January 31, 2023 • 35 mins
In this episode, Shail Khiyara (Founder VOCAL Council), Frank Casale (Founder The Institute for RPA & AI), Ian Barkin (Entrepreneur & Investor), and Andreas Welsch discuss the trends that will shape AI and intelligent automation in 2023. Frank shares how technologies adjacent to RPA deliver value. Shail points to multi-vendor environments that have historically grown. And Ian emphasizes the need to stay relevant in today's market. They provide valuable advice for listeners looking to maximize their investment in intelligent automation and who would like to understand how generative AI might shape the way we work already in the near future.
Key topics:
- What’s next for established RPA organizations
- How automation orchestration optimizes your operations
- Generative AI’s impact on the future of work
Listen to the full episode to hear how you can:
- Expect to see a tipping point from automating to emulating knowledge work
- Focus on people and culture for success
- Stay current on technologies and trends to future-proof your career
Watch this episode on YouTube: https://youtu.be/ll7XgaA_iJI
Questions or suggestions? Send me a Text Message.
***********
Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Andreas Welsch (00:00):
Today we'll talk about the trends that will shape
intelligent automation and AI in2023.
And who better to talk to aboutit than three experts in this
space?
Shail Khiyara, Frank Casale, andIan Barkin.
Hey everyone.
Thanks for joining.
Shail Khiyara (00:15):
Hey Andreas, thanks for having us here.
Frank Casale (00:17):
Happy to be here.
Andreas Welsch (00:19):
That's awesome.
Hey, I'm sure most people in theaudience might already know who
you are.
But why don't you introduceyourself real quick.
Shail Khiyara (00:26):
Sure.
My name is Shail Khiyara.
I've been in the automationspace for the last decade, have
had the opportunity to helpshape this market and work for
three leading automationproviders: Automation Anywhere,
Blue Prism, and UIPath.
I now run an independentcustomer think tank called VOCAL
which, stands for Voice ofCustomer in the Automation
(00:47):
Landscape.
And I've also joined and servedon the board of Turbotic and
joined Turbotic as a Presidentand COO.
Over to you, Frank.
Frank Casale (00:56):
Super.
Great to be here.
Appreciate the invite FrankCasale here, coming to you from
New York.
I guess most notably founder ofInstitute for Robotic Process
Automation and ai.
That's why I know most of thepeople in this space prior to
that founder of the OutsourcingInstitute.
Had a good run, maybe close totwo decades on in the labor
(01:17):
arbitrage space.
In the last decade, more in thekind of automated labor and
related.
So looking forward to today'sdiscussion.
Andreas Welsch (01:25):
Fantastic.
Great to have you with us andover to Ian.
Ian Barkin (01:28):
Thanks for having us.
Yep.
Ian Barkin.
I have spent a decade in the RPAintelligent automation space.
Learned about it actually firstand foremost from a conference
that Frank threw way back inlike 2013.
Co-founded Symphony Ventures,which is an RPA consultancy and
advisory, which I then sold afew years ago and spend my time
(01:49):
now creating LinkedIn Learningcourses, generally trying to
develop useful and educationalcontent and investing and
advising startups and disruptorsin the world of work.
Thanks for having us here.
Andreas Welsch (02:03):
Fantastic.
So I'm really looking forward toour conversation today and if
you're just joining the stream,drop a comment in the chat where
you are joining us from.
I'm really curious to see howglobal our audience is because
we have more than 930 peoplethat said: Hey I'm interested in
this show.
I want to watch it.
Awesome.
Two more quick things to sharewith you before we really get
(02:24):
started.
Don't forget to sign up for mynewsletter at
intelligencebriefing.com andstay up to date how you can run
AI and automation projectssuccessfully.
Now, we have plenty of time foryour questions as well today, so
please don't be shy and put themin the chat as well.
So let's finally jump right in.
First question for you, Frank.
I, know a lot of organizationshave implemented RPA over the
(02:47):
last couple of years and manyautomation leaders are now
wondering what's actually next?
So how can they build on theirexisting program or initiative
in 2023?
And what would you say are themajor trends they should look
for?
Frank Casale (03:02):
I would say if you've turned on your laptop at
all in the past 30 days, we allknow what's next.
It's ChatGPT, but we'll build upto that.
We'll build up to thatcrescendo.
From, where I sit, Andreas themajority of the people that have
invested in RPA over the pastdecade, are typically looking
(03:23):
for what I would say ROIamplifiers.
And it typically takes, I wouldsay about 12 months before an
enterprise user realizes thatthey need some adjacent
technology.
In the bulk of what I'm seeingin our space are things like IDP
and conversational AI as twokind of big plays that are great
(03:46):
bolt-ons.
It's not a rip and replace,either one of them are overlays.
And the majority of RPA usersthat I see that are getting real
return on investment from theRPA investment is not directly
through RPAs, a standalone.
It's really more through theseadjacent technologies that
suddenly begin to have muchgreater impact.
(04:08):
So I'll stop there.
Not to take up too much time.
But that's what we're seeing.
A lot of activity in the IDPspace.
Conversational AI,conversational business apps.
I think that's where the actionis right now.
Andreas Welsch (04:21):
Fantastic.
Thanks.
Anybody else wanna build onthat?
Ian Barkin (04:24):
I would add the process stuff, process mining,
process discovery, task mining,all of those the gateways into
helping enterprises identifywhere to apply all the rest of
the stuff.
Hopefully with a healthy focuson fixing and simplifying
processes before just throwingtech at it.
Andreas Welsch (04:43):
How, much do you see leaders and companies a
actually do this?
We love to think about it asthis ideal typical stage of,
Hey, first you analyze, then youfigure out what you can
automate, and then you buildsomething top.
How do you see this happentoday?
Is this really how you see itcan happen?
Frank Casale (05:03):
I guess it's tough to go broad brush strokes and I
think my colleagues would agree.
There's a very small and activeportion, I would say, of the
community that continues toinvest and push the envelope
that's looking for, I would sayleapfrog innovation.
And those are very muchscreening in opportunities and
with good, top-down support andinvestment.
(05:25):
I would say both in dollars andI would say in mindset if you
will.
But on the other end of thespectrum we're seeing a sizable
percentage of people that are abit disenamored with with RPA.
So they're just sitting therewondering what and maybe what
did they do wrong?
(05:45):
Who explained what incorrectlyor over-hyped what on the buy or
sell or advisory side, andeverybody's pointing to the
other person.
And so those guys are goingnowhere.
But I'm seeing kind of twoextremes.
Shail Khiyara (06:00):
I tend to agree with with you, Frank.
I think the"just do it"automation era has to a large
extent slowed down and we'restarting to see a lot more
emphasis on value.
Frank mentioned ROI earlier.
It's ROI and it's what kind ofcustomer experience are you
driving?
(06:20):
What kind of revenue enhancementare you driving through
automation?
So automation value is becomingmore and more prominent in the
decision making for automationtechnologies.
And there are several of them.
Ian Barkin (06:32):
Yeah.
I would concur.
I know Andreas, you want somemore drama, but I I would concur
with what we just said.
I think my biggestdisappointment, the RPA space
specifically, has meant a lot tome.
I built a team there, succeededin that space.
I think globally we haveabsolutely failed at achieving
(06:53):
the full potential and impact ofthat one technology.
And I think we're on the path tofail at applying all of the
other augmenting technologiesthat Frank just mentioned
because enterprises are goingabout it in the wrong way,
right?
They're fascinated by the tech.
