Latest / AI for Founders with Ryan Estes / AI in Enterprise: Security, governance, and robots

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AI in Enterprise: Security, governance, and robots · AI for Founders with Ryan Estes

0:00
Welcome back to AI for Founders. I'm Ryan Estes, and today we've
0:02
got a really special conversation lined up with the
0:05
Jim Spignardo, Director of Cloud Strategy and AI Enablement at
0:09
Pro Arc. Now, Pro Arc is nearly 20 years
0:12
old, which means they've seen it all.
0:14
From the birth of YouTube to the rise of the iPhone, the
0:16
explosion of cloud computing, and today's AI hype cycle.
0:21
Jim has been at the center of that transformation, helping
0:23
companies figure out how to turn cloud and AI from necessary evil
0:27
to powerful engines of productivity.
0:30
In this episode, we get into what AI really means for
0:32
businesses, how to cut through the noise, and why the best use
0:36
cases are often the simplest, like automating meeting notes or
0:39
eliminating the drudgery of RFPs.
0:41
If you've ever felt overwhelmed by now with AI headlines, this
0:46
episode is going to reset your perspective.
0:49
But for some business, this episode is brought to you by
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Tonight Shine Stars Computer Life AII take the flight in the
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glow with me on. Brian, Jim, thanks for joining
2:38
me. No problem, good to be here.
2:41
Absolutely. Now you're with pro arc.
2:43
Give us a a broad understanding of what Pro Arc does and what
2:48
your role with the organization is.
2:50
Sure. Yeah, Pro Arc is a a global IT
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consulting and services organization.
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We have locations here in the North America, in Atlanta, in
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upstate New York, as well as the UK and India.
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And my role specifically with Pro Arc, which I've been here
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for now almost nine years, my current role is as Director of
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cloud Strategy and AI Enablement.
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So which is pretty new, pretty new for this organization, as it
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probably is for most organizations, as these roles
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didn't really exist a few years ago.
3:27
So cool and I love talking to like seasoned companies like
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this because Pro arc is nearly 20 years old in IT, which means
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you guys have gone through massive amounts of changes from
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like, you know, if we're thinking about 2006, I'm
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thinking about like the birth of YouTube, you know, and they have
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kind of like iPhone comes out and then you have Web 2 with all
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the social media implication. Then you have the cloud
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development and you just all of these huge benchmarks.
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So it's interesting to me like how cloud infrastructure becomes
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kind of a part of AI as far as this next round of of this
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massive hype cycle around AI, but also the lasting power of a
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truly transform, transformational kind of
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technology. So how do those two kind of play
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together? Well, I think you know, really
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the the role of of cloud infrastructure with an
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organization is to find or or define what the technology tool
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sets are, right and best leverage them to assist the
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business. At least that's the way we look
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at it and how we consult with our customers.
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I think there's a lot of organizations out there that
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look at it as as well. It's just a necessary evil of
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doing business. We would really see it as a way
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to enable business to be more productive.
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So an obvious extension of that right is AI and the that tool
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set in how it can not only bring in end user productivity, but
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also can transform the way work gets done for for organizations
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as a whole. Yeah.
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And it's interesting because we were kind of chatting about this
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before, that there is a. Certain amount of AI anxiety.
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For, for founders, for CE OS, for IT professionals, for
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security professionals, largely because AI becomes some weird
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blanket wrapper they put around absolutely everything from, you
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know, Amazon's creating like new AI generated movies.
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So it's like, oh, is it a movie or you have automations within
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your work flows? Is it, is it that it just become
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kind of this catch all? It really reminds me of like you
5:30
remember when omega-3 fatty acids like became like a big
5:34
thing in diet. Oh yeah, eat more salmon.
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And suddenly it's like your crackers now with omega-3, you
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know, like, Dang, do I need like fish oil in my crackers?
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Like what's happening? But it be it becomes kind of a
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marketing trend. So we're probably on the
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backside of that where the standards I think of AI being a
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successful product is it just kind of works magically.
