Let’s take a look at five practical applications of AI that fall within these three categories and how they can improve enterprise automation outcomes.
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The holy grail of self-healing processes isn’t far away with the addition of emerging augmented intelligence models. This technology has the potential to detect bottlenecks in processes, provide suggestions for enhancement and either automatically update models or update them following human validation of the decision.One compelling use of generative AI involves the generation of testing data for processes.
Companies with advanced AI capabilities can harness machine learning-ready datasets from a process orchestration system, seamlessly integrating them with internal datasets to anticipate patterns and extract valuable insights for informed decision-making.Generative AI can play an important role in streamlining certain human tasks. Take, for example, a community market that wants to process applications for new vendors.
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