
Geopolitical turbulence puts Brazil in focus – but sustained growth needs a strategy
Latin America’s largest economy by GDP needs a multi-pronged approach addressing fragile governance, deep inequality, and uneven institutions. ...

by Simon J. Evenett, Johannes Fritz Published March 18, 2026 in Geopolitics • 10 min read
When a board receives a geopolitical briefing from a former ambassador or a retired intelligence official, it is receiving something valuable: deep knowledge, pattern recognition, and institutional memory built over decades. It is also receiving something less visible: the cognitive biases that accompany all human judgment. Recency bias – overweighting the latest dramatic event; confirmation bias – seeking evidence that supports an existing view; anchoring – locking onto a single historical analogy and filtering everything through it. These are not character flaws. They are well-documented features of how human minds process complex, uncertain information.
In a slow-moving policy environment, their effects are manageable. In a fast-moving, multi-front conflict with commercial consequences reaching across continents, they can lead to misjudgments on exposure, timing, and risk.
One way to mitigate such limitations is to complement expert judgment with structured analytical tools. Recent advances in artificial intelligence make it possible to monitor geopolitical crises through multiple competing analytical frameworks simultaneously. Scenario-monitoring systems can continuously assess open-source evidence, test alternative interpretations, and update probability estimates as events unfold. By forcing analysts to make their assumptions explicit and subject to challenge, such tools introduce a degree of rigor and transparency that traditional briefings alone rarely provide.

The Gulf conflict shows why this kind of analytical discipline is essential. Two weeks into the US-Iran war, the crisis spans military operations across Iran, Lebanon, Iraq, and the wider Gulf; energy markets are in turmoil; and shipping insurance markets have effectively closed the Strait of Hormuz to commercial traffic. Kuwait has declared force majeure on oil exports. Bahrain’s only refinery has been destroyed. Petroleum-dependent supply chains face input shortages that will ripple through agriculture and manufacturing. Brent crude is above $100. Economist Mohamed El-Erian warned recently in the Financial Times that the cumulative effect is a fresh bout of stagflation. Meanwhile, central banks with limited policy flexibility may delay rate cuts or tighten further.
In short, no single expert, however distinguished, can maintain continuous, structured assessment across these domains simultaneously.Furthermore, relying on a single authoritative view creates a different risk: analytical convergence around one narrative. In intelligence studies, some of the most consequential failures have come not from lack of information but from too quickly settling on a dominant interpretation. The challenge is therefore not whether their geopolitical advisor is good. It is whether their overall assessment process systematically exposes assumptions to challenge and incorporates competing interpretations as events evolve.
The Iran Conflict Scenario Monitor was developed by our technology team at the St. Gallen Endowment, a Strategic Partner of IMD.
This is precisely the kind of analytical challenge that structured scenario monitoring is designed to address. The Iran Conflict Scenario Monitor was developed by our technology team at the St. Gallen Endowment, a Strategic Partner of IMD. The tool tracks eight competing scenarios for the Gulf conflict using fourteen independent AI-driven analytical agents, each applying a distinct academic framework. The agents assess the same open-source evidence in complete isolation. Every probability adjustment must name the specific causal mechanism driving it. A dedicated adversarial agent challenges the consensus every cycle. The monitor updates three times daily, runs on Anthropic’s Claude, and is freely accessible at lab.globaltradealert.org.
A strategy team can stress-test planning assumptions against the timeline predictions.
Consider what the monitor reveals right now and how it differs from what a single briefing might convey. Fifteen days in, it assigns a 42% probability to regional war as the dominant trajectory four weeks from now. That number has climbed steadily since Day 5, driven by an accumulation of structural shifts: Iran striking energy infrastructure across six Gulf states, Hezbollah opening a second front from Lebanon provoking an Israeli response, Iranian missiles intercepted over Turkish airspace, and the US bombing of Kharg Island. Scenarios implying containment or resolution have collapsed to near zero.
The timeline predictions are concrete: 1% consensus probability of an unescorted Hormuz transit within two weeks, 3% within four weeks; and a 9% chance of US military strikes ceasing within a month. Like humans, AI analysts can differ.  A human advisor might reasonably disagree with any of these numbers. But that disagreement, tested against fourteen independently reasoned frameworks with their mechanisms exposed, produces a more rigorous basis for decisions than agreement with a single expert’s intuition.
This is the core argument for complementarity, not substitution.The monitor enforces independence between its analysts. It mandates adversarial challenge at every cycle. It requires named causal mechanisms for every judgment, making the reasoning auditable. An experienced Middle East advisor can look at the monitor’s scenario probabilities and ask: where do I disagree, and why? A strategy team can stress-test planning assumptions against the timeline predictions. An operations leader can use the Hormuz transit estimates to trigger contingency plans for alternative routing or sourcing. A CFO can map the interest rate implications of a conflict that the monitor’s agents assess has a two-in-three chance of persisting beyond two months. The structured AI provides the disciplined baseline; the human expert provides the contextual judgment no model can replicate.
Our monitor puts that rigorous geopolitical assessment within reach of mid-sized firms, institutional investors, and organizations building this capability for the first time.
Effective open-source intelligence—structured monitoring with named frameworks, continuous updating, and transparent reasoning—was until recently available only to governments and the very largest multinationals. AI tools have democratized it. Our monitor puts that rigorous geopolitical assessment within reach of mid-sized firms, institutional investors, and organizations building this capability for the first time. The practical question for senior leaders is straightforward: audit your current geopolitical monitoring for domain coverage, bias mitigation, and update frequency. If it does not cover military, energy, diplomatic, and financial dimensions simultaneously, it doesn’t match the scale of the risks your company faces. If it relies on a single perspective without structured challenge, it is vulnerable to exactly the biases that produce the costliest misjudgments.
As upheaval becomes a recurring feature of the global economy, the question for leadership is no longer whether such capabilities are needed but how quickly they can be built into the firm’s decision-making architecture—the analytical architecture described here offers one blueprint for doing so.

Professor of Geopolitics and Strategy at IMD
Simon J. Evenett is Professor of Geopolitics and Strategy at IMD and a leading expert on trade, investment, and global business dynamics. With nearly 30 years of experience, he has advised executives and guided students in navigating significant shifts in the global economy. In 2023, he was appointed Co-Chair of the World Economic Forum’s Global Future Council on Trade and Investment.
Evenett founded the St Gallen Endowment for Prosperity Through Trade, which oversees key initiatives like the Global Trade Alert and Digital Policy Alert. His research focuses on trade policy, geopolitical rivalry, and industrial policy, with over 250 publications. He has held academic positions at the University of St. Gallen, Oxford University, and Johns Hopkins University.

Senior Fellow for Tech Policy & Business, IMD
Johannes Fritz is the Senior Fellow for Tech Policy & Business at IMD and the CEO of the St. Gallen Endowment, a Swiss non-profit that champions international openness, collaboration and exchange. He leads the Digital Policy Alert transparency initiative focusing on prominent digital trade issues such as data transfers and AI regulation. He is also a lecturer in economic history and economic thought at the University of Fribourg, Switzerland. Johannes holds a Ph.D. in economics, and his work focuses on utilizing technology to bring transparency to public policy choice.

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