Operationalizing AI and automation with digital workers
5Automation has been offered as relief to key operational challenges from the Great Resignation to offering a stronger Customer Experience (CX). Basically solving: “too much work, not enough workers.” But slowing automation success has often been the variety of data part of these operational processes, the documents, and other unstructured data that are too complex to solve with a rules-based approach. Machine Learning has brought promise, but ML success is much more than training a model. It must be operationalized end-to-end, solving business problems now and ongoing into the future. AI-enabled digital workers allow technology to be “hired” for complete job functions – expanding operational capacity for areas such as AML and KYC in banking, leveraging techniques like human-in-the-loop, continuous learning, and federated learning to maintain and improve performance over time.
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