Analytics solutions & Business Process Improvement
RPA process improvement using Artificial Intelligence And Machine Learning

The impact of Robotic Process Automation (RPA) on the enterprise business functions is proven and the use of RPA agents to execute repetitive work reduces costs, reduce errors, and improve customer experience. The following is the area with AI can work in conjunction with RPA to achieve next milestone.

Managing unstructured data

The unstructured data exists in many forms in organizations such as; contracts, forms, contracts, and other free text content. And it requires tremendous effort to convert into structure form to feed in the RPA robots.

RPA functions are based on set business rules based on structure data and processes. The RPA core functionality which supposes to mimic human actions and simulates computer input devices such as keyword, mouse and OCR exaction failed to deliver when it comes to unstructured data.

RPA can take a role to aggregate all the unstructured data and feed into the API modules for answers and act on it. In a sense, the AI modules become one of the RPA activity along with human touch simulation.

Customer Service

The large organizations’ IT in built upon massive and sometimes outdated systems, the access to information required to service a client or partners is tedious work and it requires in-house developed applications and layers of management to deliver the information down in the hands of customer service departments.

The rise of Alexa, Google Home, and Chatbot made organizations think of their customer service strategies. In order to make information available to clients, it requires a number of employees to get the information manually out of the outdated systems. Now, if the same information needs to be available for Chatbot, Alexa, or SMS, it will be next to impossible for organizations to stay competitive.

That’s where RPA can step in along with AI and NLP (Natural Language Processing) to deliver right content in an efficient manner from a system which can’t be expanded to connect with an external system with an APIs.

Data Analytics

Cooperations need data to understand their business, bottom line, ROI and targets. And many times it’s not from one source, the reports may need data from several other legacy systems which requires a human touch and intelligence to aggregate and prepare reports for the management and clients. This is a time-consuming process and in today’s business world where everyone excepts to have information NOW to make decisions. The RPA can be a great tool when it comes to extracting data from different systems and aggregates it. And AI can use natural language processing to create a summary from a block of raw data produced by RPA robots instead of using armies of people.