Example Concept: Organizations should implement a bias mitigation strategy that includes regular audits of AI systems using fairness dashboards, applying bias detection algorithms, and integrating stakeholder feedback. This approach helps identify potential biases in data and models, allowing for corrective actions such as data rebalancing, algorithmic adjustments, and transparent reporting of AI decisions.