They are not putting in thefoundation stones of solid
enterprise change with a visionand a mission and communications
(07:17):
and buy-in and all that otherstuff.
And so it's frankly a littledisappointing.
I think the potential is huge.
The actual achieved outcomesthus far are frankly pathetic.
And it's up to folks like us onthis call to try to educate
everybody into a pragmatic,methodical, mature set of
(07:41):
activities around understandingand adapting and applying all of
the tech available today.
Andreas Welsch (07:48):
Thank you for sharing that and for building on
each other's answer.
So I'm having a quick look atthe chat here.
Boy, that's really global.
For those of you who have joinedfrom.
Lebanon to Morocco, to the U.K.,Austria, Italy, the U.S.
So that's really awesome.
(08:08):
Thank you for, joining.
Let's, take one question fromthe chat.
Maya is asking what are themajor misconceptions companies
had about RPA and where was thedisconnect?
Ian Barkin (08:21):
This is so easy a business analyst can do it" was
the narrative that was dumpedinto the market for years.
And when you tell people it'seasy, they prepare for easy
voyages which means that theyunder prepare for the real
voyage ahead.
And therefore they didn'teducate broadly enough.
They didn't allocate enoughfunds, they didn't put together
(08:42):
the right SLAs and objectivemeasurements to decide what good
is early stage, mid and laterstage in their maturity and
scalability.
And so I think you end up with abunch of abandoned POCs and
pilots that prove the point, butnever really embedded in a
habit.
Frank Casale (09:02):
Yeah, if I could pile on.
As I saw it, and I've beeninvolved almost since the
beginning, I think there werethings that people should have
known and I would also say therewere things that none of us
knew, but we learned over time.
What we should have known is, atleast, I felt was fairly basic,
is when somebody sets out toquote unquote increased
(09:23):
productivity.
To this day I hear, and mycolleagues may agree or
disagree, but if, I'm pulledinto a discussion and the
mission is increasedproductivity and I can't get
three people in thatorganization agree on what that
means, I know that the businesscase is dead.
So, the more specific and themore definable, the more
(09:46):
measurable an outcome is, thenyou could look and say, okay,
fine, does this technology getus there?
And I would say in many casesRPA may not.
Cuz at the end of the day it isnon-intelligent automation of a
task in many cases a subtask.
So how far does that get ifwe're able to free up 10% of
(10:06):
Ian's time each day by somenifty tool, cuz we're automating
his travel expenses reporting.
And how do we know?
How does he know?
How do we know if that increaseshis productivity?
We'll never be able to connectthe dots as I see it.
I don't think I'm being apessimist.
I think I'm just being apragmatist.
What most of us didn't knowgoing into this is even if you
(10:28):
ran the numbers and it lookedlike it worked, most of us
didn't anticipate the cost onthe back end to manage and
repair these bots.
I don't know, maybe Ian andShail, maybe you guys sensed
that early on.
That certain was a surprise tome and many folks that I knew
that you say.
Wow.
And, I would argue maybe not toodissimilar from those of us that
came from the outsourcing spacewhere we thought that in the
(10:52):
early days in the nineties wherewe were doing outsourcing deals
and I was involved with ahandful of really big ones where
the assumption was, okay, we ranthe math, ink the deal.
Let's go, have a steak dinnertonight and we're looking good.
And suddenly we say, wow, we'regonna need a team of 3, 4, 6
people in maybe two, threedifferent cities to manage this
(11:12):
thing.
And then suddenly that kind ofthe numbers got funky from that
point forward.
Yeah.
Andreas Welsch (11:19):
Perfect.
Maybe let's move on to the nextquestion.
Thank you both for sharing your,perspectives.
So if I put my old IT hat backon for a second and it of goes
in the direction also what Ianand Frank have said.
I think there are a lot oflandscapes that have evolved
over time, right?
Maybe you've integrated anacquisition or onboarded another
(11:42):
division that's on differentplatform and you inevitably get
to a multi-vendor operation.
From an IT point of view I knowthat's never really ideal,
because you're trying tostandardize much as you can.
So I'm wondering is thismulti-vendor automation
landscape really the newreality?
And how can automation leadersoptimize their footprint?
Shail Khiyara (12:03):
No, that's a good question.
As you heard Frank and Ian talkabout the fact that there are
multiple technologies inautomation out there, right?
There's IDP, process mining,machine learning capabilities,
cognitive X, Y, Z, and analyticsin addition to the RPA
technology that we're talkingabout.
So what I'm hearing fromcustomers is that this
(12:25):
multi-vendor landscape and thedesire to have multiple
technologies to do variousdifferent things under the
umbrella of enterpriseautomation is inevitable.
There are about 40 to 45,000customers using RPA across the
globe.
Today, 40 to 45% of them areusing multi vendors.
And that is continuing to growas we see commoditization,
(12:47):
particularly of the attendedautomation capabilities with
some of the new large entrantsthat have entered into this
space.
What's really interesting isthat over the last, I would say
three years or so, about 11billion of investment has gone
into RPA.
A lot of it has gone into thethree major players and then the
(13:08):
long, tail of 65 other playersthat exist in the market.
However, if you look at theacquisitions over the last two
years, 14 acquisitions totallingabout one and a half billion
dollars.
So 10 billion gone into the coreRPA vendors, one and a half
billion dollars gone intoacquiring 14 companies for large
(13:30):
entrants like Microsoft, IBM,SAP, and various others to enter
into this market, starting tocommoditize attended automation.
So with that kind of a dynamic,there are a collection of
technologies customers areusing.
They're struggling with how tostitch these technologies
together because the corefundamental focus of RPA vendors
(13:53):
has always been to sell bots.
The orchestrators are lackinginnovation, in my opinion.
And because of that gap,customers are struggling with,
if I have multiple vendors, howdo I manage these vendors?
Where's the single pane of glassto be able to manage the entire
lifecycle of automation?
(14:14):
Andreas, if you walk into aCFO's office today, she cannot
tell you that she can't give youfinancial information because
she doesn't have a system forit.
She does.
If you walk into a CRO's office,he can't tell you that he won't
give you sales forecast.
He has a system for it.
It's a CRM system.
If you walk into a CoE today,not all of them, but a few of
(14:34):
them, you do find Excelspreadsheets, SharePoints
PowerPoints, SMS messages tomanage the entire lifecycle of
automation to manage all thesemultitude of technologies that
exist today.
And that is a significantchallenge.
And we're starting to see theemergence like we saw in the
network world, like we saw inthe cloud world.
(14:55):
Where we saw networkoptimization tools, cloud
optimization tools emerge.
We're starting to see theemergence of these single pane
of glass automation optimizationtools.
There's still a long way to goin this market, but I think
coming back to your question.
Yes, I think the multi-vendorlandscape is inevitable.
(15:16):
Ian, Frank what are yourthoughts.
Frank Casale (15:19):
Yeah, I'm happy to weigh in on this.
My feeling is if you really wantto de-risk it and have one neck
to choke, then outsource it.
It's pretty straightforward as Isee it.
However, realize there's no riskfree path, so you outsource it.
You have predictability there,but you're giving a margin and
(15:41):
you're giving up potentiallybest in class solution.
But that's the way to go.
On the other hand, if you wantbest in class and you have a
comfort level that your IT teamhas some experience cuz you
really want to get beyond themlearning this on your dime, if
you will.
