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Generative AI And RPA: A New Age Of Automation

Generative AI has significantly influenced various industries. Its integration with robotic process automation (RPA) has the potential to introduce new levels of adaptability and advanced automation systems, marking the emergence of what we can refer to as the next generation of RPA—RPA 2.0. At its core, RPA is about automating repetitive and mundane tasks across business applications and systems within an organization. Traditionally, RPA relies on predefined rules and sets of workflows consisting of repetitive rule-based instructions that humans execute on machines. For the next generation of RPA to achieve its full potential, I believe it must coexist with generative AI. While RPA excels at the rule-based workflow, its reliance on predefined rules can diminish efficiency. AI can help with the machine learning algorithm as it can be continuously optimized, resulting in more efficient and faster automation with larger accuracy. Not all organizational tasks are rule-based; some require cognitive decision-making, especially when dealing with unstructured data or anomalous tasks. Generative AI can help bridge this gap by creating models that inform decisions based on the data they have been trained on. This relationship ensures that while RPA handles the rule-based and repetitive tasks, generative AI can manage tasks that require a human-in-the-loop. Generative AI techniques such as generative adversarial networks (GANs) and retrieval-augmented generation (RAG) have demonstrated capabilities ranging from generating realistic images to providing contextually relevant information. These advancements are part of why I believe generative AI is the heart of RPA 2.0.

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