I'm thrilled to introduce our next speaker. Antique. Karjalainen Antti is
here to talk to us about hyperautomation as we heard from
Jen, some of the challenges of making decisions in
real time our that you're trying to simulate an integrate so much information from so many
sources and then apply context for that to make the organization
more agile, make the organization, more adaptive and optimize many
of the things that are going on on. She's been working on this problem for quite
a while.
And has a lot of interesting insights into how this stuff gets deployed and really how
to how to how to the sausage is made. Kind of it's nice to say,
oh you're going to get a magical decision and it will be right there. Will be optimal but
making that happen. Using modern text acts is a real challenge.
Our next speaker. Hi Auntie. Hey, thank you,
great. So I was I was before getting started. I was looking at
a lot of the attendees here on the session and just trying
to see what kind of backgrounds people have. And, and, you know,
it is, is great to have all the Automation and modern
technology available to us. But but many of you as
attendees will probably know what it means to actually be.
Deploy something in an Enterprise and what kind of struggle
that can be at times. Even the, you know, the best of
Technologies is no use, if you can put it into action. So
so I'm going to be talking about how we actually Master
hyperautomation, with the help of our ba and
an Opa might be familiar to a lot of you and I'm so, but
I'm going to go still briefly over. What is our PA
and where does it come from historically?
And then go into hyperautomation. How hard be a fits
into hyperautomation and then how the next generation of our
PA that we are deploying here at robocorp? For instance is helping you
actually enable hyperautomation in an Enterprise.
So, on the, on the basic level of be a is
all about DT dot workers. So replacing humans. In in it
tasks, doing monitor knows repetitive work, and,
and opa. As you might know, it can interact with any
application that you have, whether it's a desktop, but there's a browser
Vision API just like a human use of wood and even go beyond
that.
And you know, too many of Ip practitioners. RPA
is something that you know, has existed as
scripts for four decades before modern days. But now with
the Advent of local, it have really exploded and and
conquered the Enterprise.
But just to level set on a basic level, I'd
like to do a little little bit of an exercise here before I get into the
topic is type into the chat. Wait
for my cue to hit and and then let's all publish the
results. So I want you to think about what's the first thing that comes to mind. When you
think about our be and how would you describe our PA? I'll give
it a brief moment here.
And just type it into a stepson chat here. And when I
say go, you can hit enter. I hope
hope that'll work out. So so what's the first thing that
comes to your mind when you think about our be a, and
how would you describe our PA?
It's, you know, unless you've been exposed to it, you
might might not kind of get it
intuitively. How does it look like? I have an example for you here after
after we done. So maybe go ahead and press
enter publish your answers.
Glorified Excel macro like it. Automate manual key pressing
routine processing recreating group The workflows requiring. No
thought.
Great. Well, for those benefiting glorified Excel,
macros a good one for those benefit who
haven't seen it in action. I just grabbed really briefly 11
video example of what does that actually look like? So this is a bot
working on a Salesforce interface and this is from a real
proof of concept where the path had to work on an essay Salesforce instance, and then
go into sap,
And and, and do bunch of auditing. Basically comparing data between
these two systems, I think this is Sox compliance thing.
So you see a lot of screens moving really
fast and, and that's typically how our PA looks like. You know, it
really started out with, with this desktop automation, but it has
moved more into the back office nowadays. So, I'll just cover
as a practitioner coming from many, many years spent
in this industry.
How I see the history of our be a and ways coming from
and where it's going from occurring, going to now.
So, so basically, our PA started out as
this well, glorified desktop, or dimensional or Excel
macros, if you want to use that, it started out from,
from Fairly standard technology
that was kind of enhanced with local code and, and it was brought into the
Enterprise
Something where, you know, everyone will have this personal but
as an assistant to help you with this tedious manual tasks on your
up and it was framed as this magical AI. That will just simply learn what you're
doing and watch over you. And then you know automate your routine
work. And and in the in the beginning it was really focusing
on as we called attended use cases so something that you do on
your own desktop and it was sold the line of business
as
Such that was, you know, maybe 2016
starting starting forward from there, and then
after a few years of initial or be a success
in the end, the price, we started seeing a lot of consolidation
obviate had become the fastest growing segments in Enterprise software for
three years. Consecutive we started seeing consolidation in the
vendor space and and you know, people were thinking about what's next in
our be a, is it going to be
You know, or don't know, autonomous, digital workers,
cognitive automation intelligent automation, study, hearing
all these different phrases put together and then you had
Skeptics asking, hey, isn't this just putting a Band-Aid over a broken
process? Shouldn't be fixed underlying systems. Instead of automating
them from from the UI. And we started
seeing this emergence of centers of excellence around RPA. So
there was definitely a need for technology.