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You don't need a like you, you don't need to emphasize it.
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So I guess when, when everyone's like saying now with AI, it, it
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leaves people in leadership positions not really knowing
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what they should do what they shouldn't do.
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So what, what are basically what should people consider with AI
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when they're like, OK, we we need to embrace some of these
6:18
new tools. Maybe what are those tools and
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and what are some some early kind of solutions you like to
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bring to an organization's getting get getting going with
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some automation? Sure.
6:28
Yeah, I absolutely hear those stories all the time from groups
6:31
that we're dealing with where, you know, we'll talk to an IT
6:34
admin and he he says, well, I'm, I'm engaging with you because my
6:39
board keeps telling me what are we doing with or asking me what
6:41
are we doing with AI. And so there, there still is a
6:44
lot of that where there's uncertainty, there's this
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expectation that we were supposed to be using it because
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from, from, you know, our perception, everybody's using
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it. And So what I would say is, you
6:58
know, look at this from the perspective of any other tool
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you would bring into the business.
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You need to define the business objective, right?
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You need to find the business requirements and understand, you
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know, what are the things based on what we're hearing, right?
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Hopefully there's a certain level of education that's going
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on and, you know, people are starting to read articles and
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understand the, the, the power and the capabilities.
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But what is it you're trying to solve for?
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What are what are the pain points you're trying to address?
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Those are things that you know, you may have been deploying
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other tool sets for that AI may have the, the ability to solve
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for. And so once you can define those
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and you have to define them pretty pretty distinctly and
7:44
pretty succinctly of, of who these are going to be targeted
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to or towards which workflows work process are you going to
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embed these in? And then kind of look at what
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are the tools that are out there that you can deploy to address
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those needs, Because you know, a has a lot of different things.
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It's not one thing. And there's, you know, avents
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and there's, there's machine learning and, you know, quite
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honestly, AI has been around for a lot longer than, you know,
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GPT. So that's where I would say they
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should begin. And, and assuming that they've
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decided to find some use cases that they want to pilot or or do
8:23
proof of concept on, they also need to kind of back things up
8:27
just a little bit and hopefully establish some good security
8:33
policies, procedures and governance.
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And in a lot of cases, that's where everybody should be before
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they even think about these cases is because these tools are
8:43
already out there, right? We get a lot of times when
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customers say we're not using AI or we don't allow AI and my, my
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next reaction is, well, you just don't know it's being used then,
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right? And if you don't know it's being
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used, then there's an inherent risk.
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So you need to establish through a good solid AI use policy, you
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know, which tools are going to be the acceptable tools to the
9:07
organization, What are the guidelines for using those
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tools, what is OK and what is not OK to do.
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And then you can kind of wrap that around your whole process
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as you start off on that journey.
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Yeah, and let's talk a little bit about use cases.
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I was meeting with a guy buddy of mine wanting some consulting
9:25
on how to utilize a on his business.
9:27
After about 10 minute conversation, I'm like, buddy,
9:30
you need Calendly and Stripe. Like there's some off the shelf
9:34
stuff right here that you should probably be investing in before
9:37
you start getting too advanced. So you know what's a good use
9:41
case from your perspective, Like when a company's really ready to
9:45
take a step into some custom automations?
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Yeah, I, I would say when, when they're looking at, you know,
9:54
how to get started initially the, the universal kind of use
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case across every single organization that invariably no
10:04
organization typically does very well.
10:06
Is that it that it's collecting notes during meetings and, and,
10:11
and being able to, to use that to inform the organization from
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an automation perspective. If you could find some
10:17
integrations that will actually allow that tool that captures
10:22
the information, then to put it into your CRM or your PSA
10:27
ticketing system or something like that, that's even better.
10:30
That takes one more step out of the equation or the folks that
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are collecting that data. But that's honestly that's the
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simplest, easiest low hanging fruit.
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Beyond that, you know, we have tons of agents we've developed
10:44
for ourselves internally, no code agents that take those at
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what I call, you know, when we thought about robotics for a
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long time, they said that robots were going to do the things that
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were dirty, dull and dangerous, right?
