AI model drift detection and management

Executive Summary Many organisations treat AI governance as a “before go-live” exercise—register the use case, sign off the risks, test performance, and launch. That approach is no longer sufficient. AI systems change after go-live—even if you never touch the model: customer behaviour shifts (economic cycles, seasonality, inflation), fraud tactics evolve, data sources change (new systems,...