Artificial intelligence becomes useful when it improves a concrete management decision. In customer service, intelligent automation can support faster and more consistent support, but only when teams connect the technology to a clearly owned workflow. Start with the decision, not the model Intelligent Automation combines rules, workflow orchestration, and machine intelligence. That can be valuable in customer service, especially around ticket triage and knowledge retrieval. The first design question should therefore be: which decision becomes faster, more accurate, or more consistent? A use case without an accountable decision owner usually remains a demo. Map the current workflow from trigger to outcome. Mark where information is missing, where people repeat manual work, and where delays create business consequences. This exposes the small number of moments where AI assistance can materially change the result. Define a narrow first use case A useful pilot has one target group, one data boundary, and one…

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