AI can compare markets faster than most teams could have imagined a few years ago. It can size opportunities, identify competitors, summarise regulations and surface potential customers or partners in minutes.
The harder question is whether it can tell you where your business should expand.
Imagine you are comparing two international markets. The first is larger, growing faster and has more potential customers. The second is smaller, but your product is easier to sell there, distribution costs are lower and customers tend to pay faster.
Which market is more attractive?
That depends on your business.
A company with limited working capital may favour shorter payment cycles and modest upfront investment. A business with an established distributor network may be comfortable entering markets that would be expensive for a company relying on direct sales. Regulatory approvals, channel margins, landed costs, pricing power and the resources required to support customers can all change the economics of an opportunity.
This is where international market selection becomes more than a research exercise.
AI has changed the research process
The speed of AI-assisted research is genuinely useful.
A team exploring international opportunities can now investigate more markets, test assumptions quickly and build an initial picture of competitors, customers and market conditions without spending weeks assembling information manually.
Research into professional services has demonstrated how significant those productivity gains can be. In a study involving 758 Boston Consulting Group consultants, participants using GPT-4 completed tasks within the technology’s capability frontier more than 25% faster and produced work that scored more than 40% higher in quality.
The same study also identified an important limitation. When participants tackled a task outside the model’s capability frontier, those using AI were 19 percentage points less likely to reach the correct answer.
The research used an earlier generation of AI, so the figures should not be treated as a benchmark for today’s models. The commercial point remains useful: AI can improve the speed and quality of analysis considerably when it is being used for the right task and the people using it understand what they are asking it to do.
International market selection is particularly sensitive to that distinction because the answer depends heavily on the company asking the question.
Ask AI to identify the best export markets for a product and it can produce a convincing ranking. But the ranking can only reflect the criteria it has been given.
For one company, the priority may be rapid revenue growth. Another may need to minimise upfront investment. A third may want to diversify away from an existing region or find a market where it can build recurring revenue with a small local team.
Those objectives can lead to very different market choices.
A big market is not always a good market
Suppose a manufacturer is comparing two opportunities.
Market A has twice the customer base and stronger category growth. Market B is smaller, but there are established distributors serving the sector, freight costs are lower and payment terms are considerably better.
An analysis weighted heavily toward market size may put Market A at the top of the list.
Once distributor margins, cost to serve, working capital, customer acquisition costs and the company’s ability to execute are taken into account, Market B may look much more attractive.
The underlying market data has not changed. The commercial criteria have.
This is why D&A does not assess international markets on size alone. Our Methodology & Ranking Framework compares opportunities across six dimensions: market size, market momentum, country risk, market foundations, market access, and cultural and geographic distance.
Looking across those dimensions helps expose the trade-offs that headline growth figures can hide.
A very large market may require expensive regulatory approvals, have entrenched competitors or demand a route to market that does not suit the company. A smaller market may offer faster access to customers, stronger channel economics or a lower-risk path to establishing an international presence.
For the company making the investment, those factors may matter far more than the size of the opportunity on paper.
Accurate information can still lead you in the wrong direction
AI-generated research also needs to be tested carefully.
The US National Institute of Standards and Technology identifies “confabulation” as a generative AI risk: systems can produce incorrect or false information with considerable confidence. Its guidance recommends verifying sources and citations and involving relevant subject-matter experts when evaluating outputs.
International expansion creates another problem. Information can be accurate and still be commercially unhelpful.
An industry report may cover the national market when the relevant opportunity sits within one state or province. A growth forecast may relate to the broader category rather than the segment a company actually serves. Pricing data may describe retail prices when the company sells wholesale. A regulation may technically apply to the product but have implications that only become obvious when speaking to local distributors, customers or advisers.
The source may be reliable. The context may still be wrong.
Good market analysis therefore involves tracing important claims to their sources, understanding how the data was produced and testing whether the assumptions behind the analysis apply to the specific business.
It also requires talking to the market.
Conversations with customers, distributors, partners and other industry participants can reveal things that published datasets often miss: how purchasing decisions are actually made, whether customers will pay the expected price, which channels have influence, how long sales cycles take and what local competitors do particularly well.
Those insights can materially change the way an opportunity looks.
Where human judgement adds value
Experienced international strategists bring commercial context to the analysis.
They know which assumptions deserve pressure-testing, which numbers need a second source and which apparent advantages may disappear once the company starts selling, shipping and collecting payment.
They also challenge the assumptions of the business itself.
A management team may be attracted to a market because it is familiar, growing quickly or regularly appears in customer enquiries. That does not automatically make it the right place to invest.
A robust market-selection process compares the opportunity with the company’s objectives, resources and ability to execute. It looks at how much capital the business can commit, how quickly it needs a return, which routes to market are realistic and where the company has a genuine basis for competing.
AI can make that process much faster. It can help advisers and internal teams explore more possibilities, analyse larger volumes of information and investigate questions that would once have taken much longer to answer.
The quality of the decision still depends on the quality of the questions and how the answers are interpreted.
At Dearin & Associates, we use AI-enabled research alongside our market-selection methodology and decades of international business experience. This allows us to move quickly through the research while keeping the analysis focused on the questions that matter commercially: where the company can compete, what it will take to enter, how much capital will be required and whether the expected return justifies the investment.
AI has made international market research dramatically faster. Choosing where to expand still requires a clear view of what success looks like for the business and a disciplined assessment of which markets can realistically deliver it.
If you are comparing markets for your next phase of international growth, Dearin & Associates can help you test the assumptions behind the analysis and identify which opportunities make commercial sense for your business.
