As AI adoption accelerates across contact centers, organizations are entering a new phase – one where AI no longer simply supports agents, but actively evaluates performance, shapes behavior, and informs operational decisions.
Unfortunately, this shift is happening faster than many traditional governance models can keep up with. AI initiatives often inherit flawed performance definitions, legacy metrics, and biased data, which can lead to confident but incorrect conclusions that undermine quality, trust, and customer experience.
So as AI systems increasingly evaluate agent performance, drive coaching decisions, and influence customer outcomes, how do organizations ensure the right governance, accountability, and validation of what is being measured?
Join us to explore why measurement validity matters, how psychometrics and human expertise safeguard decision-making, and what it means to move from AI-enabled operations to AI-governed enterprises.
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