Shaping the Deep Tech Revolution in Agriculture 2025

5. Geopolitical instability and friction Geopolitical tensions, trade restrictions, conflicts and shifting global alliances increasingly disrupt agricultural supply chains and input flows. These instabilities lead to volatility in commodity prices, restricted access to critical resources such as fertilizers and uncertainty in global trade corridors. Countries heavily dependent on imports for agricultural inputs or exports for food revenue are particularly vulnerable. To address this challenge, technology use cases should support localized production, supply chain risk assessments and traceability. Global agricultural trade can be complex and opaque, making it difficult for companies to track products from origin to consumption. This lack of transparency poses a significant risk for these companies, preventing them from effectively monitoring risks and addressing critical challenges such as deforestation and labour conditions. A common reliance on supplier-provided data further exacerbates this problem because it often provides an incomplete and unverifiable picture. As a response to these challenges, Trase offers open-access data solutions that help manage agricultural supply chain risks and monitor progress. Taking a pragmatic approach, Trase leverages often underused datasets, combined with cutting-edge data science, including AI-enhanced approaches, to connect vast amounts of publicly available data – such as trade records, shipping documents and satellite imagery – to map supply chains at a large scale. By combining, evaluating and transforming these diverse data streams, Trase connects individual companies with the specific subnational regions in which its commodities, such as soy or palm oil, are produced, and at the scale of entire countries and markets. This provides an independent, open- access assessment that empowers companies, financial institutions, governments and other stakeholders to better understand, manage and mitigate sustainability risks, and to strengthen accountability for sustainability goals.25CASE STUDY 10 Deforestation risk management through AI – Trase Use case 10: Supply chain risk forecasting systems Technology convergence Machine learning and satellite-enabled remote sensing Description Risk-forecasting systems integrate real-time geopolitical, trade, climate and commodity data to anticipate supply disruptions and price shocks. These dashboards can simulate scenarios such as fertilizer embargoes, port blockades or conflict-triggered migration, offering actionable intelligence for strategic planning and contingency management. Shaping the Deep-Tech Revolution in Agriculture 33