In the rush to innovate, it's easy to forget: AI doesn't just optimize, it reflects. And what it reflects depends on the values we embed, the questions we ask and the systems we build. The Ethical Reckoning of AI As organizations integrate AI deeper into decision-making, the stakes get higher. Biases in training data can lead to real-world discrimination. Black-box systems can obscure accountability. Speed can come at the cost of scrutiny. Regulators, stakeholders and customers are paying attention. Ethics is no longer a sidebar; it’s a core performance issue. The Illusion of Neutrality Many still believe AI is neutral because it’s mathematical. But algorithms inherit the biases of their creators, the limitations of their data and the assumptions of their design. Performance must now include ethical impact: not just what AI does but how it does it and to whom. Embedding Ethics into Performance Thinking Organizational performance frameworks, like IMPACT, are ...