RPA and Chatbots: The Powerful Intersection of AI

By 5 Minute Read

RPA and Chatbots: Winning AI Technologies


Terminology abounds in the area of artificial intelligence (AI) and multiple definitions can lead to confusion and blurring.

In industry sectors like manufacturing, utilities, energy, finance, healthcare, and telecommunications, routine, rules-based, and repeatable business processes have been subjected to increasing degrees of automation throughout the decades. Increased accessibility and advances in the area of Artificial Intelligence (AI)  are creating another wave of opportunities to not only increase the degree of automation but also to apply greater intelligence and cognitive understanding to workflows and processes.

One area of technology evolution in process automation has been in the area of robotic process automation or RPA. But more recent developments in chatbot technology and conversational AI may be set to disrupt how organizations approach the automation of business processes. There seems to be confusion regarding these two topics with an increasing blurring of the lines between the two. So how do these two differ and how do they intersect? 

To try to clear up any confusion we decided to explore the characteristics of both, compare and contrast them, and uncover where they are being used across different industries.

The Characteristics of RPA and Chatbots

RPA applies software robots or bots, to further automate processes, eliminating inefficiencies, cutting costs, and improving speed and performance. It is the next stage in the evolution of traditional process automation, which has been around for decades. The technology can vary from basic rules-based automation to very complex solutions based on machine learning. At the more basic end of the spectrum, solutions are often an extension of traditional business process and rules management while at the more advanced end, the complexity means that data scientists are required to build highly custom AI solutions that are both expensive and difficult to scale or adapt with shifting demand. 

The key characteristics of RPA are:

  • It is applicable to routine, repeatable, rule-based, or predictable business processes.
  • It is primarily based on automating existing business processes.
  • It focuses on eliminating manual or human involvement in process steps.
  • It is governed by structured data inputs and not human inputs or chat.
  • It is a  process-centric, bottom-up approach
  • It decreases friction across process tasks by limiting human handoff
  • It focuses on back-office processes governed by rules and business logic, for example in the areas of finance, operations, production, HR, and distribution departments
  • It lacks the flexibility to adapt quickly to changes or exception-handling
  • Finally, RPA implementations are generally IT-led with input from the business

Where the confusion between RPA and Chatbots comes in is that both are strongly associated with robots or ‘bots’. In the case of RPA, these are automation bots and in the case of Conversational AI, these are chatbots (often also referred to as conversational bots, AI bots, or digital assistants). RPA bots don’t have a chat element whereas chatbots rely on natural language technologies to emulate human-like conversations. In the early days of chatbot technology, these were often characterized as digital assistants that responded to simple Q&A-type requests. Now they have evolved to be much smarter conversational bots that can automate tasks, detect sentiment, respond to context switching,  and handle complex user journeys.

The key characteristics of Conversational AI are:

  • It is applicable to any user-centric process or journey that is initiated or conducted via voice (phone, physical or voice-activated interfaces) or message (text, chat, email, web, etc).
  • It is primarily based on automating user-facing interactions and journeys on digital channels, transforming digital engagement models.
  • It focuses on simulating human conversations and understanding human intent to perform automated tasks.
  • It is governed by free form or guided conversations that are less structured
  • It is a  data- and conversation-centric, top-down approach
  • It decreases friction across process tasks by limiting human intervention
  • The current focus is on front-end customer-facing processes (for example customer service, sales, and marketing) but they are equally powerful in many back-office tasks where they are gaining traction (e,g, HR, IT Helpdesk, Claims Management, etc.).
  • It is very versatile, adapting quickly to changes and gaining intelligence and capabilities through training
  • And, chatbot implementations are mostly business-led, but involving IT.

RPA and Chatbots: The Powerful Intersection of AI 1

Chatbots always involve some form of conversational interaction, via either voice-activated or messaging interfaces. RPA, on the other hand, can be applied to a discrete process that does not involve any type of user chat or interaction. For example, RPA could be applied in generating customer invoices by downloading customer order information from back-office systems or screen-scraping and extracting the information when it is not available from code. A chatbot, on the other hand, can be used to respond to a customer’s text requesting details of an invoice, interpret the intent, retrieve the appropriate data required to fulfill the request, and present the information to the customer. 

Recommended Reading: The Fundamentals of a Successful Chatbot Strategy

RPA and Chatbot Approaches Differ

Process automation has been around for decades with robotic process automation representing more of an evolution in approach. In RPA, processes are automated by teaching robots what to do rather than automating them through code or scripts. So it’s a step up the curve towards more intelligent automation.

As RPA evolves it is increasingly intersecting with conversational AI technology. In fact, more and more, recent media articles have added the word bot or chatbot when referencing RPA, making things even more blurred.  However, it’s important to recognize that the RPA approach is much different from the conversational AI approach and each requires different skillsets.

Conversational AI represents a revolutionary approach, where conversations and user intent dictate the tasks and processes that are executed in order to fulfill the intent. By its nature, it is more free-flowing and unstructured requiring a high degree of flexibility in orchestrating the right tasks at the right time. This contrasts with RPA where the processes are less fluid and more rigid. Layering conversational AI on top of RPA creates the potential for a more comprehensive end-to-end approach to automation.

Bot orchestration is probably one thing that makes the conversational approach much easier, faster, and more versatile than an RPA approach.  At ServisBOT, by using a clever bot orchestration approach, a Dispatcher can hand off a high-level customer intent to an appropriate task-oriented bot who can either execute on the intents or invoke the help of another bot, if needed. In this way, multiple bots can be assembled to handle different tasks in a customer journey and individual bots can be deployed or removed according to how the conversation guides the execution of tasks. This is a much more flexible and modular approach than traditional RPA.

Bot Orchestration Diagram - ServisBOT

But will Chatbots replace RPA? 

Whether RPA will be fully replaced by chatbots is doubtful as there will always be use cases that lend themselves more to RPA, but there definitely are strong arguments that may lead to conversational bots stealing some of the thunder from RPA. Or maybe there’s merit in them working together to unite the best of both worlds? 

Conversational AI is a greenfield technology and approach to smart conversations and these are increasingly not just focused on simple Q&A type interactions. Rather, a chatbot can now understand high-level customer intent and pass that to a task-oriented bot to gather any additional data needed and execute the necessary tasks. As this evolves and matures, smart conversational bots are set to eat away at the RPA space.

The Use Cases for Chatbots

The broad differences between RPA and Chatbots have been mentioned above as have some of the high-level use cases. Wherever there is a chat element to a process think in terms of conversational AI. And if the process is highly administrative with no chat element, maybe RPA is the right choice. Another blog describes more about the intersecting use cases for chatbots and RPA

Don’t think too narrowly about conversational AI. Many of the current implementations are in the areas of more basic customer service use cases. However, businesses are increasingly extending their horizons beyond customer service, recognizing the potential for bots to go broad as well as deep across and within their organization and to be used in outbound marketing campaigns, in field sales or service operations, or in employee-facing engagements. Here are some use case categories that may help guide you in choosing conversational AI 

For more information about prioritizing the use cases for conversational AI and building and deploying AI bots that can intelligently engage with your customers and handle complete customer journeys, you can visit our resource library or download our new eBook: A Conversational AI Journey Guide.

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