If you're the internal clientand, I would say the majority of
(16:02):
global 2000 have some experiencehere, then you go best in class
and maybe bring in ideally thethird party just for success
insurance and build somethingawesome.
But even then now you haveintegration, creates
uncertainty.
And I would assure you, whateveryou like this year, you will not
(16:23):
like next year.
It is a bit of a dilemma.
And then again, looking where weare now, and I promise I'm not
getting a commission, that eachtime I say ChatGPT, somebody
sends me$50.
If you look at where we are now,we're on the precipice of the
whole game changing so, we justneed to be aware of it.
It's still young and it's notenterprise ready.
(16:45):
It's very cool.
It's very interesting.
I believe it's likely to changea whole bunch of things.
That's my understatement, butnonetheless I don't see an
enterprise ready.
One last thing I'd like to say.
When we think about the buyers,obviously there's a lot of
different ways to define large,medium and, small, et cetera.
But what I've seen, and I thinkmany of you have seen is, a
(17:09):
significant difference intraditional companies versus
digital native organizations ofhow they do this.
So I would caution against thebig kind of macro view of the
market because the way I wouldapproach a strategy at JP Morgan
(17:30):
and the way that would be or notbe embraced would be totally
different the way I wouldapproach it at Spotify, a place
that was born in the cloud,digitally native.
In the latter scenario, which issmall, digital, native,
non-regulated industry, that'sgonna be a shorter cycle, less
landmines.
We're just gonna be moving andgrooving.
(17:51):
It's gonna be a lot faster.
You get involved with a big bankor an insurance company, the
ultimate impact could besignificant, but it will be
painful.
I know I have battle scars doingthose deals, and I know a couple
my colleagues do.
Andreas Welsch (18:08):
Awesome.
Anybody else wanna add Ian?
Ian Barkin (18:10):
Yeah.
This dates us all, I think.
But, that conference I mentionedthat Frank held, that introduced
me to RPA was an outsourcinginstitute conference, not an RPA
conference.
And RPA came out of theoutsourcing industry because we
were using whatevercapabilities, tools, resources
we had available to us to makean outcome for our client.
In that case it wastransactional processing at a
(18:33):
more affordable rate.
We happened to use arbitrage, sowe went offshore and used people
in places like India.
Then RPA came along and it itmatched that to some degree cuz
it enables us to continue to dothat process transaction
activity.
But with a different agent.
It wasn't the Indian, it was arobot.
(18:53):
So we said it would happen thatway, but then we got too
fascinated by the tech itselfand enterprises started to be
told that they could do it, sothat you don't need a third
party partner who happens to bean expert in this.
You can just fire up your HRteam and ask them to spend their
evenings and weekends digitizingthe tasks they worked on that
did not work.
So to Frank's point working withan expert I think will more
(19:17):
likely be the path to successhere, but it rests on all of us
to figure out a little bit moremodern, interesting
collaborative business modelsand collaborative structures so
that yeah, you're gonna paysomebody.
So there will be some margin,but I'll tell you that margin
will be a function of all of thepain, technical debt and waste
(19:40):
that's happened in enterprisesin the last 10 years, trying to
figure out and deploy the RPA,IDP, process mining,
conversational AI, et cetera,that they're tinkering with
right now.
So I think the future is somesort of hybrid where you're
working with experts, stillemploying the capabilities in
the subject matter experts in.
Maybe to scout and find goodareas to deploy this stuff.
(20:03):
But that's how we're gonnareally make the most of the
tools available to us.
And the need, the big enterpriseis not the digital native ones
that can just start from scratchand be, more be more structured
and, digital from the beginning.
That's, the way we all need togo.
Andreas Welsch (20:20):
Fantastic.
Thanks.
I think well rounded answer andgood to see the different
perspectives here from you.
So if I take a look at the chat,there are some questions about
AI.
For example, Michael is asking: Will ChatGPT and its equal, but (20:32):
undefined
opposite generative AIdetection, become a new market
category, if not in 23, then in25?
Or Christine is asking (20:43):
Do you believe that more attention
towards data monetization inindividual organizations will be
the trend that will shape AI andautomation in 2023?
I think personally I have anopinion on the generative AI
topic and I believe at least forthe time being that we're, still
(21:05):
as an industry, as leaders,figuring out where can we
actually use this and where canwe use it in a way that it makes
sense.
If, we on one hand haveproprietary or models.
On the other hand, we have opensource models.
If we use the ones that areproprietary like CHatGPT, we
don't really know what data hasgone into it.
And you see some discussion andconcerns, for example, over at
(21:29):
Amazon.
Hey, this thing spits out codethat looks suspiciously familiar
to our own IP.
Or questions around informationsecurity more broadly.
Please don't copy confidentialinformation into this chat
prompt, or are the answers thatit generates really reliable, or
do they just sound plausible?
So I think there's still somethings that the industry needs
(21:51):
to figure out.
And, similar I think also to,RPA and, other AI scenarios.
We might want to have the humanin the loop for some time to
review it.
It's good, at least at themoment, right?
In the scenarios we see, and atthe moment it's good as a
kickstart for ideas and to getcreativity flowing.
Maybe to reword or rephrase afew things.
(22:14):
And, I'm sure you know this.
We'll, see a thousand more waysto use this.
I don't think its own category.
I think much AI it'll help a newkind of application, be powered
and, deliver more.
And I think also on the otherside, organizations looking into
monetization, I think there area few that they're doing this or
(22:38):
will be doing this and will bedoing it well.
But also depends on theunderlying architecture.
Do you have the data strategy,the processes, things in place
to be able to do that.
And maybe part of that goes backto digital natives and
established companies as wellwho might be able to do it
easier if you're starting new inthe cloud, relatively new
compared to having legacy andhistory.
(23:01):
But I'm curious what do youthink?
What are you seeing there?
Maybe just briefly.
We have a few more minutesbefore we wrap up and wanna get
to Ian.
And, the question I have for youas well.
Frank Casale (23:11):
Okay.
May I, in a friendly way,disagree with you with
opponents?
Andreas Welsch (23:15):
Sure.
I'm more optimistic than youseem to be, Andreas with regard
to ChatGPT.
And I think it'll besignificant, I think from a
standpoint of category.
I recommend that we all thinkabout less about what it is and
we focus more about what itdoes, which you alluded to.
(23:35):
I think it's all about use case.
And I think there are people onthis line now that have ideas
for use cases, and I would saythe right use case with the
right commercial strategy isyour fast track to independence.
I think there'll be billions ofdollars made.
Some people will make millions,some people will make billions
for anyone.
And the barrier to entry is verylow.
(23:59):
Which is it?
Okay.
Double-edged sword.
But still the, opportunity forsomeone now with an idea,
getting a whole of technologythat is cheaper than cheap.
Why?
Because it's free it issignificant.
So I've been watching this veryclosely.
I've been fortunate enough,maybe the older guy on the panel
here, I've been through a coupleof cycles.
This is significant.
(24:19):
However yes, there will be a tonof lawsuits.
I think IP becomes debated.
I think it becomes very, veryfuzzy whether you're in the
insurance game or a collegestudent doing a paper.
I think that becomes very fuzzy.
However literally this weekendyou could launch a business and
go.
There are tremendousopportunities.
(24:41):
One quick thing, if I may, ondata monetization.
From what I've seen, thediscussions have been amazing.
I've seen very amazing stories.
I think for the average company,if you're a bank or an insurance
company or in telecommunicationsor you're a media company, the
(25:02):
odds of you investing the time,by the way, you may have a
billion dollars worth of IP dataand yes, data is the new oil,
blah, blah, blah.
