One of the seductive things about technology is how easily it travels.

Software doesn’t care whether the customer is in Reykjavík, London or Oranjestad. A cloud platform can be deployed anywhere. A model can be accessed from almost anywhere. A product can launch in another country without opening an office there.

This creates an appealing assumption about international growth: if the product works in one market, find customers with the same problem elsewhere and repeat what worked.

I’ve recently been reminded how dangerous that assumption can be.

I have been helping Smart Data / Snjallgögn, an Icelandic enterprise AI company, explore opportunities in the Dutch Caribbean. Smart Data / Snjallgögn has been successful selling its platform in Iceland, so there was an obvious logic to taking that experience into another market.

The technology travelled perfectly.

The adoption environment didn’t.

In Iceland, conversations about AI tend to start relatively far along the curve. Management teams know AI matters. Employees are already using it. There is competitive pressure to understand what it can do. The conversation can move fairly quickly toward applications, implementation and value.

When we started talking to two of the largest organizations in the Dutch Caribbean, the conversations began somewhere else.

Both were interested in AI. Some employees were already experimenting with it. But organizationally, they were much earlier in the journey.

There was no clear AI roadmap. No organization-wide strategy. The question wasn’t yet simply, “Which platform should we use?”

It was closer to, “What should AI mean for our organization?”

That changes the sale completely.

Same product. Different starting points.

The numbers suggest that what we experienced wasn’t entirely accidental.

In 2025, 42 percent of Danish enterprises reported using AI technologies, as did 37.8 percent in Finland and 35 percent in Sweden. The EU average was 20 percent. European Commission

Iceland shows a similar pattern. Statistics Iceland reported in March 2026 that 48 percent of companies used some form of AI software and 50 percent used specified AI technologies. Statistics Iceland

Across the Caribbean, the picture is very different. Caribbean Development Dynamics 2026, published by the OECD and Inter-American Development Bank, reports that only 12 percent of businesses in the region use AI, while more than 90 percent spend nothing or very little on it. OECD/IDB

Those figures aren’t perfectly comparable. The surveys use different definitions and populations, so it would be misleading to turn them into a tidy Nordic-versus-Caribbean league table.

But directionally, the gap is difficult to ignore.

And even Iceland contains an important warning against simplistic conclusions.

While roughly half of Icelandic companies report using AI, only 25 percent can identify specific business tasks where they use it, and just 14 percent have developed an AI strategy. Statistics Iceland

So even within a relatively advanced adoption market, there is a significant distance between using AI and organizing around AI.

That distinction matters enormously when you cross a border.

We export products. We assume readiness.

International expansion is usually analysed through market size, competition, pricing, localization and distribution.

All sensible questions.

But there is another one I think we underestimate:

What must already be true inside the customer for this technology to be adopted successfully?

Does management understand the technology?

Is someone responsible for it?

Is there a strategy?

Is there budget?

Are employees encouraged to experiment?

Does procurement know how to buy it?

Are the necessary data and systems available?

Does the organization feel competitive pressure to act?

And perhaps the most important question of all:

Is the customer choosing a solution, or are they still trying to understand the problem?

Those are radically different buying situations.

Research supports the idea that management itself is part of the adoption infrastructure. A 2026 NBER study comparing AI use across the US and Europe found significant differences between countries and firms, with adoption closely associated with personnel-management practices and whether companies actively encouraged employees to use AI. National Bureau of Economic Research

The technology can be identical.

The organization receiving it isn’t.

A market can want your product and still not be ready for it

This creates an interesting problem for international growth.

A market can have the money.

The underlying business problem can exist.

Executives can be interested.

Your product can technically solve the problem.

And the organization can still be unready to adopt it.

That doesn’t necessarily make it a bad market.

It means the commercialization model needs to change.

In a relatively mature environment, an enterprise AI company might enter the conversation here:

“We know AI matters. Show us what your platform can do.”

The vendor is selling execution.

In an earlier-stage market, the conversation may begin several steps upstream:

“We know AI is important. Where should we start?”

Now the customer may first need help understanding opportunities, assessing readiness, identifying use cases, establishing governance and choosing an initial workflow.

Only then does the platform become the obvious next step.

The product hasn’t changed.

What surrounds the product has.

This is why I think international technology companies need to think beyond localization.

Translating a website is localization.

Changing prices is localization.

Hiring a local salesperson is localization.

But when customers are standing at different points on the adoption curve, you may need to localize commercialization itself.

Product fit isn’t enough

I increasingly think about international technology expansion through four layers:

Product fit → Market fit → Adoption readiness → Adoption fit

Product fit asks whether the technology solves the problem.

Market fit asks whether enough customers in the market have that problem and are economically attractive.

Adoption readiness asks whether those customers have the organizational conditions required to implement the technology.

And adoption fit asks whether your sales, implementation and support model matches where those customers actually are.

The first two receive most of the attention.

The last two can quietly decide whether international expansion works.

The implication is slightly uncomfortable.

A go-to-market motion that worked brilliantly in your home country may fail abroad even when the product is good and the market opportunity is real.

The instinct will be to blame sales execution, positioning or the market.

Sometimes the real problem is simpler.

You arrived with an answer to a question the customer isn’t ready to ask yet.

Technology scales globally. Adoption happens locally.

Aruba offers a useful wider backdrop. In July 2026, the government began developing a national strategic plan for AI covering areas including governance, regulation, infrastructure and capacity building. Government of Aruba

That is not evidence that individual Aruban companies are behind. But it does show an ecosystem still building some of the institutional scaffolding around widespread AI adoption.

And that matters.

Because technologies don’t enter markets in isolation.

They enter management cultures, regulatory systems, procurement processes, existing infrastructure, competitive environments and networks of trust.

International growth therefore isn’t simply about transporting a successful product into another geography.

It is about understanding which conditions helped that product succeed in the first place, then asking whether those conditions exist in the new market.

If they don’t, you have a choice.

Wait for the market to catch up.

Or help create the conditions for adoption.

The second option is harder.

It may also be where the opportunity is.

The product is global.

Adoption isn’t.