Small countries have always lived with a quiet disadvantage. Their disadvantages include limited capital, narrow markets, and modest political influence. In the industrial economy, scale decided almost everything. Bigger factories won because of bigger budgets, and bigger countries moved faster simply because they could afford to, translating resources into velocity with exceptional efficiency. Artificial intelligence is changing that equation.
In the last quarter’s edition, I wrote about the compound effect and why the Western Balkans need long-term stability to catch up economically. The argument was simple: 1% daily improvement, compounded over time, creates exponential advantage. That article focused on what we must fix. This one focuses on what we can leverage. AI does not reward size. It rewards speed of implementation, and in that race, small countries finally have a structural advantage.
The paradox we’re living
Across the Western Balkans, the ICT sector employs approximately 150,000 people, around 1.5% of the total workforce, and contributes close to 2% of regional GDP.¹ This is not a marginal sector. Local companies already build software, data systems, and AI-driven tools for Fortune 500 clients. The paradox is not talent. The paradox is application. We are very good at building AI for others. We are far less effective at using it ourselves. That gap between exporting intelligence and applying it locally is the opportunity.
Why implementation is the real race
The cost of AI implementation is now so low that the competitive advantage isn’t in who has the biggest budget. It’s in who moves fastest. Speech-to-text tools cost €50/month. Customer inquiry routing costs €100/month. Inventory forecasting costs €200/month.
The Balkans should compete on implementation, not innovation. Implement where possible, even if small, because compounding produces huge results.
At Bloomteq, we’ve implemented AI across multiple processes: better proposal quality, more accurate work estimates, and improved code testing. We’re not using AI to write code by default or design architecture. We’re using it to improve what humans already do well.
Result: Our proposals are 30% more accurate. Our delivery timelines are more reliable. That’s not super intelligence. That’s automating small tasks to create huge improvements.
Every company and institution can do the same. Courts can use speech-to-text to transcribe proceedings automatically, so the judges spend more time on justice and less time dictating notes. Hospitals can use AI transcription so doctors spend 15 more minutes daily with patients instead of typing reports. Manufacturing plants can use predictive maintenance to catch failures before they happen, reducing downtime by 20%. None of this requires super intelligence. It requires implementation.
The structural advantage of being small
In my work implementing Fortune 500 systems across regional companies, I’ve learned something counterintuitive: small organizations have AI advantages that large ones don’t.
Speed of decision-making: for example, a big automotive company needs 18 months to approve a new AI tool. A 30-person company can pilot it in three weeks.
Focused problem sets: Fortune 500 companies have 10,000 processes to optimise. Balkan SMEs have 20 critical processes. That’s not a disadvantage, it can be used as an advantage.
The compound effect I wrote before works both ways. Consistent improvement creates exponential growth. But consistent advantages in decision speed, multiplied over time, create exponential competitive positioning.
What to do next
This demands iteration, not reinvention. This week, identify one inefficient process that wastes 3+ hours weekly. Find one affordable AI tool (€50–500/month) that solves it. Pilot it for 30 days. Measure results and implement if it works.
Speech-to-text for meeting notes saves 1–2 hours weekly per person. Email classification saves 30–60 minutes daily. Medical transcription gives doctors 15–30 minutes more with patients. The question is not “How do we become an AI company?” The question is “How do we become a better version of the company we already are?”
The bottom line
Small countries have smaller budgets and shorter decision cycles. For decades, this limited growth. Today, it accelerates it. In the AI era, scale matters less than speed. Adoption matters more than invention. Implementation costs less than delay.
The Balkans’ SMEs don’t need to catch up to Silicon Valley. They need to implement existing AI tools faster than bureaucracies can slow them down. Small, consistent improvements create exponential growth. Small, consistent delays create exponential disadvantage. The choice is ours.
¹ OECD, Economic Convergence Scoreboard 2025