AI is the defining word of our time. Conversations about AI permeate every aspect of the energy business from coding assistance, data analysis, and forecasting to interface development, risk management, back-office operations, decision support, natural language processing, and reporting. But what is truly transformative, and where are people simply jumping on the train out of fear of missing out? One of the biggest concerns revolves around AI-driven trading decisions. Since trading decisions can lead to significant losses, accountability for such losses must ultimately rest with humans. I recently had a discussion with Chris Regan, the Managing Director of Brady, about AI-powered algorithmic trading trying to identify the exact role of AI in the process and quantify the gains AI usage brings. Most algorithmic trading solutions focus on automated rule-based intraday trading. They process real-time market information and position data, using rule-based algorithms to make trading decisions. A human trader always retains a kill switch to halt execution. My question was: where does AI fit into this process? Chris explained that Brady’s algorithmic trading solution isn’t a set of fixed, pre-coded algorithms. Instead, it offers a library of Python-coded components, forming an ecosystem that customers can orchestrate into their own trading… continue reading