoption associated with a total productivity increase of ~5.6–6.7% between measurement periods (not annual). https://www.aspeninstitute.org/publications/employee-ownership-and-esops-what-we-know-from-recent-research-2025/