| |June, 20229links in a complex automation envi-ronment having workflows and other automation elements.· AI/ML: Algorithmic layers allow to build continuous learning models that learn through the ongoing automation steps and the human in the loop exception management and improve over time. A combination of AI/ML and RPA can build end to end digital automation solutions by themselves. · Cloud: It can be used as staging for storing the intermediate files created by OCR and IDP and also as data repository, as an automation platform, or for hosting business systems that are in the loop of the end-to-end automation. It offers high scalability to improved compute time to the entire automation effort.· Analytics: It offers 360 degree analytics of the data generated and provides intelligent and actionable insights about operations at the click of a button. Do It Yourself (DIY) features and visual analytics allow you to drill down into the data at will, anytime anywhere. Important use cases leveraging Intelligent Automation & RPA combinationIt is interesting to note that a vast dif-ference exists between point solution automation in smaller enterprise pock-ets and automation programs execut-ed through an Intelligent Automation Centre of Excellence (CoE). A CoE led automation allows to reap benefits of scale and generate maximum through-put. It can be implemented seamlessly in a paper-driven ecosystem or a semi to a highly automated business entity.Some of the important Intelligent Automation and RPA use cases include end to end automation of accounts payables, health claim document processing, operations in banking & treasury, and know your customer procedures. Following are some of the important use cases in different industry domains that serve as a springboard to jump start the Intelligent Automation journey ­· Banking· Financial Services· Manufacturing· Logistics· Insurance· Healthcare· Telecom· Government & Public Services· Retail & E-Commerce· Real Estate· Travel & Hospitality· Education· Media & Entertainment Advantages of Intelligent Automation· Interoperable: Functions with all product platforms and technologies to deliver flexible yet robust automation solutions.· Modular: Allows you to select the component as per business requirement and in any desired sequence.· Continuous Learning: Offers continuous machine learning through AI/ML algorithms and improved performance through each exception handling. · Multi-structured Data: Processes a wide spectrum of data from unstructured to structured to multi-structured, which is eventually integrated in the core systems. · Universal Recorder: Offers process automation that extends across multiple systems, from mainframes to Citrix to ERPs to Cloud.· Reusability: Generates reusable components through each automation exercise. Simply putIntelligent Automation is a suite of products including RPA, AI/ML, IDP, Cloud, and Analytics. When implemented through a CoE approach to address the problem statement, it offers maximum throughput and allows automation of highly complex business cases. The reusable components generated can be used in other automation cycles throughout the enterprise. It offers high interoperability with different product platforms and technologies to generate robust yet flexible automation solutions. Rajesh Agarwal, SVP & Head ­ RPA
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