I haven't seen it.
I haven't seen it yet.
I think it's likely gonna be anindependent organization.
Shail Khiyara (25:17):
Look I'm very bullish on what you just said,
Frank.
Very bullish on generative AI asa whole.
I wouldn't say just focusing onChatGPT, but if you look at the
marginal cost of energy, it'sapproaching zero.
That's going to happen to theintelligence as well.
Marginal cost of intelligenceapproaches zero, and it's
happening at an extremely fastpace.
(25:37):
If you look at Transformers,when you look at BERT back in
2017 to ChatGPT now in less thanslightly more than five years.
The next five years, you'regoing to see transformers even
evolve even further.
Where prompts or questions arenot going to be the key focus
areas anymore.
It's going to be theconversation that you and I are
(25:58):
having right now that is goingto be prevalent in terms of how
you interface with thesesystems.
So I do think the opportunity isimmense.
I do think that there issignificantly fast-paced
technological innovation that isgoing on.
To Frank's earlier point, whatyou may like today, you may not
like tomorrow.
Same applies to ChatGPT as well.
(26:19):
You may like it today, butthere's something new coming
tomorrow very quickly.
That's one aspect of it.
The other aspect of it is Ithink it's going to change the
structure of interfaces insociety as we know it in many
ways.
Frank talked about lawsuits.
There's already discussionsabout how to use this or not to
use this in schools.
(26:40):
There are already discussionsabout how, who owns digital art
as an example.
So these are new questions thatare coming forth that we have
not dealt with before as asociety.
So that's going to be a veryinteresting change across the
world.
And by the way, ChatGPT, rightnow, the interface is English.
Wait till that changes.
Andreas Welsch (26:59):
Excellent point.
Maybe Ian I'll go over to youfor the next question that we
have, so we can finish somewhatin time.
But I really appreciate the goodconversation and discussion we
are having here.
Also the questions in the chatgo in that direction if there
are these huge shifts and thisnew momentum for automation, for
(27:21):
AI.
I know you often post about thisand call it the workers of the
future in the future of work.
So I'm, wondering what does itmean?
What do you mean by that andwhat does it take to be a future
worker?
Ian Barkin (27:34):
Sure.
Ultimately the divide of IT andbusiness has held back true
evolution just cuz businessknows what they need and IT
knows what they can build andwhat they have.
And so the last 10 years we'veaspired to bring those groups
together or at least empowerbusiness to run a gray rogue IT
operation where they can getdone what they think they need
(27:55):
to get done in the future.
Because every company is asoftware company.
We all need to evolve ourskills, and enterprises need to
realize that.
Cuz as we've just discussed,there'll always be a new tool.
There always will be.
Ultimately we need to build aflexibility and a foundational
digital literacy and digitalquotient within enterprises so
(28:18):
that we can assess incorporateand apply whatever comes next.
If it's ChatGPT or if it's RPAor whatever else.
And, then we need to be able toadapt the organization design
really good incentive structuresand initiatives to make the most
of it.
Because right now, in RPA, weare hoping business could do it.
(28:41):
It's a little hard.
We got it doing it, but we don'thave enough IT folks.
We don't have enough developersin the world to build all of the
apps and the configurations thatbusinesses believe they need.
And so you're leaning on yourcitizenry to do that.
And yet the citizens aren'tnecessarily.
Skilled up yet to be able to dothat.
So most of the citizendevelopment initiatives that are
(29:03):
happening in the world arepilots.
They're small in scale andimpact.
And so over time, foundation ofdigital literacy, we need to
create a better organizationalstructure with incentives
because the smart people, theones who actually know how to do
this, are using it to digitizetheir jobs and then just go play
video games for half a week.
(29:25):
So those are the ones who havethe moonlighting and the gigs
and the side hustles.
So they don't have any incentiveto, to share what they've, what
their ingenuity and theirability have allowed them to
develop for their enterprise,cuz what's in it for them.
There are a lot of pieces thatneed to be worked out to truly
harness the ingenuity ofeveryone within an organization.
(29:47):
Make them capable of adoptingthe tools that come out as they
come out and then to have thesemeaningful discussions about how
we're gonna experiment andimprove out their value and
apply them in a broader scale.
Andreas Welsch (29:59):
Perfect.
Thank you.
That's awesome.
I think that's a really good wayto also end today's session on.
But before we do, I waswondering if you can each
summarize one key takeaway forour audience today.
Starting with Frank and to Shailand to Ian again.
Frank Casale (30:17):
Wow, that's tough.
I believe I coined a term abouta decade ago digital labor and I
for years kept thinking thatwe're almost there.
RPA?
Nope.
Intelligent automation.
Close.
Maybe full on AI.
Not sure.
I believe we're approaching thattipping point where intelligent
(30:39):
technology will shift fromassisting knowledge workers to
emulating knowledge workers.
Now that's exciting and alsofairly scary.
So there will be people thatwould be able to find
opportunity here.
But regardless of who you are,buyer, seller, advisor,
entrepreneur, wanna beentrepreneur I would recommend
(31:02):
that you think about thefollowing and I jotted them down
because I think it's importantfor each of us as people,
workers, professionals, and youhave a life, you have a family,
I would say.
To power through the change.
Most relationships win.
Biggest network helps a mindsettoward continuous learning.
(31:25):
You can't, if you get stuck withthe old dog and the new tricks,
you're stuck.
And last, by not least,financial runway could be a good
amount of turbulence dependingon who you are.
I think at that point you're,you have the best odds of
powering.
Andreas Welsch (31:39):
Fantastic.
Thanks.
Going over to Shail.
Shail Khiyara (31:42):
Yeah, look, there are two things that make up
organization.
It's people and everything else,right?
So I would say that it the sameapplies to automation as well.
Automation, it's not the botsdriving your automation.
It's actually the peopleinvolved in it and the ecosystem
around it.
So my key takeaway is that focuson the software aspects of
(32:03):
automation, which is theculture.
How do you create a borderlessorganization?
How do you create a no fearzone?
How do you actually empowerpeople to drive automation
inside your organizations?
The last thing I wanna say isthat look I just want to express
my gratitude sitting herelistening to industry experts
who.
(32:24):
In many ways helped educate themarket, Frank through IRPAA and
other means, Ian, throughLinkedIn Learning and, other
means as well.
And Andreas, what you're doingas well.
So I'd encourage the audience asa takeaways, follow them.
There's a lot to be learnedhere.
Andreas Welsch (32:41):
Perfect.
Thank you.
And very nicely put.
Hard to disagree with that one.
So over to Ian.
Ian Barkin (32:48):
And hard to follow those two guys.
Man, what the hell am I leftwith saying?
I agree with everything thatFrank and Shail just said.
It is about people.
It's about that commitment todigital literacy.
It's a more exciting future nowthan it was 10 years ago when I
started playing with this stuff.
It's certainly more confusingbut it's just because we've got
(33:11):
more tools and more players andmore enthusiasm in the space.
So, you really owe it toyourself to stay plugged in and
educate.
As the guys just said before.
The group on this call reallyhas committed and dedicated a
lot of their energy to doingthat.
To exploring for their ownunderstanding and then sharing
for the understanding and thedevelopment and betterment of
(33:33):
our communities.
Follow Shail, follow Frank,follow Andreas.
Those guys are putting outincredible content.
And thanks for having us,Andreas.
This is a great discussion.