That would enable you to well take sap here in the demo video. For
instance, take your existing, it infrastructure and layer on top of that
automation that would kind of patch over missing
integration points and you know, few years forward from that
we are seeing that, you know, happy has been validated as
something. That pretty much, every Enterprise will identify
something that they must have. And, and we have
moved and shifted.
Way from the citizen developer phase where we had bought for every
employee. See your desktop assistant. It will learn into a
space where we are. We are close to a line to it
and and we are seeing that, okay, maybe our PA wasn't the glorified
desktop macro, or Excel macro, but it's
actually something that will work on tedious. High-volume
routine back office. Work loads like working with systems of
record.
Good erps, patient data record systems Etc and and
because we are kind of moving past the hype and into into a
phase where we have Enterprises deploying hundreds, and
thousands of Autobots churning through tens of thousands of
hours of work, every every month, producing immense
value. And it's not seeing as a Band-Aid anymore.
And so, of course, coming from a background of creating an
opa,
Technology and and, and seeing this trend play
out, you know, we are, we are in a space where we want to want to become
something of the next generation of PA. That's what we have, the gen2
RPA here as a title, but the main takeaway here is that
apia isn't that the Band-Aid technology anymore, but it's adopted by
pretty much any every Enterprise out there. And it's more aligned
nowadays with Artie than the line of business. So so
how does this
Whole work with hyperautomation then if you put it into that context
so hyperautomation was already defined in this earlier
talk here. But you know, Gardner definition would be that
it's, you know, business driven approach to
to rapidly identify better than and automate business processes and ID
process and it will include Technologies like AI
am l or PA as one and
and
I based automation but you typically see kind of classical
hyperautomation applications being things like intelligent document processing,
taking, unstructured data, and using OCR
and document understanding to structure eyes and
then putting that into action. Chatbots is a good example of
hyperautomation Technologies. So so
this is sort of an emerging picture that
be as a vendor has
have seen while talking with dozens of customers and and now touching
point is typically a VP in charge of in the price
Automation and and they will have these initiatives
from hyperautomation where they
acquired tools and Technologies and capabilities, but they
actually struggled to put that into action in into into
the existing it landscape. So, this is where our peer really from a
practitioner standpoint comes in
And it can act as the as the central backbone of
hyperautomation where you can take a intelligent document processing
capability and give like we'd like to say give
hands for the AI. So I allow the AI to touch
the existing Enterprise it infrastructure and
Landscape. So you have systems like sap or Oracle
for Erp, you might have, you know, a patient
data record system like it.
And other things that are maybe have
evolved over the last two decades and now you'll start
trying to layer on top of that. This hyperautomation strategy
and an RPA can act as the hands
for that AI to really bring it together and allow you to say
you have a chatbot interacting with your
customer in the front end. You might
this is a real world use.
In case you might need to create a new debit card for that customer, but your core
banking system is is really not meant to play
nice with a chatbot. So you'll take happy about take the initiative
from the chat Bots and then process it and return back to the chat
as you can actually really rapidly deploy these new capabilities into
your existing landscape by by the help of using the help of our PA.
And and so, so how the next generation of our PA comes into play? In this
equation, I already alluded to the Next Generation, but
how we see it is really happy shifting
towards it, coming away from the citizen
developer and line of business. Towards IP it
and and in the second generation of our baby, take a more
automation, develop a focused approach while maintaining the ease of
view.
