Oil prices maintained their gains as market participants balanced geopolitical risks against worries of oversupply. Brent crude hovered around $62 per barrel, following a 2.1% increase on Monday. West Texas Intermediate traded above $58.

Venezuela began closing oil wells in a region with the world's largest oil reserves. This action was in response to a partial US blockade that restricted crude exports, leading to full local storage capacity. Separately, President Trump announced a US strike on a facility within the country.

The geopolitical instability in Venezuela, coupled with tensions involving Russia and Iran, created upward pressure on prices. However, concerns about a potential glut in the market acted as a counterweight, preventing further price increases. Traders are employing sophisticated AI-powered algorithms to analyze news feeds, satellite imagery of storage facilities, and shipping data to predict supply and demand fluctuations with greater accuracy. These algorithms use machine learning to identify patterns and correlations that human analysts might miss, providing a more nuanced understanding of the market.

The oil industry is increasingly reliant on AI for optimizing production, refining, and distribution. AI-driven predictive maintenance reduces downtime and improves efficiency in oil extraction. AI is also used to analyze seismic data for more accurate oil exploration. The rise of AI in the oil sector has significant implications for employment, potentially displacing workers in some areas while creating new opportunities in data science and AI development.

Looking ahead, the oil market's trajectory will likely depend on the interplay between geopolitical events and global economic growth. AI-powered forecasting models will play an increasingly important role in helping companies and investors navigate the complex and volatile oil market. The accuracy and reliability of these models will be crucial for making informed decisions and mitigating risks.