Really appreciate you puttingthis together.
Frank Casale (33:45):
Thanks, Andreas.
Andreas Welsch (33:47):
Yeah, so thanks for joining us.
When we started this, we startedon RPA.
I wasn't quite sure how far intointo AI we would get.
And here we were talking aboutgenerative AI and ChatGPT.
So I think, we really coveredall the major trends and really
appreciate you sharing yourexpertise with us and the
community here as well.
(34:08):
Yeah, so I think the only thingleft to do then is to close us
out.
Thanks Shail, Frank and Ian forjoining.
Today we'll talk about the trends that will shape
intelligent automation and AI in2023.
And who better to talk to aboutit than three experts in this
space?
Shail Khiyara, Frank Casale, andIan Barkin.
Hey everyone.
Thanks for joining.
Shail Khiyara (00:15):
Hey Andreas, thanks for having us here.
Frank Casale (00:17):
Happy to be here.
Andreas Welsch (00:19):
That's awesome.
Hey, I'm sure most people in theaudience might already know who
you are.
But why don't you introduceyourself real quick.
Shail Khiyara (00:26):
Sure.
My name is Shail Khiyara.
I've been in the automationspace for the last decade, have
had the opportunity to helpshape this market and work for
three leading automationproviders: Automation Anywhere,
Blue Prism, and UIPath.
I now run an independentcustomer think tank called VOCAL
which, stands for Voice ofCustomer in the Automation
(00:47):
Landscape.
And I've also joined and servedon the board of Turbotic and
joined Turbotic as a Presidentand COO.
Over to you, Frank.
Frank Casale (00:56):
Super.
Great to be here.
Appreciate the invite FrankCasale here, coming to you from
New York.
I guess most notably founder ofInstitute for Robotic Process
Automation and ai.
That's why I know most of thepeople in this space prior to
that founder of the OutsourcingInstitute.
Had a good run, maybe close totwo decades on in the labor
(01:17):
arbitrage space.
In the last decade, more in thekind of automated labor and
related.
So looking forward to today'sdiscussion.
Andreas Welsch (01:25):
Fantastic.
Great to have you with us andover to Ian.
Ian Barkin (01:28):
Thanks for having us.
Yep.
Ian Barkin.
I have spent a decade in the RPAintelligent automation space.
Learned about it actually firstand foremost from a conference
that Frank threw way back inlike 2013.
Co-founded Symphony Ventures,which is an RPA consultancy and
advisory, which I then sold afew years ago and spend my time
(01:49):
now creating LinkedIn Learningcourses, generally trying to
develop useful and educationalcontent and investing and
advising startups and disruptorsin the world of work.
Thanks for having us here.
Andreas Welsch (02:03):
Fantastic.
So I'm really looking forward toour conversation today and if
you're just joining the stream,drop a comment in the chat where
you are joining us from.
I'm really curious to see howglobal our audience is because
we have more than 930 peoplethat said: Hey I'm interested in
this show.
I want to watch it.
Awesome.
Two more quick things to sharewith you before we really get
(02:24):
started.
Don't forget to sign up for mynewsletter at
intelligencebriefing.com andstay up to date how you can run
AI and automation projectssuccessfully.
Now, we have plenty of time foryour questions as well today, so
please don't be shy and put themin the chat as well.
So let's finally jump right in.
First question for you, Frank.
I, know a lot of organizationshave implemented RPA over the
(02:47):
last couple of years and manyautomation leaders are now
wondering what's actually next?
So how can they build on theirexisting program or initiative
in 2023?
And what would you say are themajor trends they should look
for?
Frank Casale (03:02):
I would say if you've turned on your laptop at
all in the past 30 days, we allknow what's next.
It's ChatGPT, but we'll build upto that.
We'll build up to thatcrescendo.
From, where I sit, Andreas themajority of the people that have
invested in RPA over the pastdecade, are typically looking
(03:23):
for what I would say ROIamplifiers.
And it typically takes, I wouldsay about 12 months before an
enterprise user realizes thatthey need some adjacent
technology.
In the bulk of what I'm seeingin our space are things like IDP
and conversational AI as twokind of big plays that are great
(03:46):
bolt-ons.
It's not a rip and replace,either one of them are overlays.
And the majority of RPA usersthat I see that are getting real
return on investment from theRPA investment is not directly
through RPAs, a standalone.
It's really more through theseadjacent technologies that
suddenly begin to have muchgreater impact.
(04:08):
So I'll stop there.
Not to take up too much time.
But that's what we're seeing.
A lot of activity in the IDPspace.
Conversational AI,conversational business apps.
I think that's where the actionis right now.
Andreas Welsch (04:21):
Fantastic.
Thanks.
Anybody else wanna build onthat?
Ian Barkin (04:24):
I would add the process stuff, process mining,
process discovery, task mining,all of those the gateways into
helping enterprises identifywhere to apply all the rest of
the stuff.
Hopefully with a healthy focuson fixing and simplifying
processes before just throwingtech at it.
Andreas Welsch (04:43):
How, much do you see leaders and companies a
actually do this?
We love to think about it asthis ideal typical stage of,
Hey, first you analyze, then youfigure out what you can
automate, and then you buildsomething top.
How do you see this happentoday?
Is this really how you see itcan happen?
Frank Casale (05:03):
I guess it's tough to go broad brush strokes and I
think my colleagues would agree.
There's a very small and activeportion, I would say, of the
community that continues toinvest and push the envelope
that's looking for, I would sayleapfrog innovation.
And those are very muchscreening in opportunities and
with good, top-down support andinvestment.
(05:25):
I would say both in dollars andI would say in mindset if you
will.
But on the other end of thespectrum we're seeing a sizable
percentage of people that are abit disenamored with with RPA.
So they're just sitting therewondering what and maybe what
did they do wrong?
(05:45):
Who explained what incorrectlyor over-hyped what on the buy or
sell or advisory side, andeverybody's pointing to the
other person.
And so those guys are goingnowhere.
But I'm seeing kind of twoextremes.
Shail Khiyara (06:00):
I tend to agree with with you, Frank.
I think the"just do it"automation era has to a large
extent slowed down and we'restarting to see a lot more
emphasis on value.
Frank mentioned ROI earlier.
It's ROI and it's what kind ofcustomer experience are you
driving?
(06:20):
What kind of revenue enhancementare you driving through
automation?
So automation value is becomingmore and more prominent in the
decision making for automationtechnologies.
And there are several of them.
Ian Barkin (06:32):
Yeah.
I would concur.
I know Andreas, you want somemore drama, but I I would concur
with what we just said.
I think my biggestdisappointment, the RPA space
specifically, has meant a lot tome.
I built a team there, succeededin that space.
I think globally we haveabsolutely failed at achieving
(06:53):
the full potential and impact ofthat one technology.
And I think we're on the path tofail at applying all of the
other augmenting technologiesthat Frank just mentioned
because enterprises are goingabout it in the wrong way,
right?
They're fascinated by the tech.
They are not putting in thefoundation stones of solid
enterprise change with a visionand a mission and communications
(07:17):
and buy-in and all that otherstuff.
And so it's frankly a littledisappointing.
I think the potential is huge.
The actual achieved outcomesthus far are frankly pathetic.
And it's up to folks like us onthis call to try to educate
everybody into a pragmatic,methodical, mature set of
(07:41):
activities around understandingand adapting and applying all of
the tech available today.
Andreas Welsch (07:48):
Thank you for sharing that and for building on
each other's answer.
