How RPA Enables Intelligent Chatbots

As companies ramp up digital transformation plans in 2022, excessive automation will escalate from an option to an indispensable necessity as organizations across industries accelerate to automate as much as possible and improve business resilience and agility. for example, Gartner He predicts that by 2024, 75% of governments will have at least three enterprise-wide hyper-automation initiatives launched or implemented.

As companies scramble to keep up with the tidal wave of messages that customers will send across a wide variety of channels, automating conversations is the next step for the hyper-automation model. Robotic Process Automation (RPA) and Conversational AI provide the perfect technology coupling to drive the next stage of transformation in a digital-first world.

RPA technology is the peanut butter of conversational AI jelly

Incorporating RPA, conversational technology, and artificial intelligence is a revolution when it comes to automation and improving customer and employee experiences.

RPA technology automates tasks. Conversations AI automates conversations. Combined together, RPA-enabled intelligent chatbots can access information from isolated and often inaccessible back-office systems and output it to users to handle complex requests and queries in real time securely and at scale—two critical factors for hyperoperability.

This technical tag team also makes it easy for customers and other untrained users to take advantage of customer service systems and quickly resolve their needs through self-service channels or rapid assessment and redirection to a direct human agent. This provides customers with the convenience of fast and accurate 24/7 service across a variety of channels.

Advances in Natural Language Understanding (NLU) and Natural Language Processing (NLP) are paving the way for more natural conversations between clients and chatbots, where interactions are based on actual words and dialogue rather than menus and hierarchical models. Chatbots are already one of the best use cases for artificial intelligence in enterprises, and when users feel more comfortable with self-service options, Adoption rates are expected to double over the next two to five years. AI-based RPA technologies will allow organizations to scale and manage growing volumes of data.

Take the mortgage application process, for example. Whereas live agents use to confirm application information with applicants on the phone and then manually add the data to the system to generate and deliver a credit bureau report, today’s RPA-powered chatbots collect data and manage applicant credit and background checks in real time—the time an applicant submits information on The channel he chooses, which can range from SMS to a chatbot.

Here, RPA and chatbots can operate asynchronously: the chatbot’s interactions with clients trigger RPA operations. RPA bots work in the background, automating all the repetitive hand movements and typing that agents use to manage them while the chatbot continues client interaction to complete the process more quickly.

Self service for expansion

Today, customers are more sophisticated when it comes to support – they know what they want and how they want to interact with the companies they do business with. AI-powered self-service is one of the rare winning scenarios where cost savings and flexibility align with customer channel preferences and improve customer satisfaction and employee experiences. according to GartnerDigital self-service channels are expected to become one of the most valuable capabilities of service organizations. The self-service approach enables organizations to deliver customer expectations for real-time and on-demand support on their preferred channel while improving operational and cost efficiencies.

The combination of RPA and chatbots provides new customer-facing self-service capabilities by automating processes that would normally require a direct agent. Instead, we design for human-machine interactions, and teach RPA-powered intelligent chatbots to understand and meet customer needs through feedback loops for continuous performance improvement. RPA technology accelerates automation, while intelligent chatbot technology enables a simplified model for a self-service experience. By leveraging the built-in automation capabilities of RPA and chat bots, organizations are gaining a consistent and scalable way to manage consistently higher levels of demand, accurately, and with better customization even in times of high volume.

Insurance companies, for example, can deploy smart chatbots to create a fully digital claims process that enables customers to fully manage their claims through chatbots, eliminating the need to print, mail and scan expensive and time-consuming materials.

A new generation of chatbots for the first digital customer experiences

Today’s smart chatbots are a far cry from the original chatbot. While chatbot 1.0 was mostly based on FAQ data, RPA-enabled chatbots are transforming customer experiences with advanced NLU and NLP technologies that enable chatbots to better understand user questions and how to best serve and meet those needs. Customized customer interactions and real-time support allow organizations to quickly and accurately resolve customer requests, increasing levels of positive customer experiences.

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