Cognitive automation vs RPA: Path to Automation

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Cognitive Automation vs RPA How Enterprise
Automation is More Effective with Cognitive
Process Automation

• Today, AI-powered automation is gaining
  widespread recognition, and for a good reason. It
  has
• made our lives easier. With the advent of virtual
  assistants, weve already experienced
• rudimentary AI via our smart gadgets. A simple
  example would be an Alexa or a Siri who can
  listen and converse with us by simply following a
  wake word. Another area where we all experience
  automation in our day-to-day lives is customer
  care. Be it our banking needs or
• fixing an issue with our mobile operator, we no
  more need to be queued up for minutes (or even
  hours) to get connected to customer care rep.
  Virtual assistants are there to not only attend
  to our simple queries but also resolve most of
  our not-so-complicated issues without any human
  intervention. Even though that is a technological
  leap compared to a decade ago, AI-based
  automation has evolved into so much more than
  just bots.
• What is Cognitive Process Automation?
• Cognitive process automation or intelligent
  automation is the process of putting intelligence
• into traditional process automation techniques by
  employing employs artificial intelligence and
  natural language processing (NLP). It enables
  enterprises to better capture data, automate
  decision-making, and scale automation. Unlike
  Robotic Process Automation (RPA) which works on
  simple if-then logic and can only handle
  structured data which is typically organized in
  enterprise systems, CRM, LMS, ERP, etc., CPA
  intelligently processes structured as well as
  unstructured data that includes voice, video,
  document repositories, URLs, and more. While RPA
  replaces the human to perform mundane,
  unintelligent tasks, Cognitive Process Automation
  puts the human in the robot to handle complex
  data, bring out insights, make decisions, and
  much more.
• Cognitive automation vs RPA Whats the
  difference between the two?
• Robotic Process Automation (RPA)
• The thing to remember is that RPA, like RDA and
  Chatbots, is more of a first-gen technology. Its
  ability to handle high-volume tasks helps with
  simple business processes like data entry.
• Meaning that it has its limitations. For
  instance, RPA is process driven its designed
  to offer
• choreographed, robotic repetition and generally
  malfunctions when dealing with inaccurate,