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And so I kind of have a different approach on that is AI
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is really going to deal with the things that are kind of
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drudgery, distractions and you know, the dull things.
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And so if you think about something that's drudgery, big
11:13
thing for any sales organization is responding to RFPs, right?
11:17
So that was one of the things that we, we almost stayed away
11:20
from that as an organization for so many years because we're
11:22
stuck to time stock and we at the end of the day, you weren't
11:26
sure you were actually going to win it anyways.
11:29
But we've created a real tight agent now that has all this
11:32
information about our organization.
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You can feed it the RFP, you can have it, you know, spit out, you
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know what the where the gaps are.
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I can start responding to that RP for you.
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So taking that we've reduced the amount of time and effort it
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takes. Any anxiety, let's face it,
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there's also anxiety around that.
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And you know, I would say on the order of, you know, 50% of the
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time, maybe even more has been reduced.
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And we've actually standardized on the way those things look
12:01
going out the door, whereas every single one before was, you
12:04
know, this unique snowflake. Yeah.
12:08
You know, yeah, I could think of, you know, 1000 more, but
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those are kind of some of the things that I think are
12:12
universal through a lot of organizations.
12:14
Those are great ones cause the RFPs, you know, we're getting to
12:17
a place where the RFPs will be AI generated, the response will
12:21
be AI generated. The response to the response
12:25
will be AI filtered and generated till you get to the
12:28
point which you, which you really need is shaking hands and
12:30
like, Hey, let's see if we can work together.
12:32
You know, so it's, it's almost becoming like a gateway in in a
12:38
sense, or like it's, it's its own filtering process because
12:42
it's going to understand like, OK, they know all the rules to
12:45
the game. We know the rules to the game.
12:47
We're getting to where we need to go to, to take the next step
12:50
is very interesting. And then like with the, the note
12:52
taking apps, you know, I'm fascinated by this because I
12:55
really feel like this is an infancy of something much
12:58
greater. The note taking apps.
13:00
I love it. You know, I've, I've used
13:02
Firefly, I've used granola. I think it's pretty cool and
13:06
then I what do? You try that one, Yeah, Renault.
13:08
'S kind of cool because it's a little clandestine so you can
13:11
record on your side. It doesn't do the video, but it
13:14
takes all the all the audio notes and doesn't tell the
13:17
person that you're in the call with that it's recording.
13:20
So I'm like, that's kind of an interesting wrinkle.
13:23
I mean, I don't know why you wouldn't.
13:24
And maybe there's some like compliance there that you you
13:27
should be. Concerned about definitely is
13:29
and you know, we we are, we're a big Microsoft shop.
13:31
So Teams is our go to tool, but we definitely see a lot of
13:35
folks, you know, that come into our meetings to have those other
13:39
other tools as well. But yeah, I did, you know, one
13:43
of the things that I, I was quite surprised by is that, you
13:48
know, we use Copilot and because all of that becomes part of your
13:52
data state, all those conversations, all those chats,
13:55
all those meetings, all those transcripts, all your documents.
13:58
I just opened up a Word template the other day and literally at
14:02
the top of that document, it asked me, hey, did you want to
14:05
create a summary of this meeting or did you, do you want to
14:07
create a justification of why that this this client wants to
14:12
or should purchase this service from you right at the top of
14:15
Word? I'm like it just because it was
14:16
looking across the things I'd recently done and said, well,
14:19
maybe you open this document. Here's a few things you might
14:22
want to actually work on. How surprised?
14:24
I'm like, that's where the integration is just kind of
14:27
driving right into the other applications and you know,
14:30
making us much more efficient and and it continues to evolve
14:34
and then impress. And you said with this, these
14:36
other tools that you've been using as well?
14:38
It's so cool. I mean, I was actually trying to
14:40
vibe code this thing the other day.
14:42
There was basically a button that you hit that starts logging
14:45
everything that's happening on your screen that is actually
14:48
looking for opportunities to automate.
