AI Governance
AI governance is the set of policies, frameworks, and organizational structures that ensure AI systems are developed, deployed, and monitored in compliance with ethical, legal, and business standards.
In Depth
As AI becomes central to customer support operations, governance becomes essential for managing risk and maintaining quality. AI governance establishes who can deploy AI models, what approval processes are required, how performance is monitored, and what happens when things go wrong. It includes model risk management (assessing and mitigating risks before deployment), ongoing monitoring (tracking accuracy, bias, and safety metrics in production), change management (controlling model updates and versioning), and compliance documentation (maintaining audit trails for regulators).
For support teams, AI governance ensures that AI agents consistently meet quality standards, that customer data is handled properly, and that there are clear escalation paths when AI behavior deviates from expectations.
Related Terms
Responsible AI
Responsible AI is the practice of developing and deploying AI systems with accountability, transparency, fairness, and ethical considerations at every stage of the lifecycle.
AI Safety
AI safety is the field dedicated to ensuring that AI systems behave as intended, avoid causing harm, and remain aligned with human values and organizational goals.
AI Ethics
AI ethics is the study and application of moral principles to the design, development, and deployment of AI systems to ensure they benefit society and minimize harm.
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