Artificial Intelligence for Efficiency Sustainability and Inclusivity in TradeTech 2025

Smart sourcing AI’s ability to analyse complex, multidimensional data in real time can revolutionize the sourcing and movement of critical raw materials. In the past 20 years, trade in energy-related minerals has risen from $53 billion to $378 billion – a compound annual growth rate of 10%, which is likely to increase as the world’s reliance on advanced technologies grows.15 But the historic volatility of metal prices poses challenges for consumers who need stable prices and reliable supply chains. AI can help offset the volatility of these markets through: –Rapid and incisive analysis: Price data, global economic statistics and market sentiment are all factors that affect supply chains. AI and especially ML tools can identify patterns that enable leaders to make more accurate predictions about future pricing. –Real-time insights: AI tools can continuously monitor news and social media to assess how various events may impact metal prices. This provides real-time insights that enable faster decision-making. –Enhanced risk management: AI can easily identify unusual trading patterns or price movements, allowing for quicker detection of market inefficiencies and new trading opportunities. Pattern recognition can flag errors and reduce risks by identifying trades that do not fit expected behaviour. –Faster trade execution: AI-driven systems can automate the process of capturing and entering trades into trading platforms, reducing manual input errors. The assets of AI can augment human intelligence and create a smarter, better-informed workforce with greater visibility over global markets. By reducing risk and costs, such tools allow access to a greater supply of critical raw materials at better prices for end consumers. Current and future applications of AI across supply chains FIGURE 5 Current applications: Supply chain mapping/uni00A0 Party authentication through digital ID Internet of things (IoT) sensor networks/uni00A0 Flagging suspicious transactions and illicit trade Counterfeit detection Fake review detection Future applications: Full traceability through transparent supply chainsCurrent applications: Facility-level Scope 3 emissions measurement Predictive maintenance/uni00A0 Demand prediction Computer vision for automated recycling Future applications: Global Scope 3 emissions tracking Maintenance automation Zero waste in manufacturing Perfect demand prediction, eliminating surplus inventory De-centralized autonomous manufacturing and delivery units (AMDU)Current applications: Demand prediction Market history analysis Fraud alerts Translation and localization/uni00A0 Dynamic pricing Future applications: De-centralized trade networks and peer-to-peer transactions/uni00A0 AI-managed decentralized autonomous organizations (DAOs) AI agents trading automatically through digital IDs/uni00A0 Flexible factories and synthetic digital assets Ethical sourcing through transparent supply chains Perfect localizationTraceability, fraud and information verification Circular economy Sourcing and purchasing The assets of AI can augment human intelligence and create a smarter, better- informed workforce with greater visibility over global markets. Artificial Intelligence for Efficiency, Sustainability and Inclusivity in TradeTech 15