Introducing GAMES
The world talks about artificial intelligence as if it were one economy. GAMES was built for the harder question: how does AI change growth, jobs, inflation, debt, and public finances country by country?
- Most AI growth commentary is too aggregate and too US-centered for country-level economic decisions.
- GAMES lets users test how AI adoption and policy choices could affect output, jobs, inflation, debt, and fiscal pressure across economies.
- The goal is not false precision; it is transparent assumptions, comparison, and better questions.
The world is not one economy
The world is talking about artificial intelligence as if it were one economy. It is not.
The usual story is simple. AI will make workers more productive. Productivity will lift output. Growth will accelerate. The countries that adopt fastest will win. That may be true in some places. It will not be true everywhere in the same way.
An economy is not just a technology stack. It is a labour market, a tax system, a welfare state, a debt profile, a set of institutions, a currency, a trading position, and a political settlement. When a new technology arrives, it does not land on a blank spreadsheet. It lands on all of that.
Why we built it
Most public discussion of AI economics is too narrow. Some of it comes from technology companies, which naturally emphasise productivity. Some comes from investors, who look first at the firms most likely to profit. Much of it comes from the United States, where the companies, capital markets, and policy debate dominate the global conversation.
Gartner forecasts worldwide AI spending will reach $2.52 trillion in 2026, including $401 billion for AI infrastructure.[^1] Yet the public debate still has far more investment forecasts than country-level macroeconomic stress tests.
But the rest of the world will not experience AI as an American press release. Countries differ sharply in the kinds of work their citizens do, the debt they carry, the taxes they can collect, and the institutions they can rely on when disruption arrives.
GAMES was built to ask a different question: which countries can convert AI into broad prosperity, and which countries face a harder transition?
What GAMES does
GAMES lets users test macroeconomic scenarios across countries. At its simplest, a user can choose a country, adjust assumptions about AI adoption and policy response, and examine how the economy changes over time.
The simulator tracks variables such as output, unemployment, inflation, public debt, and fiscal pressure. It is designed to make trade-offs visible rather than hide them behind a single headline number.
GAMES uses transparent scenario modelling and uncertainty-aware simulation to produce these outputs, with explicit ranges of plausible outcomes rather than false-precision single figures.
A country may show stronger output but also higher unemployment during the transition. Another may appear resilient on growth but fragile on debt. A third may benefit only if policy arrives early enough. The value of a simulator is that those tensions can be seen together.
What makes it different
GAMES is built around three principles. Assumptions should be explicit. Countries should be treated as countries. Claims should be traceable.
That does not make the model perfect. No macroeconomic model is. But it does make the work inspectable. A result should carry its assumptions, data vintage, country set, and scenario logic instead of floating as a confident slogan.
The point is not to replace judgement. The point is to improve the quality of the argument.
Explore GAMES now
GAMES is live at econpredict.com. Access country-level AI macroeconomic scenarios immediately, with transparent assumptions and comparative outputs across advanced and emerging economies.
Explore the simulatorWhat comes next
This first article is an introduction, not a results dump. The research that follows will look at the uneven geography of AI: which countries appear resilient, which look exposed, where output and employment move in different directions, where debt constrains policy, and where a slower transition may be safer than a faster one.
Our first research release will break down the drivers of AI transition resilience across benchmarked economies, including the gap between the most and least prepared quartile.
Some findings will be intuitive. Others will not. That is the point of doing the work country by country rather than assuming the answer in advance.
AI may become one of the most important economic forces of the next decade. But it will not arrive in every country with the same benefits, costs, or timing. The economy does not guess. Neither should we.
[^1]: Gartner, "Gartner Says Worldwide AI Spending Will Total $2.5 Trillion in 2026," January 15, 2026. https://www.gartner.com/en/newsroom/press-releases/2025-01-15-gartner-says-worldwide-ai-spending-will-total-2-point-5-trillion-dollars-in-2026