With a view to enhancing productivity and cost-effectiveness, many organizations have embraced RPA (Robotic Process Automation). RPA is primarily implemented to perform repetitive tasks involving structured data processing, with accuracy and speed. Traditional RPA lacks the capability to handle unstructured content such as texts, images, emails, invoices, legal documents, web content, etc.
Over the years, it has been observed that 80% of the content is unstructured in nature and therefore, organizations can no longer rely on traditional RPA solutions. With growing competitiveness of the market, companies are investing heavily in newer and advanced technology such as AI (Artificial Intelligence) having NLP(Natural Language Processing) and computer vision capabilities.
AI can process unstructured content and hence complements the capability of traditional RPA. With both AI and RPA, it is possible to automate tasks that are not only repetitive but also involve unstructured content.
Before the advent of AI, unstructured content used to be processed solely through manual intervention due to inability of traditional RPA in handling unstructured content. AI in tandem with RPA led to the concept of cognitive automation which automates processing of unstructured content using NLP and computer vision capabilities.
For example, in many organizations, manual document processing is a costly and time-consuming task. Though traditional RPA can automate structured-document processing, it is an ineffective solution to tackle multi-format, unstructured documents. It is precisely for this reason, AI-powered RPA is an efficient solution that can be leveraged to automate the task and enhance efficiency, scale, speed, cost-saving and ROI.
Applications of AI-powered RPA Automation
With NLP, it is possible to analyze natural languages. This finds wide application in customer care departments where NLP is used to solve customers’ queries without manual intervention. NLP analyzes email content or service tickets and provides relevant, accurate responses in a matter of seconds, improving turnaround time and customer satisfaction.
Computer Vision automates processing of several formats of documents such as checks, handwritten applications, forms, quotes, invoices, etc. across myriad of industries such as banking, healthcare, legal, insurance, hospitality, retail, manufacturing, etc. When AI is implemented alongside RPA, the combination can boost efficiency through cost reduction and faster turnaround time. Many companies are equipped with traditional systems to automate structured data processing. This type of data can be represented within a database and can be processed easily. When it comes to unstructured content such as texts, web content, images, PDFs, etc., companies struggle to process them with traditional solutions as this requires AI capabilities.
Therefore, some of the front and back office business processes involving unstructured content cannot be automated with RPA alone. Hence, it is imperative that organizations introduce AI-powered RPA automation to go beyond the traditional realms of automation and enable unstructured content processing to boost productivity, scale, cost-saving and efficiency. Cognitive automation strengthens competitiveness of an organization.
You can read more about how AI-driven RPA is transforming customer care in our blog How AI is Revitalizing Customer Care.
If you would like to explore how implementing AI-powered RPA can improve your business operations, the RAP AI team would be glad to help you. Our next-gen, AI-powered content intelligence platform RAPFlow enables full lifecycle AI orchestration on a single platform. When used in tandem with our RPA solution RAPBot, it provides end-to-end workflow automation capabilities that can be deployed in just weeks. You can even build your own use case and the platform can easily integrate with your existing systems. Book a demo to get a more detailed understanding of how our products can transform your business.