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unstructured, or blank data. In other words, it
cannot problem-solve. When it hits a wall, human
intervention is required to complete the task and
watch for the subsequent breakdown. Besides, RPA
is best to be deployed in a stable environment
with standardized and structured data. Meaning,
RPA is typically programmed for back-office
automation and especially excels at automating
rules-based tasks that strictly follow
if-then-else logic. It can be largely used to
drive a degree of process efficiency and
reduction in routine manual processing. Although
it is able to drive significant value but isnt
incompatible with truly transformational change
in enterprise functionality due to its inability
to deal with complex decision-making tasks. The
other issue with RPA is the cost. It would cost
an organization a significant sum to build or
outsource the technical know-how required to
automate each process individually. This could
take months to accomplish. Not to mention, the
desired results depend on the entire process
remaining the same for all that time. Any change,
however minute, could result in additional
expense and development. Cognitive Process
Automation Cognitive Process Automation is built
on AI-based human-like thinking. Hence,
CPA-powered AI solutions can be implemented to
handle complex employee and customer-centric
tasks. This can automate a variety of tasks
across enterprise processes including HR, sales
and marketing, IT operations, customer service,
finance, and more including lead creation,
discovery, support, ticket generation, leave
application and approval, and much more. With
CPA, its possible to manage all this in natural
language using an omnichannel interface across
the web, WhatsApp, Teams, and more. Its suitable
for a complex IT environment with
non-standardized and unstructured data as it can
efficiently turn any data gathered from
documents, customer interactions, or voice into
an efficient business workflow. In other words,
CPA helps bridge the gaps between RPA chatbots,
low-code applications, and programming
interfaces. Cognitive Process Automation is great
for deriving meaningful conclusions from
unstructured data. Most business processes can be
automated resulting in an organizations improved
efficiency, especially in customer-facing
processes, given the importance of capturing and
understanding users requirements and feedback.
Furthermore, it blends a variety of AI techniques
such as NLU, sentiment analysis, image
identification, and intelligent data extraction
to analyze huge volumes of information around
complex business tasks in a way that mimics human
thought and decision-making making it seamless
for businesses to adapt quickly and act on new
patterns and insights. How Does Cognitive
Automation Help in Coping with the Limitations of
RPA?
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Much of the confusion around RPA and cognitive
automation comes from the fact that they are
closely related to each other and in many areas,
have worked hand in hand. These technologies are
two ends of the same intelligent
automation. Scope Traditional automation and RPA
can only be used to automate repetitive,
mechanical, straightforward, and mundane tasks
which follow a rigid set of rules and hardly
require analysis or thinking. Cognitive
automation, on the other hand, is all about
bringing automation to major enterprise processes
that require a certain level of decision-making,
human-like judgment, intelligence, and insights.
It enables machines to complement the human
workforce when it comes to tasks or processes
that involve challenging amounts of data to be
processed, monitored, and analyzed with specific
business objectives. The type of data
processed In todays world, data is at the core
of any business, data that comes in various
forms. An organization thats not employing ways
to harness it is sure to lag in the cut-throat
competition. It can be organized in a predefined
format, say a database or spreadsheet with rows
and columns known as structured data. This kind
of data can be easily handled and hence,
automated using RPA for the obvious reason that
it doesnt require intelligence to be processed.
However, a major chunk of enterprise is
classified as unstructured data from videos to
audio files, images, web URLs, and more stuff
that cannot be processed by RPA. This is where
cognitive process automation tools play the role
of bringing in the intelligence that it takes to
make sense of this enormous amount of data
reducing human intervention, augmenting speed and
accuracy, and enabling enterprises to achieve a
superior level of intelligent business
automation. Automation method RPA typically is
applied to automate processes that require
decisions that follow a simple if/then logic to
eliminate the manual effort from time-consuming
tasks that need rapid and monotonous step-by-step
actions. Cognitive process automation on the
other hand, enables machines to make human-like
conversations and make decisions as a result of
AI and NLP-led training that they go through to
learn human behavior and comprehend information
in various formats including but not limited to
voice and video.
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In simple terms, AI co-workers configured using
CPA can think, reason, and perform activities
like humans but on both structured and
unstructured data with better accuracy and speed.
RPA and other traditional bots on the other hand
need to be told what to do and can only follow a
set of instructions, processing only structured
data. Without specific instructions, which is
impossible in the case of complex processes
involving a volume of unstructured data, RPA can
malfunction or even crumble, hence limiting its
application. But, as humans, what do we do when
faced with incomplete instructions or
information? We problem-solve, learn, adapt, and
grow. Thats exactly what CPA does, and it does
so more efficiently! Conclusion RPA helps
organizations reduce back-office costs and
increase productivity by performing basic tasks
with greater precision and accuracy. While some
of the mundane processes can be automated using
RPA, complex tasks require context, judgment,
prediction, and an ability to learn. Cognitive
automation tools use AI techniques in places
where document processing, vision, natural
language, and sound are required, taking
automation to the next level allowing
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humans to sit back and let the machines do the
work. Additionally, it gives enterprises the
ability to foresee and continuously bring process
improvements in response to changes, trends,
patterns, and more! Intelligently Automate Your
Business Processes with E42 E42 is a no-code
Cognitive Process Automation platform that offers
enterprises the ability to implement various AI
co-workers irrespective of their line of business
to automate complex tasks or processes. These AI
co-workers could be customized accordingly to
help businesses solve a particular problem area
across verticals and functions. The most integral
component of these AI co-workers is that they can
think like humans, predict customer behavior,
understand user sentiments, take charge based on
analysis, as well as learn from each interaction.
These AI co-workers can work independently or can
be clubbed with other AI co-workers in the fields
of HR, finance, IT, customer care, and more
bringing process-agnostic automation to
enterprises!