14:50
I think like one of the pain points I have is like OK do I
14:56
want to sit down and try and create an NAN workflow by this
15:00
with this super complex thing? I just like Nah I'll just keep
15:04
doing it this way because it seems too annoying and I don't
15:07
want it to break 2 weeks later. This is backwards thinking, but
15:11
what I, what I wanted, what I wanted is something to just like
15:16
automatically check because these are the, this is the, the
15:18
glaring one. Like, OK, I'm doing this thing,
15:20
but I'm, I guarantee there's probably 10-11 other things that
15:24
I'm doing. Just, I'm not noticing that like
15:26
this process should be automated.
15:28
So having a master button that would like basically log all of
15:31
my actions and then make recommendations of like easy
15:35
tools and ways to integrate them.
15:37
I think that would be really cool.
15:39
Yeah, and, and I think we're getting there, right.
15:41
So I know on the consumer side, Microsoft now has the ability
15:46
for Copilot to see your screen, to actually watch what you're
15:49
doing and you can actually ask it to collaborate with you.
15:53
So, you know, you can go to a a shopping site and, you know,
15:58
say, well, would this look good in my living room here?
16:00
I'm going to upload a photo with this piece of furniture look
16:03
good in that room, right, And also being able to just see
16:07
everything else you're doing. So I think think those abilities
16:09
are are we're we're pretty close and then with chat GP TS agent
16:14
function, right, that's not necessarily it watching you, but
16:19
you're telling it to go do something for you, right.
16:22
I actually tried this out and said, you know, I I own a an old
16:25
Fiat 500 E and I love this little car, but I just wanted to
16:30
see what this was possible. I was capable with ChatGPT agent
16:34
and I said, find me a Fiat in this color this year, this many
16:39
miles for this price, right. And it just opened up a browser
16:43
and AVM and went to work and 20 minutes later at a list of 10
16:48
vehicles in the around the country that fit those batch,
16:51
those specific specifications I provided.
16:55
And then it wanted to follow up and said, what do you want me to
16:57
actually reach out to these buyers and tell them that you're
17:00
interested? And so that's kind of, you know,
17:03
the other aspect of that, yeah, 1 is watching what you're doing
17:07
to help you get better. But then the other part is just
17:10
giving it the thing you want to do and having it go do it,
17:13
right, which is follow up with you, which is really kind of
17:16
getting to the point where that's true assistance, right?
17:19
That's a true assistant. It's unbelievable and it it
17:22
ultimately ends up in personal customization of absolutely
17:25
everything you want with a predictive kind of aspect that
17:28
it's giving you what it thinks you want.
17:30
And it probably knows it pretty well.
17:32
You know, I was building a little application that was kind
17:34
of a, a copilot for these podcast interviews that would it
17:39
in real time, like pull up like you're talking about Fiats.
17:42
He would start pulling up that car and might pull up the
17:44
websites and might pull up all these things just as a way to
17:47
like feed the conversation. But in that instance, I found it
17:51
like actually it, it wasn't irritating.
17:53
It was distracting from the conversation like because it I
17:58
feel like as a a journalist and I wouldn't call myself that, but
18:01
like a, a good journalist is like listening for openings and
18:05
looking for to go deeper in a conversation as opposed to being
18:08
like, oh, dude, the red one's really cool or how that ends up.
18:13
But this also kind of points and I appreciate going down this
18:16
little rabbit hole a little bit because the future of this is so
18:19
interesting. I know Anthropic just released
18:22
like a browser function. So like my little button idea.
18:24
They they're they're way ahead of that.
18:26
That's coming for sure. The the note taking apps
18:30
fantastic. We're already on zoom or we're
18:32
on, we're on Microsoft Teams. Like we can do this automated or
18:35
or automated and bring it all over the place.
18:38
But I was. Kind of playing around with this
18:40
thing. Called.
18:40
It's a wearable called B computer.
18:43
Yep. I've seen it.
