JPMorgan Forecasts Silver Shortage Driven by AI and EV Demand

The global silver market has been in a structural deficit since 2021, with demand consistently outpacing supply. This imbalance is projected to create a cumulative deficit of 796 million ounces between 2021 and 2025. The deficit is driven by surging industrial demand, which now accounts for over half of all silver consumption, a stark contrast to gold where investment and jewelry dominate. JPMorgan forecasts an average silver price of $81 per ounce in 2026, more than double its 2025 average. Other institutions have also issued bullish forecasts, with Bank of America projecting a potential range of $135 to $309 per ounce by the end of 2026, depending on whether a physical squeeze occurs. This price action is underpinned by tight supply, as over 70% of silver is produced as a byproduct of mining other metals, limiting the industry's ability to quickly ramp up production in response to price increases. The 1979-80 silver market comparison refers to the Hunt brothers' attempt to corner the market, which drove prices from $6 to nearly $50 per ounce in just over a year. The brothers acquired massive physical holdings and futures contracts, at one point controlling up to two-thirds of the global supply. The rally ended when regulators intervened with "Silver Rule 7," which restricted leveraged purchases and led to a 50% price collapse on a single day known as "Silver Thursday." Junior silver miners are exploration-focused companies that are more sensitive to silver price changes than major producers. Their smaller capital bases and focus on new discoveries offer higher potential returns but also come with greater risk, including financing challenges and operational hurdles. Successful exploration by a junior miner can lead to exponential growth, making them attractive acquisition targets for larger producers seeking to replenish their reserves. From a platform perspective, the mining industry is undergoing a significant transformation through AI and machine learning. AI is being deployed for predictive maintenance on equipment, optimizing extraction through geological data analysis, and enhancing worker safety with real-time hazard detection. This shift toward data-driven operations creates opportunities for platform teams to build systems that manage autonomous vehicle fleets, process vast sensor data streams for ore-grade prediction, and provide supply chain traceability to meet ESG requirements.