The rise of generative AI is changing how IT departments operate across industries, and commodity trading is no exception. GenAI copilots can support developers, analysts, and operations teams by automating repetitive tasks, generating code, and surfacing insights faster than traditional tools. For CIOs, the question is not whether to adopt GenAI but how to integrate it effectively into trading IT.

GenAI copilots can accelerate software development by assisting with .NET and Python code, reducing the time required for bug fixes, integrations, and enhancements. They can help data engineers build Databricks pipelines or optimize queries for Snowflake. In risk management, copilots can generate scenario models or automate compliance documentation, ensuring faster responses to regulatory demands.

The transformation potential is significant, but there are challenges. CIOs must ensure copilots are trained on secure, relevant data. They must also integrate copilots into Azure-based environments with governance and monitoring in place. Adoption requires not just technology but change management across IT teams.

Staff augmentation provides a pathway to make this adoption successful. External AI specialists can help configure copilots, connect them to CTRM and ETRM systems, and implement guardrails for compliance and security. By combining internal expertise with augmented teams, CIOs can accelerate GenAI adoption while minimizing risks.

GenAI copilots will not replace IT teams but will augment their capabilities. CIOs who embrace this shift will empower their departments to innovate faster, manage complexity, and focus more on strategic goals.