18:45
It was acquired by Amazon recently, but it's like 50 bucks
18:48
you clip it on and then it's it records everything that's
18:51
happening right it's. Got a little blinking button on
18:54
it. Yeah, well, it didn't blink at
18:56
first. Oh, really?
18:58
OK. Yeah, so, but and I had two
19:00
people that were like, what's that?
19:01
And I was like, oh, it's AB computer.
19:03
They're like, are you recording this?
19:04
And like the look on their face kind of went white.
19:07
And they're like, they're like replaying like, what did I say?
19:10
And it felt like an intrusion, you know, it, it felt like, and
19:16
I think some of this is also like, if we're thinking in a
19:18
professional sense, like this is also where you're going to need
19:21
guidance from a company like Pro Arc, because again, like, do you
19:24
want to allow Bill Gates to see everything you're doing on every
19:27
single person's device? Do you want that What, what kind
19:30
of guardrails you want to put up?
19:32
What kind of parameters you want to put up for Sam Altman and
19:36
Bill Gates and everybody else? Jeff Bezos and yeah, yeah,
19:39
hungry. Don't forget Mark Zuckerberg.
19:42
Yeah, lungs out there. Sure.
19:47
You know, that's, that's, that's the things we that we, we, we
19:50
struggle with. And that's a question we get a
19:52
lot from our clients too. Is, is this secure?
19:56
How do I know it's secure? And so we spend a lot of time
19:59
discussing responsible AI pro work actually has the a solution
20:05
we developed that's actually called AI Examine.
20:08
And it's, it's meant for companies that have developed
20:12
their own AI solutions, you know, full stack solutions, but
20:16
it's able to evaluate the outputs from that system and
20:21
measure it for bias, measure it for accuracy.
20:25
And so you now have a way to, to kind of use that dashboard to
20:29
dial in that, that, that system to get it to be more accurate,
20:33
less biased, less, you know, if it's doing things that are, are
20:37
unethical. And so all of that can be
20:39
evaluated and kind of slapped on top of your solution to be able
20:42
to, to go through that and learn that.
20:45
But what it comes down to too, is, is doing your due diligence
20:49
and making sure you understand those tools that are using.
20:52
What are their privacy policies? How do they treat privacy?
20:57
And that's part of why we, you know, we're a big advocate for
20:59
Microsoft again, and I don't, I don't propose that Copilot is
21:03
the best AI solution out there. I use a lot of different things.
21:06
I use a notebook LMI use Gemini, I use Claude.
21:11
But what it does that others don't is it does truly respect
21:15
the privacy and has lots of security controls that you can
21:19
dial in, right? I've been in the Microsoft world
21:23
for a very long time. I was a Microsoft certified
21:25
trainer for nine years, worked for, you know, Microsoft took
21:30
partners for the majority of my career.
21:32
And I've what I've always said is Microsoft's not the most
21:35
securable platform or it's not the most secure platform, but
21:39
it's one of the most securable platforms if you want to take
21:41
the time to actually use the capabilities they have.
21:46
It gets you a long way there to the point where you know, you
21:50
can get visibility into not only the use of Microsoft's AI tools,
21:56
but also through their security stack, be able to see what
22:01
people are using from a third party tool tooling perspective.
22:04
That's kind of where we started on that conversation earlier
22:06
about you don't know what you don't know, right?
22:08
These companies that think they're not doing AI well, they
22:11
have no visibility. Microsoft, through their
22:13
Defender for Cloud app security solution can actually tell you.
22:16
And then you can make decisions, you know, informed decisions
22:19
about do I want to allow this particular application based on
22:23
its security review score? You know, their what's their
22:26
privacy score? And then you can choose to to
22:28
turn that stuff on or off. But, but going back to your
22:31
initial thing about that little bee thing reminds me of Google
22:34
Glass. Great when it first came out.
22:38
People are just like, put turn that off, get that off your
22:40
face. I don't want.
22:42
People are versed to it now, you know, but I, I think that's
22:45
going to fade away pretty quickly.
