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· 51 min
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Everyone assumes AI in customer operations means fewer people and lower costs. The data from 700 customer operations leaders is more complicated, and more honest. Dan O'Connell, CEO of Front, joins Craig Smith with findings from a survey of customer support, service, and account management leaders that reveal what's actually happening as enterprises deploy AI at scale, and the central finding is a problem nobody has named yet. For every hour of actual customer resolution, organizations spend roughly three hours on internal coordination: the handoffs, context transfers, escalation management, and back-channel communication that happens invisibly between customer interactions. More than 40% of companies don't measure this at all. AI is making it worse before it makes it better, because more agentic automation generates more coordination events, not fewer, and the companies reporting the highest AI technology satisfaction in the survey are also reporting higher coordination burdens. The survey also pushes back on a dominant narrative: that AI in customer operations is primarily about cutting headcount. O'Connell's respondents are overwhelmingly focused on improving net revenue retention and customer expansion. The conversation closes with O'Connell's most forward-looking observation: the coordination tax is a temporary problem that AI should eventually solve, but measuring it is the prerequisite that most enterprises are still skipping. Subscribe to Eye on A.I. for weekly conversations with the people building and deploying the future of AI.
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