So I'm having a quick look atthe chat here.
Boy, that's really global.
For those of you who have joinedfrom.
Lebanon to Morocco, to the U.K.,Austria, Italy, the U.S.
So that's really awesome.
(08:08):
Thank you for, joining.
Let's, take one question fromthe chat.
Maya is asking what are themajor misconceptions companies
had about RPA and where was thedisconnect?
Ian Barkin (08:21):
This is so easy a business analyst can do it" was
the narrative that was dumpedinto the market for years.
And when you tell people it'seasy, they prepare for easy
voyages which means that theyunder prepare for the real
voyage ahead.
And therefore they didn'teducate broadly enough.
They didn't allocate enoughfunds, they didn't put together
(08:42):
the right SLAs and objectivemeasurements to decide what good
is early stage, mid and laterstage in their maturity and
scalability.
And so I think you end up with abunch of abandoned POCs and
pilots that prove the point, butnever really embedded in a
habit.
Frank Casale (09:02):
Yeah, if I could pile on.
As I saw it, and I've beeninvolved almost since the
beginning, I think there werethings that people should have
known and I would also say therewere things that none of us
knew, but we learned over time.
What we should have known is, atleast, I felt was fairly basic,
is when somebody sets out toquote unquote increased
(09:23):
productivity.
To this day I hear, and mycolleagues may agree or
disagree, but if, I'm pulledinto a discussion and the
mission is increasedproductivity and I can't get
three people in thatorganization agree on what that
means, I know that the businesscase is dead.
So, the more specific and themore definable, the more
(09:46):
measurable an outcome is, thenyou could look and say, okay,
fine, does this technology getus there?
And I would say in many casesRPA may not.
Cuz at the end of the day it isnon-intelligent automation of a
task in many cases a subtask.
So how far does that get ifwe're able to free up 10% of
(10:06):
Ian's time each day by somenifty tool, cuz we're automating
his travel expenses reporting.
And how do we know?
How does he know?
How do we know if that increaseshis productivity?
We'll never be able to connectthe dots as I see it.
I don't think I'm being apessimist.
I think I'm just being apragmatist.
What most of us didn't knowgoing into this is even if you
(10:28):
ran the numbers and it lookedlike it worked, most of us
didn't anticipate the cost onthe back end to manage and
repair these bots.
I don't know, maybe Ian andShail, maybe you guys sensed
that early on.
That certain was a surprise tome and many folks that I knew
that you say.
Wow.
And, I would argue maybe not toodissimilar from those of us that
came from the outsourcing spacewhere we thought that in the
(10:52):
early days in the nineties wherewe were doing outsourcing deals
and I was involved with ahandful of really big ones where
the assumption was, okay, we ranthe math, ink the deal.
Let's go, have a steak dinnertonight and we're looking good.
And suddenly we say, wow, we'regonna need a team of 3, 4, 6
people in maybe two, threedifferent cities to manage this
(11:12):
thing.
And then suddenly that kind ofthe numbers got funky from that
point forward.
Yeah.
Andreas Welsch (11:19):
Perfect.
Maybe let's move on to the nextquestion.
Thank you both for sharing your,perspectives.
So if I put my old IT hat backon for a second and it of goes
in the direction also what Ianand Frank have said.
I think there are a lot oflandscapes that have evolved
over time, right?
Maybe you've integrated anacquisition or onboarded another
(11:42):
division that's on differentplatform and you inevitably get
to a multi-vendor operation.
From an IT point of view I knowthat's never really ideal,
because you're trying tostandardize much as you can.
So I'm wondering is thismulti-vendor automation
landscape really the newreality?
And how can automation leadersoptimize their footprint?
Shail Khiyara (12:03):
No, that's a good question.
As you heard Frank and Ian talkabout the fact that there are
multiple technologies inautomation out there, right?
There's IDP, process mining,machine learning capabilities,
cognitive X, Y, Z, and analyticsin addition to the RPA
technology that we're talkingabout.
So what I'm hearing fromcustomers is that this
(12:25):
multi-vendor landscape and thedesire to have multiple
technologies to do variousdifferent things under the
umbrella of enterpriseautomation is inevitable.
There are about 40 to 45,000customers using RPA across the
globe.
Today, 40 to 45% of them areusing multi vendors.
And that is continuing to growas we see commoditization,
(12:47):
particularly of the attendedautomation capabilities with
some of the new large entrantsthat have entered into this
space.
What's really interesting isthat over the last, I would say
three years or so, about 11billion of investment has gone
into RPA.
A lot of it has gone into thethree major players and then the
(13:08):
long, tail of 65 other playersthat exist in the market.
However, if you look at theacquisitions over the last two
years, 14 acquisitions totallingabout one and a half billion
dollars.
So 10 billion gone into the coreRPA vendors, one and a half
billion dollars gone intoacquiring 14 companies for large
(13:30):
entrants like Microsoft, IBM,SAP, and various others to enter
into this market, starting tocommoditize attended automation.
So with that kind of a dynamic,there are a collection of
technologies customers areusing.
They're struggling with how tostitch these technologies
together because the corefundamental focus of RPA vendors
(13:53):
has always been to sell bots.
The orchestrators are lackinginnovation, in my opinion.
And because of that gap,customers are struggling with,
if I have multiple vendors, howdo I manage these vendors?
Where's the single pane of glassto be able to manage the entire
lifecycle of automation?
(14:14):
Andreas, if you walk into aCFO's office today, she cannot
tell you that she can't give youfinancial information because
she doesn't have a system forit.
She does.
If you walk into a CRO's office,he can't tell you that he won't
give you sales forecast.
He has a system for it.
It's a CRM system.
If you walk into a CoE today,not all of them, but a few of
(14:34):
them, you do find Excelspreadsheets, SharePoints
PowerPoints, SMS messages tomanage the entire lifecycle of
automation to manage all thesemultitude of technologies that
exist today.
And that is a significantchallenge.
And we're starting to see theemergence like we saw in the
network world, like we saw inthe cloud world.
(14:55):
Where we saw networkoptimization tools, cloud
optimization tools emerge.
We're starting to see theemergence of these single pane
of glass automation optimizationtools.
There's still a long way to goin this market, but I think
coming back to your question.
Yes, I think the multi-vendorlandscape is inevitable.
(15:16):
Ian, Frank what are yourthoughts.
Frank Casale (15:19):
Yeah, I'm happy to weigh in on this.
My feeling is if you really wantto de-risk it and have one neck
to choke, then outsource it.
It's pretty straightforward as Isee it.
However, realize there's no riskfree path, so you outsource it.
You have predictability there,but you're giving a margin and
(15:41):
you're giving up potentiallybest in class solution.
But that's the way to go.
On the other hand, if you wantbest in class and you have a
comfort level that your IT teamhas some experience cuz you
really want to get beyond themlearning this on your dime, if
you will.
If you're the internal clientand, I would say the majority of
(16:02):
global 2000 have some experiencehere, then you go best in class
and maybe bring in ideally thethird party just for success
insurance and build somethingawesome.
But even then now you haveintegration, creates
uncertainty.
And I would assure you, whateveryou like this year, you will not
(16:23):
like next year.
It is a bit of a dilemma.
And then again, looking where weare now, and I promise I'm not
getting a commission, that eachtime I say ChatGPT, somebody
sends me$50.
If you look at where we are now,we're on the precipice of the
whole game changing so, we justneed to be aware of it.
It's still young and it's notenterprise ready.
