Have you tested any AI-enabled cybersecurity solutions that promised significant improvements but failed to deliver measurable outcomes? What were the key lessons you learned from that experience?

We are extremely cautious about adopting AI. We have been using AI for decades, primarily in the form of basic machine learning, especially in the cybersecurity realm. Many of our tools have incorporated machine learning and basic AI for years, so we have not implemented anything that made grand promises but failed to deliver. This is mainly because our first question is always: how is this tool any different? What is this AI? We have declined many proposals from our lines of business because they appear shiny and attractive but do not offer anything different from what we already have. These solutions are not going to help our teams do their jobs better, and there are significant security questions around them. As a financial institution, we cannot allow our data to be used for training on open platforms, so we must be very cautious. What we have put in place has been very successful, largely due to our stringent due diligence process.