With low code and as a rope as company robocorp, we
have be aligned with what we are dedicated to to build an
open-source standard for our PA. Maybe that's a, you know, topic
for later talk. But we want to create this open source
standard like technology stack into our p and then
allow it to better shift with sit next to it.
Bit processes like
You know, continuous integration and deployment, and that's something that
we call automation Ops in the industry. So
automation Ops is really Central to being able to operate
a robust function with
the center of excellence with our PA, so that you can actually rely on
these pots. It's not the sort of the brittle,
you know, glued on plaster like
band aid technology, but it's really
A robust way to build Integrations into existing it stack
and so automation Ops in the second generation of RPM. Now enables you to work
with things like get Version Control, full hoarded
ability, full logging of your but actions have devops like
routines for maintaining them and and really
going away from the shadow. It moniker that
had been given to 2R P, NY many it leaders used to
hate it.
And then reusing bought Assets in the form of
code is a big part of this as well.
So so
the first generation of our PA if you contrast it to
that, second generation started off with really, this sort of the
we're going to build a into end hyperautomation
platform and, you know, I think some of
them even even mentioned becoming the next sap.
But the but the way we see in the second generation of obviate the second
emerging technology stack is that rather than trying to build a
into--and wall to wall, covering in the price wide
hyperautomation platform, the next generation is going to be more in the
credible so so you're going to have a new and emerging
hyperautomation technology vendors. Like in this picture we have
Rothstein base64 as good examples of of
fast, moving fast, emerging new technologies.
We want to be able to integrate all of those through the
central backbone of our PA into the Enterprise it landscape. And
thus enable enable kind of faster move woman the into
into hyperautomation. So my view for
sure is that hyperautomation is going to be a multi vendor
approach rather than a single platform
that covers all of this. Just because the that the space is so fast moving
So, wrapping up here
as a summary RPA, while
it's considered as one of the sort of hyperautomation Technologies
next to things like chat Bots and AI am L
capabilities can really act as the as the
central backbone for for hyperautomation and and it should be
considered as such. And then for those
not nice,
He's deep into our PA every day. We've seen that it started out with this
glorified macro but then moved into something that's governed by a
center of excellence. That's aligned with it and actually can
be a fairly robust way to automate business processes across
an Enterprise. And, you know, we see that
hyperautomation is so fast moving space, that
there's not going to be a single vendor that will be able to cover all the
angles, all the needs and
So we're going to see in the next year's many many new vendors, come
Innovative automation capabilities and we want to be able to incorporate them
into a stack.
So, so that's that's my wrap up and I'll
open it up for questions. Thank you so much, talk to you, and
we are about to go into a break here, but if you have a couple of questions we can
feel them here. In looking in the event chat, we've had a few folks
talk about sort of hyperautomation and the contrast between the
Automation and Hyper and what makes it special
and I think you know, really what you were talking about
as a differentiator things like the ability to do auditability.
And to make it more of an operational process, instead of a shadow 80
issue is at the core of this. What do you see
as the big barriers to widespread open source
adoption of this as opposed to sort of Shadow it doing it in the
background with with cans and string? Well I mean
the way apia really exploded in the beginning was that it wasn't a line
with idea. It was this Shadow ID approach for you.
Just you know, popping a few licenses and you're all set and you start
building and then you end up with this Mick mishmash of
processes on automation. That doesn't really scale in any way,
it's harder to maintain every day and week and
so so I think I think that was necessary stage in the growth of our
PA, but as we as we go into this more
scaled up operation, we need to have better governments governance and
and all the controls.
Place. And when we talk about hyperautomation contrast to your sort of
regular day automation, I think it is. The speed of
adoption is what we are we are talking about is not
building a multi-year project to build a, you know,
end-to-end Enterprise automation platform is the speed of being able to adopt
automation Technologies and that's part of where our PA becomes.
The central backbone where it's faster to build Integrations to
our be a than,
That means even you know think about telling to
a CIO that we need an new sap project in terms of integration
c not going to make it most likely but if it's a
digital work or doing the integration, you'll be able to pull it off in a few
months. I'll drink you so much for being with us today. Really fascinating. Look at
how this is kind of gone from Skunk Works to the mainstream and
continues to do. So thank you so much.