How forecasting the future of AI saw BCom student Kento Hikima become a winner of the 2026 Bridgewater and Global Citizen ‘Forecasting the Future’ Challenge.
A few months ago, I entered Bridgewater Associates and Global Citizen’s Forecasting the Future competition, a global economics challenge asking participants to develop a set of forecasts about how the intersection of AI and modern mercantilism could shape the world over the coming years.
After hundreds of hours of preparation and research, I was ultimately selected as one of five global winners from more than 1,300 submissions across over 150 countries.
I initially entered the competition for two reasons. First, I wanted to explore my curiosity about economics and finance through the unique lens through which Bridgewater analyses the world, a curiosity I had developed through my experiences at university and across internships. Second, I was eager to test my abilities against some of the strongest talent in the field globally, particularly because the competition was not limited to students.
My submission focused on the interaction between artificial intelligence and what I described as a new form of modern mercantilism – the growing role of the state in prioritising national security, strategic industries and economic resilience over pure market efficiency. The central idea was that AI is becoming more than a productivity tool. Rather, it is increasingly a strategic asset, encouraging governments and companies to secure access to computing power, energy, semiconductors, infrastructure and supply chains.
From there, I developed a series of forecasts around how this could affect capital expenditure, productivity, trade, cross-border investment and government policy. The challenge was not simply to predict what might happen, but to make each forecast measurable, assign a probability to it and explain the assumptions that would make it more or less likely.
One of the highlights was the finalist roundtable, where we discussed and challenged each other’s ideas. That experience changed the way I think about research, as I learnt that a strong thesis is not just about having an interesting conclusion, but also acutely dependent on whether the assumptions underneath it are sound, whether the causal chain holds together, and whether you are willing to update your view when new evidence emerges.
It also reinforced the value of disagreement. The most useful conversations were not necessarily those where people agreed, but those where someone identified an assumption you had not questioned yourself enough, or introduced new information that could change your forecast.
The opportunity to compete and win was a surreal experience; however, what I value most are the lessons that came out of it. I was pushed to understand the world through facets and perspectives that were often foreign to me. Ironically, in a world where AI can easily shortcut comprehension, trying to forecast its future deepened my own understanding of markets and changed the way I approach problems.
For students considering opportunities like this, my main advice would be to apply even if you do not think you fit the conventional profile. Global opportunities can sometimes feel distant when studying in Melbourne, particularly when you are competing at 2am, but this experience showed me that geography matters far less than the quality of your ideas and the work you are willing to put behind them.
The biggest lesson I took away is simple: the best ideas should win, no matter who has them or where they come from. The important part is being willing to test them rigorously, expose them to disagreement and keep improving them.