AI‑Enhanced RPA for Smarter Automation
Key Points
- Hyper‑automation combines RPA with AI to create smarter bots that reduce errors, enable direct AI integration, and make human‑like judgment calls on tasks that require cognitive processing.
- IBM RPA offers a drag‑and‑drop Studio with over 650 pre‑built commands—including AI, browser automation, and terminal integration—allowing rapid development of both rule‑based and “no‑thought” automation with just a few lines of code.
- In the ACME Magazine scenario, AI is used to reconcile newly captured handwritten responses with an existing customer list, handling nickname variations and imperfect OCR extraction that traditional RPA could not reliably process.
- By inserting an “approximately equal” AI command that leverages a weak‑tolerance Jaccard distance algorithm, the bot can fuzzy‑match first and last names, automatically flagging potential matches and outputting the results for human verification.
Full Transcript
# AI‑Enhanced RPA for Smarter Automation **Source:** [https://www.youtube.com/watch?v=EBEIVhkIW2w](https://www.youtube.com/watch?v=EBEIVhkIW2w) **Duration:** 00:04:24 ## Summary - Hyper‑automation combines RPA with AI to create smarter bots that reduce errors, enable direct AI integration, and make human‑like judgment calls on tasks that require cognitive processing. - IBM RPA offers a drag‑and‑drop Studio with over 650 pre‑built commands—including AI, browser automation, and terminal integration—allowing rapid development of both rule‑based and “no‑thought” automation with just a few lines of code. - In the ACME Magazine scenario, AI is used to reconcile newly captured handwritten responses with an existing customer list, handling nickname variations and imperfect OCR extraction that traditional RPA could not reliably process. - By inserting an “approximately equal” AI command that leverages a weak‑tolerance Jaccard distance algorithm, the bot can fuzzy‑match first and last names, automatically flagging potential matches and outputting the results for human verification. ## Sections - [00:00:00](https://www.youtube.com/watch?v=EBEIVhkIW2w&t=0s) **AI-Enhanced Hyperautomation for Smarter Bots** - The speaker outlines how embedding AI into robotic process automation—through resilience, cognitive decision‑making, and drag‑and‑drop AI tools—creates hyper‑automation that enables bots to handle unstructured tasks like handwriting capture for a magazine publisher. ## Full Transcript
we know that makingbot smarter is the
next generation of robotic process
automation
often referred to as hyper automation ai
in rpa is frequently considered
accelerated capture
or process mining capabilities but
that's not the full story
ai matters with rpa when we say bots
working more intelligently
we mean providing resilience where the
bots make less errors
facilitating ai where the bots allow
enterprises to easily apply artificial
intelligence directly to their tasks in
cognitive processing
allowing bots to make judgment calls
that previously were reserved for humans
i'm zach silverstein ibm rpa america's
technical lead
and i'm excited to present to you today
about how ai-powered automation
can infuse rpa with cutting-edge
capabilities
to make your bots work smarter for you
not every task we deal with
is perfectly structured for traditional
rpa implementation
the tasks our knowledge workers execute
often require some cognitive thought
processes
such as categorizing tickets
understanding an email
or cross-checking names with ibm rpa
we can accelerate our implementation of
those no thought and lothal automation
opportunities
natively in just a few lines some of
these include
our easy to implement knowledge bases as
well as our ai processing through drag
and drop commands
so let's talk about our scenario we have
acme magazine company implementing a
handwriting capture solution
on their pre-addressed mail acme has a
list of their current customers
but if they get a response flyer a human
must still manually validate that the
submitting customer
isn't already subscribed oftentimes
people may use nicknames
or the capture solution may not
perfectly extract the handwriting
so previously rpa couldn't be applied
well let's see just how easy it is to
automate
this is our ibm rpa studio on the left
hand side we can see our toolbox
with over 650 commands including ai
browser automation terminal integration
and a ton of other pre-built commands
right in the middle of the screen we can
see a command palette that we've
partially filled out
now let's take a look at our two files
we have our csv
file of the new customers from the
capture system
and an excel file of our existing
customers
we can see some capture errors similar
characters
and even people submitting cards with
their nicknames
let's go ahead and now execute that bot
we can see that there's only one perfect
matching record
based on first name and last name now
let's add a bit of ai
we'll go ahead and grab the
approximately equal command
and drop it right into our script we're
going to provide the source text
for the existing customer's first name
and last name
and we're going to compare that with the
target text of the new customer's first
name and last name
we support many different algorithms but
due to the type of data we're working
with
we'll use a weak tolerance jaccard
distance for its flexibility
we've now simply applied ai to our bot
next let's have our bot print out the
results of that ai action
we'll grab our log message command and
drag it into our script
and we'll type is existing customer
first name
last name similar to new customer first
name
last name and then our flag let's now go
ahead and execute the script
the results we can see reflect ai
cognitively comparing the names
now we can see our bot is already using
ai in just one command
to apply fuzzy logic to painful everyday
scenarios that plague businesses
with just a few clicks we can make your
bots work smarter for you
using ibm rpa in its ai powered
automation capabilities
thank you for watching if you have any
questions please drop us a line below
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more about ai-powered automation from
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