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Automation has become a pressing mandate for businesses to cope with the increasing demand for streamlining processes, increasing efficiency, and reducing dependency on labor. As per a Gartner survey, 85% of Infrastructure and Operations leaders without full automation expect to increase automation by 2025. Combining the capabilities of artificial intelligence with automation can supercharge automation efforts and deliver a bigger payoff. In the words of Maureen Fleming, Program Vice President at research firm IDC, as shared on CIO, ‘AI tends to broaden the reach and impact of automation, taking on activities that cannot be performed solely through automation.’
AI-powered Intelligent Process Automation broadens the scope of automation helping tackle challenges from the extremely complex to the most common across the various stages of the automation journey. While integrating AI into existing automation efforts tops the list of must-have capabilities, realizing its complete potential can be an ask if not done strategically and systematically.
The first step towards realizing intelligent automation is to identify all possible processes that can be automated. Zeroing in on repetitive, rule-based tasks that consume a significant amount of valuable resources is an ideal starting point. Processes such as data entry, document processing, customer support, and inventory management, perfectly fit the bill for automation.
Once the suitable processes have been identified for automation the next step in the journey is to analyze these processes thoroughly to have an inside-out understanding of the intricacies and potential. The analysis will then help map out the steps involved, identify bottlenecks, and seek feedback from the employees who handle these tasks regularly. The analysis and the follow-up action are essential to lay down the foundation for streamlining and preparing processes before injecting automation.
Following up on the analysis businesses need to select the appropriate IPA tools and technologies that align with the requirements. Choosing the best fit among the technologies like Robotic Process Automation (RPA) software, AI-driven data analytics platforms, Natural Language Processing (NLP) solutions, machine learning algorithms, and more, ensure smooth integration with the existing systems.
A pilot implementation on a single process or a subset of a process, carried out on a small scale helps test the effectiveness of the chosen IPA technologies. Closely monitoring the results and gathering feedback from employees involved in the pilot will chart out the progress by helping gather feedback from employees involved in the pilot, ironing out issues as they arise, refining the automation parameters, and ensuring that the automation aligns with desired outcomes.
The ensuing step after successful pilot testing is to gradually scale up the implementation of intelligent process automation across other processes. Keeping a close monitor as the purview of intelligent automation spreads across processes enables us to keep an eye on efficiency, accuracy, and employee experience. A dedicated view of the emanating feedback and data helps keep the processes flowing uninterrupted and drives design improvements. Keeping a close watch on automation efforts also provides organizations with a valuable understanding of how and when to scale and derive optimized potential from the efforts.
As with the adoption and use of any new technology, the integration of IPA too can face hurdles. A defined, transparent, training and communication plan to educate the workforce on the possible changes can ensure the smooth integration of automation across processes and functions. Providing required training and upskilling opportunities to employees is essential for IPA efforts to take flight and for businesses to realize the benefits.
Innover’s Intelligent Process Automation solutions can be customized to meet the automation needs and strategies of organizations, fitting in perfectly to align with your automation journey. Our ready-to-use bots, AI models, robust frameworks, and expertise across a variety of technologies ranging from OCR, ICR, NLP/NLU/NLG, Computer Vision, Deep Learning, Neural Networks, and more redefine your enterprise-wide process automation for increased productivity and efficiency with a keen focus on ROI. Partner with us to embolden your automation efforts to meet the evolving demands of business, deriving unrealized potential, and designing future business narratives.
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