(16:45):
It's very cool.
It's very interesting.
I believe it's likely to changea whole bunch of things.
That's my understatement, butnonetheless I don't see an
enterprise ready.
One last thing I'd like to say.
When we think about the buyers,obviously there's a lot of
different ways to define large,medium and, small, et cetera.
But what I've seen, and I thinkmany of you have seen is, a
(17:09):
significant difference intraditional companies versus
digital native organizations ofhow they do this.
So I would caution against thebig kind of macro view of the
market because the way I wouldapproach a strategy at JP Morgan
(17:30):
and the way that would be or notbe embraced would be totally
different the way I wouldapproach it at Spotify, a place
that was born in the cloud,digitally native.
In the latter scenario, which issmall, digital, native,
non-regulated industry, that'sgonna be a shorter cycle, less
landmines.
We're just gonna be moving andgrooving.
(17:51):
It's gonna be a lot faster.
You get involved with a big bankor an insurance company, the
ultimate impact could besignificant, but it will be
painful.
I know I have battle scars doingthose deals, and I know a couple
my colleagues do.
Andreas Welsch (18:08):
Awesome.
Anybody else wanna add Ian?
Ian Barkin (18:10):
Yeah.
This dates us all, I think.
But, that conference I mentionedthat Frank held, that introduced
me to RPA was an outsourcinginstitute conference, not an RPA
conference.
And RPA came out of theoutsourcing industry because we
were using whatevercapabilities, tools, resources
we had available to us to makean outcome for our client.
In that case it wastransactional processing at a
(18:33):
more affordable rate.
We happened to use arbitrage, sowe went offshore and used people
in places like India.
Then RPA came along and it itmatched that to some degree cuz
it enables us to continue to dothat process transaction
activity.
But with a different agent.
It wasn't the Indian, it was arobot.
(18:53):
So we said it would happen thatway, but then we got too
fascinated by the tech itselfand enterprises started to be
told that they could do it, sothat you don't need a third
party partner who happens to bean expert in this.
You can just fire up your HRteam and ask them to spend their
evenings and weekends digitizingthe tasks they worked on that
did not work.
So to Frank's point working withan expert I think will more
(19:17):
likely be the path to successhere, but it rests on all of us
to figure out a little bit moremodern, interesting
collaborative business modelsand collaborative structures so
that yeah, you're gonna paysomebody.
So there will be some margin,but I'll tell you that margin
will be a function of all of thepain, technical debt and waste
(19:40):
that's happened in enterprisesin the last 10 years, trying to
figure out and deploy the RPA,IDP, process mining,
conversational AI, et cetera,that they're tinkering with
right now.
So I think the future is somesort of hybrid where you're
working with experts, stillemploying the capabilities in
the subject matter experts in.
Maybe to scout and find goodareas to deploy this stuff.
(20:03):
But that's how we're gonnareally make the most of the
tools available to us.
And the need, the big enterpriseis not the digital native ones
that can just start from scratchand be, more be more structured
and, digital from the beginning.
That's, the way we all need togo.
Andreas Welsch (20:20):
Fantastic.
Thanks.
I think well rounded answer andgood to see the different
perspectives here from you.
So if I take a look at the chat,there are some questions about
AI.
For example, Michael is asking: Will ChatGPT and its equal, but (20:32):
undefined
opposite generative AIdetection, become a new market
category, if not in 23, then in25?
Or Christine is asking (20:43):
Do you believe that more attention
towards data monetization inindividual organizations will be
the trend that will shape AI andautomation in 2023?
I think personally I have anopinion on the generative AI
topic and I believe at least forthe time being that we're, still
(21:05):
as an industry, as leaders,figuring out where can we
actually use this and where canwe use it in a way that it makes
sense.
If, we on one hand haveproprietary or models.
On the other hand, we have opensource models.
If we use the ones that areproprietary like CHatGPT, we
don't really know what data hasgone into it.
And you see some discussion andconcerns, for example, over at
(21:29):
Amazon.
Hey, this thing spits out codethat looks suspiciously familiar
to our own IP.
Or questions around informationsecurity more broadly.
Please don't copy confidentialinformation into this chat
prompt, or are the answers thatit generates really reliable, or
do they just sound plausible?
So I think there's still somethings that the industry needs
(21:51):
to figure out.
And, similar I think also to,RPA and, other AI scenarios.
We might want to have the humanin the loop for some time to
review it.
It's good, at least at themoment, right?
In the scenarios we see, and atthe moment it's good as a
kickstart for ideas and to getcreativity flowing.
Maybe to reword or rephrase afew things.
(22:14):
And, I'm sure you know this.
We'll, see a thousand more waysto use this.
I don't think its own category.
I think much AI it'll help a newkind of application, be powered
and, deliver more.
And I think also on the otherside, organizations looking into
monetization, I think there area few that they're doing this or
(22:38):
will be doing this and will bedoing it well.
But also depends on theunderlying architecture.
Do you have the data strategy,the processes, things in place
to be able to do that.
And maybe part of that goes backto digital natives and
established companies as wellwho might be able to do it
easier if you're starting new inthe cloud, relatively new
compared to having legacy andhistory.
(23:01):
But I'm curious what do youthink?
What are you seeing there?
Maybe just briefly.
We have a few more minutesbefore we wrap up and wanna get
to Ian.
And, the question I have for youas well.
Frank Casale (23:11):
Okay.
May I, in a friendly way,disagree with you with
opponents?
Andreas Welsch (23:15):
Sure.
I'm more optimistic than youseem to be, Andreas with regard
to ChatGPT.
And I think it'll besignificant, I think from a
standpoint of category.
I recommend that we all thinkabout less about what it is and
we focus more about what itdoes, which you alluded to.
(23:35):
I think it's all about use case.
And I think there are people onthis line now that have ideas
for use cases, and I would saythe right use case with the
right commercial strategy isyour fast track to independence.
I think there'll be billions ofdollars made.
Some people will make millions,some people will make billions
for anyone.
And the barrier to entry is verylow.
(23:59):
Which is it?
Okay.
Double-edged sword.
But still the, opportunity forsomeone now with an idea,
getting a whole of technologythat is cheaper than cheap.
Why?
Because it's free it issignificant.
So I've been watching this veryclosely.
I've been fortunate enough,maybe the older guy on the panel
here, I've been through a coupleof cycles.
This is significant.
(24:19):
However yes, there will be a tonof lawsuits.
I think IP becomes debated.
I think it becomes very, veryfuzzy whether you're in the
insurance game or a collegestudent doing a paper.
I think that becomes very fuzzy.
However literally this weekendyou could launch a business and
go.
There are tremendousopportunities.
(24:41):
One quick thing, if I may, ondata monetization.
From what I've seen, thediscussions have been amazing.
I've seen very amazing stories.
I think for the average company,if you're a bank or an insurance
company or in telecommunicationsor you're a media company, the
(25:02):
odds of you investing the time,by the way, you may have a
billion dollars worth of IP dataand yes, data is the new oil,
blah, blah, blah.
I haven't seen it.
I haven't seen it yet.
I think it's likely gonna be anindependent organization.
Shail Khiyara (25:17):
Look I'm very bullish on what you just said,
Frank.
Very bullish on generative AI asa whole.
I wouldn't say just focusing onChatGPT, but if you look at the
marginal cost of energy, it'sapproaching zero.
That's going to happen to theintelligence as well.
Marginal cost of intelligenceapproaches zero, and it's
happening at an extremely fastpace.
