AI Governance
AI governance is the set of policies, oversight mechanisms, and accountability structures that ensure AI systems are used responsibly and effectively.
In Simple Terms
Think of AI governance as the guardrails on a highway—they keep you safe without stopping you from moving forward.
Detailed Explanation
AI governance covers ethics, bias, transparency, privacy, security, and compliance. It defines who approves AI use cases, how models are audited, and what happens when things go wrong. When to use: Before deploying AI at scale. Common mistakes: Treating governance as an afterthought or making it so rigid that innovation stalls.
Related Terms
Explainable AI (XAI)
Explainable AI (XAI) is the field of methods and techniques that make AI model decisions interpretable or understandable to humans. It answers why a model gave a certain output so users can trust and debug it.
Read moreOperating System (Business)
In business context, an operating system is the set of processes, workflows, and standards that define how a business runs day to day—not software, but the human and procedural backbone.
Read moreAI Roadmap
An AI roadmap is a phased plan for AI adoption, from pilot projects to enterprise-scale deployment. It prioritizes use cases, timelines, and resource needs.
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