Example Concept: Organizations should establish a bias mitigation framework that includes regular bias audits, the use of fairness metrics (such as demographic parity or equalized odds), and the deployment of bias detection tools. This framework should be integrated into the AI development process, ensuring that biases are identified early and addressed before deployment. Additionally, organizations should provide training for teams on recognizing and mitigating biases and maintain transparent documentation of their efforts.