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Enable End-to-end Automation With RPA , Process Mining and AI
“DATA MANAGEMENT AND QUALITY ARE ABSOLUTELY CRITICAL IN THE INTEGRATION OF AI WITH RPA ”
TIM PETERS CHIEF MARKETING OFFICER , ENGHOUSE SYSTEMS their outdated infrastructure to support these advanced technologies , or deem the task of digital transformation too large to tackle .
Although the task is big , Peter explains how it is not insurmountable , saying : “ Organisations should start by investing in robust data management practices . This includes data cleansing , normalisation and governance , to ensure that the AI models have access to high -quality , consistent data .”
Additionally , adopting a phased approach to integration , starting with pilot projects that target specific processes before scaling up can give companies clear goals , minimise
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