According to Chris Olah on X, AI interpretability techniques are now being used in pre-deployment audits to enhance transparency and safety before models are released into production (source: x.com/Jack_W_Lindsey/status/1972732219795153126). This advancement enables organizations to better understand model decision-making, identify potential risks, and ensure regulatory compliance. The application of interpretability in audit processes opens new business opportunities for AI auditing services and risk management solutions, which are increasingly critical as enterprises deploy large-scale AI systems.