RPA and Chatbots: The Powerful Intersection of AI

Almost every industry sector has increasingly become subject to the ever-evolving technology of automation. In the surge of disruptive technologies, AI is creating another wave of opportunity to not only improve the degree of automation but also applying intelligence and cognitive understanding of workflows and processes.

Automation technologies, like the Chatbots, are rising increasingly, allowing RPA to collaborate with cognitive capabilities and artificial intelligence. As more complex activities are emerging for automation, so does the functionality will continue to transform. In the upcoming years, we shall see some procurement functionality integrated with a virtual workforce of AI chatbots and RPA technologies. 

As McKinsey states, AI with machine learning & other related technologies are making road towards process management software, natural language processing & generation, and cognitive agents or bots.

As RPA technology is evolving with the assistance of AI. However, conversational AI and RPA intersection may have given rise to smart bots or the chatbots. Conversational AI, a revolutionary approach where user intent and conversation dictates the tasks. This process is unstructured and free-flowing that tries to read the intent of the user in order to fulfill it successfully. 

Bots Overlapping the Popularity of RPA

With the conversational bots on the stage, there had been strong arguments about Chatbots overpowering the capabilities of RPA. Through the conversational AI and approaches to smart conversations, the bots are to progress from a simple Q & A type of interactive software. 

Chatbots are made much more intelligent to understand high-level customer intent and pass to the task-oriented bot for gathering added information to execute the task. 

The latest conversational AI platforms contain technologies, tools, and approaches that are faster and efficient than the legacy system and methodologies.  

How Chatbot and RPA Prove Brilliant Companions?

Business-process is an ever-evolving system that needs cognitive decision-making capability to provide scalable solutions. Thus a single tool like RPA can only work on rule-based repetitive tasks to assuage the manual mundane task. So, cognitive engagement in the form of a bot gives an edge to achieve end-to-end automation. 

The ways that make the amalgamation of these two technologies complimentary are -

Inputs and Processes 

Since it is known that RPA works accurately when the rules are defined for specific tasks, but chatbot, on the other hand, does not require a rule book to function, it can work for a specific use-case to trigger RPA. Thus these both can work together - like a bot to gather information and give its inputs to RPA to process and provide real-time end solutions.

Intelligent Layer 

Another benefit to integrate the bot with the RPA is its robust cognitive engagement feature. One of the renowned automotive organizations evolved a stateful network for the AI process (SNAP)  that makes the bot intelligent by restricting itself to deliver an anomalous reaction or unnecessary transactions. However, the self-learning ability of Chatbot allows process automation to perform intelligent decision-making to streamline business flow.

Real-Time Execution

Combining cognitive qualities in Chatbot with RPA can seamlessly handle the most complex tasks and queries of the users in real-time. Companies are planning as well as some working to build their bots to understand user intent and gather the data from them in order to give their customers relevant information when required. 

User Experience

Like offering a 2-way communication, a Conversational AI bot can also engage the user. Unlike the traditional ways to gather user data, RPA bots can gather data through mediums like forms and surveys that provide user feedback on the brand's services. This collective data not just helps the brand to improve user engagement but deliver a better experience altogether.

A chatbot can easily understand the user intent, gather user information, and have a human-like conversation. The information can be transported to RPA, capable of handling back-office complex tasks easily, effectively, and in-time. So, the Chatbot handles the front face, and RPA works behind the scene.

Kinds of Bots Used for Different Services

• Service Bots

These bots can automate simple tasks, service requests, making service experiences more convenient and available 24/7 across multiple channels. 

• Journey Bots

These kinds of bots are developed to manage multi-step, guide through specific workflows, fulfilling particular tasks. 

• Campaign Bots

These bots are designed to be deployed for outbound tasks, executing marketing campaigns such as proactive loyalty outreach, promotions, retention, win-back, collections, and upsell or cross-sell opportunities.

• Employee Bots

Employee engagement is the foremost priority for any business. Workplace bots can handle internal employee-related tasks, improve the efficiency of field service workflows, HR-related tasks, and IT help desk operations. 

• Automation Bots

These kinds of bots are designed to perform recurring tasks such as billing, renewals, and appointment setting. They proactively automate regular tasks for improving overall efficiencies, freeing employees to focus on more complex tasks.

The amalgamation of Chatbot and RPA can solve some of the major challenges of enterprises. They can together overcome internal and external issues reducing operational costs by solving user queries without any human intervention. 

Use Cases of Chatbots with AI 

There are some chatbot engines integrated with AI decisioning tools, but you cannot build momentum on one particular solution, says Gartner. 

Decision points 

You can change the conventional business process by adding intelligent decision points. 

An insurance policy provider, American Fidelity Assurance, was facing issues related to automatic routing emails that came every day to correct the destination. They then integrated an AI platform, DataRobot from an RPA vendor. 

This helped the new email process, which combined RPA components with machine learning components. These two technology components decide where the email needs to be routed. 

Further, the organization is looking to use AI for process mining to automate process discovery, rather than business analysts figuring it out.  

Process Mining 

The conventional process for mining included various persons, like the business analyst, managers, and other employees of the organization. They were meant to carry out audits, create charts, and workflows that illustrate business processes. Today, machine learning is doing half of the work, process mining. As businesses evolve, the tools can update the processes and spot anomalous behavior in real-time. 

One of the real-time examples of automated process mining is Chart industries. Their process of providing different opportunities and benefits to their customers was vast, which made the back office work hard to manage.

Thus with the help of a process mining vendor, they could easily uncover the opportunities. Their challenge to lift the data between their organization to SaaS applications or Amazon back end was resolved with the help of a process mining vendor. 

The vendor offered software that has eased up the process of the organization by allowing its managers to view the individual level transactions as well as check business processes in form of charts and diagrams.

A Versatile Bot

This use case is about a bot that has the capabilities of governance, management, as well as supports multi-linguist. Germany based an automotive supplier, which intelligently created a sharp bot to manage business processes as well as answer repetitive questions humbly.

The automotive bot creation company understands the need for automating repetitive manual tasks. Thus they planned on developing more than just an automated bot, a software that can utilize the disruptive technologies and combine them for effective solutions.

So, ZF Group could successfully create a bot that can underline all necessary tasks. With an AI process, the company could manage the bot to train itself from performing an unwelcoming behavior. This process also ensured that any transaction must be stopped or not shared if found any compliance violations or inappropriate.

In the Nutshell -

RPA can further associate with bots to automate processes, eliminate inefficiencies, cutting costs, and improve speed & performance. This is the next step to the traditional process of automation. This new automation varies from the rules integrated automation, capable of solving complex tasks.

So, we can say that, as automation drives productivity in the organizations where procurement will be at the center of the growth agenda driving connected ecosystem driven digital technology. Observing, many organizations have already started investing heavily in the growing digital capability while reducing the conventional cost of transactional and tactical activities. To make your business process efficient, contact Robotic Process Automation Company that offers the development of different kinds of bots that are compatible with the company�s requirements.