RPA (Robotic Process Automation) deals with the underlying opportunities of Artificial Intelligence that enabled RPA in an ERP ecosystem.

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How a Chatbot can combine RPA, AI, and ERP
venkat k
May 12 · 4 min read
RPA (Robotic Process Automation) deals with the underlying opportunities of Artificial
Intelligence that enabled RPA in an ERP ecosystem.
Chatbots, simulate automate human conversation through voice commands, text chats,
or both. They can be used through messaging applications or web pages and are
naturally deployed in dialog systems for various application fields (e.g. customer
service). The boom of AI enables smarter Chatbots to understand unstructured human
input by applying natural language processing (NLP).
Also Read: Top 10 Ecommerce App Development Companies In New York

2. 5/13/2020 How a Chatbot can combine RPA, AI, and ERP - venkat k - Medium
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How to further increase the potential and overcome the
limits of RPA?
In recent years, RPA has been one of the most impactful technologies in process
automation in all kinds of organizations. Most of the RPA systems rely on structured
data, static rules, and a recurrence of events.
They capture structured data based on the rules engine to perform the pre-defined
workflows. However, the static setup does not allow the processing of unstructured data.
AI is the needed game changer and adds an intelligence layer on top of RPA systems so
that they can handle unstructured data thanks to their dynamic ruleset.
Then RPA will be able to manage exceptions, and the system improves itself after further
training. AI can derive sense out of unstructured data and deliver the now structured
data to the existing RPA systems.
Algorithmisation is the process cycle of the gathering of information out of data for
Machine Learning and creates new processes plus data for further processing again.
Chatbots integrated into existing RPA & ERP ecosystems can provide structured data out
of the human conversation for the processing of the back-end systems.
How can Chatbots support in Master Data Management?
Let’s see how Chatbots can further optimize the master data management processes.
Often the employee needs to manually structure the unstructured customer input (e.g.,
email, phone) before it can be automatically processed by RPA.
A Chatbot would offer a natural way for the customer to directly change his master data
without the need to find the right account settings or form. It also facilitates back-office
employees and they can focus on exception handling or more value-adding tasks. The
single automated communication channel saves time for both.
Possible use cases are ranging from simple ones such as an update of the name, postal or
email address, phone number, etc. to more complex ones where more data needs to be
analyzed by the AI. For instance, the change of order details, contract data,
authentication method, or the request of the FAQ. A text Chatbot should be

3. 5/13/2020 How a Chatbot can combine RPA, AI, and ERP - venkat k - Medium
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implemented before a Voicebot since it needs the same underlying logic system and
voice integration is more complicated. All mentioned use cases have several benefits in
common:
Direct Plug-in between different systems (same front-end)
Scalable AI and RPA capabilities (from simple to complex use case)
Best of both: Combining the strength of AI (unstructured data) and rule-based RPA
No human interaction required in the whole process
How can a Chatbot with RPA and ERP integration be set
up?
Within eight weeks we developed a tangible AI MVP (minimum viable product) for
automatic master data updates starting with the chat as an input channel and the
customer’s wish to change the postal address. We utilized IBM Watson and its
conversation as services for the NLP capabilities of the Chatbot. It is entirely integrated
into an existing UiPath and SAP system, but could also work with other RPA/ ERP
software.
Successful execution requires end-to-end expertise due to the various tasks. Capgemini
as a Group is delivering the Chatbot MVP as a team of experts from multiple fields:
Consulting Services:
Leading overall agenda and bringing in experience in RPA, ERP, and digital
customer journeys
Use case creation, functional and business specifications, setup of UiPath and SAP
workflow, and agile project management
Technology Services:
The Capgemini APPS — IBM Watson Team is responsible for the Development of the
AI conversational service, core application, and the front-end development
Business Services:

4. 5/13/2020 How a Chatbot can combine RPA, AI, and ERP - venkat k - Medium
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Focus on combining RPA and AI and the seamless integration of the interfaces
Experience Design Services:
UI design and visualization of the Chatbot characteristics
Further competencies with additional complimentary 3rd party software partner,
Consulting companies, or the client are working with, can be brought in depending on
the specific requirements and client setup.
Based on our experience we suggest four months to implement a Chatbot into a live
environment. Our MVP took us two months, but integration into a live back-end system
and the training of the NLP capabilities would require two additional months.
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