AI has been used in financial markets for years, and its role continues to deepen. Algorithmic trading systems use machine learning to identify patterns, predict price movements, and execute trades at speeds no human could match. Investment firms use AI to analyse company filings, news, social media sentiment, satellite imagery, and alternative data sources to inform investment decisions. Quantitative hedge funds that build their strategies around AI and data analysis manage billions in assets. Beyond trading, AI helps with credit scoring, portfolio optimisation, financial planning, and regulatory compliance. The technology is genuinely powerful in this domain because financial markets generate enormous, well-structured datasets and the feedback loops are clear - your model either makes money or it does not. The risks include systemic effects when many firms use similar AI strategies (potentially amplifying market movements), the opacity of AI-driven trading decisions, and the possibility of AI systems exploiting patterns that reflect market microstructure rather than fundamental value. Regulators are increasingly focused on understanding and managing the risks that AI introduces to financial stability.