(25:37):
If you look at Transformers,when you look at BERT back in
2017 to ChatGPT now in less thanslightly more than five years.
The next five years, you'regoing to see transformers even
evolve even further.
Where prompts or questions arenot going to be the key focus
areas anymore.
It's going to be theconversation that you and I are
(25:58):
having right now that is goingto be prevalent in terms of how
you interface with thesesystems.
So I do think the opportunity isimmense.
I do think that there issignificantly fast-paced
technological innovation that isgoing on.
To Frank's earlier point, whatyou may like today, you may not
like tomorrow.
Same applies to ChatGPT as well.
(26:19):
You may like it today, butthere's something new coming
tomorrow very quickly.
That's one aspect of it.
The other aspect of it is Ithink it's going to change the
structure of interfaces insociety as we know it in many
ways.
Frank talked about lawsuits.
There's already discussionsabout how to use this or not to
use this in schools.
(26:40):
There are already discussionsabout how, who owns digital art
as an example.
So these are new questions thatare coming forth that we have
not dealt with before as asociety.
So that's going to be a veryinteresting change across the
world.
And by the way, ChatGPT, rightnow, the interface is English.
Wait till that changes.
Andreas Welsch (26:59):
Excellent point.
Maybe Ian I'll go over to youfor the next question that we
have, so we can finish somewhatin time.
But I really appreciate the goodconversation and discussion we
are having here.
Also the questions in the chatgo in that direction if there
are these huge shifts and thisnew momentum for automation, for
(27:21):
AI.
I know you often post about thisand call it the workers of the
future in the future of work.
So I'm, wondering what does itmean?
What do you mean by that andwhat does it take to be a future
worker?
Ian Barkin (27:34):
Sure.
Ultimately the divide of IT andbusiness has held back true
evolution just cuz businessknows what they need and IT
knows what they can build andwhat they have.
And so the last 10 years we'veaspired to bring those groups
together or at least empowerbusiness to run a gray rogue IT
operation where they can getdone what they think they need
(27:55):
to get done in the future.
Because every company is asoftware company.
We all need to evolve ourskills, and enterprises need to
realize that.
Cuz as we've just discussed,there'll always be a new tool.
There always will be.
Ultimately we need to build aflexibility and a foundational
digital literacy and digitalquotient within enterprises so
(28:18):
that we can assess incorporateand apply whatever comes next.
If it's ChatGPT or if it's RPAor whatever else.
And, then we need to be able toadapt the organization design
really good incentive structuresand initiatives to make the most
of it.
Because right now, in RPA, weare hoping business could do it.
(28:41):
It's a little hard.
We got it doing it, but we don'thave enough IT folks.
We don't have enough developersin the world to build all of the
apps and the configurations thatbusinesses believe they need.
And so you're leaning on yourcitizenry to do that.
And yet the citizens aren'tnecessarily.
Skilled up yet to be able to dothat.
So most of the citizendevelopment initiatives that are
(29:03):
happening in the world arepilots.
They're small in scale andimpact.
And so over time, foundation ofdigital literacy, we need to
create a better organizationalstructure with incentives
because the smart people, theones who actually know how to do
this, are using it to digitizetheir jobs and then just go play
video games for half a week.
(29:25):
So those are the ones who havethe moonlighting and the gigs
and the side hustles.
So they don't have any incentiveto, to share what they've, what
their ingenuity and theirability have allowed them to
develop for their enterprise,cuz what's in it for them.
There are a lot of pieces thatneed to be worked out to truly
harness the ingenuity ofeveryone within an organization.
(29:47):
Make them capable of adoptingthe tools that come out as they
come out and then to have thesemeaningful discussions about how
we're gonna experiment andimprove out their value and
apply them in a broader scale.
Andreas Welsch (29:59):
Perfect.
Thank you.
That's awesome.
I think that's a really good wayto also end today's session on.
But before we do, I waswondering if you can each
summarize one key takeaway forour audience today.
Starting with Frank and to Shailand to Ian again.
Frank Casale (30:17):
Wow, that's tough.
I believe I coined a term abouta decade ago digital labor and I
for years kept thinking thatwe're almost there.
RPA?
Nope.
Intelligent automation.
Close.
Maybe full on AI.
Not sure.
I believe we're approaching thattipping point where intelligent
(30:39):
technology will shift fromassisting knowledge workers to
emulating knowledge workers.
Now that's exciting and alsofairly scary.
So there will be people thatwould be able to find
opportunity here.
But regardless of who you are,buyer, seller, advisor,
entrepreneur, wanna beentrepreneur I would recommend
(31:02):
that you think about thefollowing and I jotted them down
because I think it's importantfor each of us as people,
workers, professionals, and youhave a life, you have a family,
I would say.
To power through the change.
Most relationships win.
Biggest network helps a mindsettoward continuous learning.
(31:25):
You can't, if you get stuck withthe old dog and the new tricks,
you're stuck.
And last, by not least,financial runway could be a good
amount of turbulence dependingon who you are.
I think at that point you're,you have the best odds of
powering.
Andreas Welsch (31:39):
Fantastic.
Thanks.
Going over to Shail.
Shail Khiyara (31:42):
Yeah, look, there are two things that make up
organization.
It's people and everything else,right?
So I would say that it the sameapplies to automation as well.
Automation, it's not the botsdriving your automation.
It's actually the peopleinvolved in it and the ecosystem
around it.
So my key takeaway is that focuson the software aspects of
(32:03):
automation, which is theculture.
How do you create a borderlessorganization?
How do you create a no fearzone?
How do you actually empowerpeople to drive automation
inside your organizations?
The last thing I wanna say isthat look I just want to express
my gratitude sitting herelistening to industry experts
who.
(32:24):
In many ways helped educate themarket, Frank through IRPAA and
other means, Ian, throughLinkedIn Learning and, other
means as well.
And Andreas, what you're doingas well.
So I'd encourage the audience asa takeaways, follow them.
There's a lot to be learnedhere.
Andreas Welsch (32:41):
Perfect.
Thank you.
And very nicely put.
Hard to disagree with that one.
So over to Ian.
Ian Barkin (32:48):
And hard to follow those two guys.
Man, what the hell am I leftwith saying?
I agree with everything thatFrank and Shail just said.
It is about people.
It's about that commitment todigital literacy.
It's a more exciting future nowthan it was 10 years ago when I
started playing with this stuff.
It's certainly more confusingbut it's just because we've got
(33:11):
more tools and more players andmore enthusiasm in the space.
So, you really owe it toyourself to stay plugged in and
educate.
As the guys just said before.
The group on this call reallyhas committed and dedicated a
lot of their energy to doingthat.
To exploring for their ownunderstanding and then sharing
for the understanding and thedevelopment and betterment of
(33:33):
our communities.
Follow Shail, follow Frank,follow Andreas.
Those guys are putting outincredible content.
And thanks for having us,Andreas.
This is a great discussion.
Really appreciate you puttingthis together.
Frank Casale (33:45):
Thanks, Andreas.
Andreas Welsch (33:47):
Yeah, so thanks for joining us.
When we started this, we startedon RPA.
I wasn't quite sure how far intointo AI we would get.
And here we were talking aboutgenerative AI and ChatGPT.
So I think, we really coveredall the major trends and really
appreciate you sharing yourexpertise with us and the
community here as well.
(34:08):
Yeah, so I think the only thingleft to do then is to close us
out.
Thanks Shail, Frank and Ian forjoining.
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