22:47
I mean, you know, and honestly, Microsoft, boy, were they in the
22:51
right position at the right time with AII mean they knocked it
22:55
out of the park. Well, they, they hooked their
22:57
wagon to the the right team, let's put it that way.
23:00
And, and as much as open AI would like to unhook, there's
23:06
they're, they're, they have a pretty solid contract that says
23:10
they, they got to stick together for at least a, a a fair amount
23:13
of time going forward. And that benefits, that
23:16
definitely benefits the Microsoft community.
23:19
You know, when chat TPT 5 came out, I was really surprised
23:23
because normally Microsoft takes months to incorporate the
23:26
capabilities in the new capabilities into the system.
23:29
They were in lock step. I mean, by the next week there
23:33
was a Tri chat TPT 5 button and copilot and you could
23:36
immediately see the benefit. And that way, you know, that why
23:39
that relationship exist. One of the things though, that I
23:41
think is the misnomer or misconception in the industry
23:47
is, you know, everybody thinks that, well, Microsoft uses open
23:50
AI. So therefore they must have the
23:52
same security and privacy as open AI.
23:54
And that's not the case, right? They use open AI as models,
23:59
adapt them to them through their own features and capabilities.
24:04
But you know, as far as training the models on your content, all
24:09
that kind of stuff, no, that's not, that's not what they do.
24:11
And, and clearly they also respect your security
24:15
boundaries, right? They respect your RBAC and your
24:17
security permissions when it comes to you know what people
24:21
can find and see. Well, and you know, I mean,
24:25
Microsoft has a pedigree of security first, which you can
24:29
rely on. And that's this is something
24:30
that open AI really doesn't. I mean, you know, not to be
24:33
judgmental, but it's like, boy, some of the stuff they're doing
24:36
is real sketchy, you know? Yeah, And I think they've, I
24:40
think they've, they want to play in that space.
24:43
From my perspective, that's why there's been a little bit of a
24:46
riff of late, because Opening Eye sees the opportunities in
24:52
their ability to grow as a business and it's it's putting
24:56
them on a collision course with Microsoft, right.
24:58
And so at the same time, they realize that if they want to be
25:01
taken serious, taken seriously as a enterprise wide solution,
25:06
not just something maybe the developer team uses or you know,
25:09
the, the executive group because they really like it, but
25:12
something that's truly an enterprise wide solution that's
25:16
respects, you know, enterprise wide security and enterprise
25:22
wide governance policies. They they need to start
25:25
including some of these things in the product.
25:27
Yeah, it's so cool, it's so fun. That tech is like competitive
25:31
and, and, and wild again, you know, tech 20/17/2018 you're
25:36
just like, all right, Zuckerberg, all right, iPhone
25:38
10, nothing like really kind of exciting.
25:42
But now we have, you know, challengers going after Google,
25:46
going after Microsoft to like hardware that's coming down the
25:49
pipe. And this is one thing I really
25:51
wanted to talk to you about too, and why I think it's important
25:54
that people get their like governance compliance, their AI
25:56
integrations going right now really fast because we're not
26:00
going to have time to blink before robots are here.
26:03
I mean, absolutely the commercial grade robots that are
26:07
out there, you know, 40,050 thousand.
26:10
So you know, you're going to have a robot lease that's going
26:13
to cost you 189 bucks a month and suddenly you have something
26:16
that comes out of the broom closet, makes you being burrito,
26:19
you know, that's coming in no time.
26:22
So, and it's hard to even wrap your head around and especially
26:25
for for companies that are thinking about how are they
26:28
going to integrate AI, it's like, well, boy, you should
26:30
really start thinking about like what kind of actual physical
26:33
robot is going to make the most sense for your.
26:36
It's like C3PO or R2D2, that's the question.
26:40
So. And no problem, honestly.
26:43
Both of them existed, right? And both of them had a specific
26:45
use case. So yeah, you'll have one that
26:47
does your chores, but then you'll have another one that
26:49
does your taxes, right. That's that's a little more high
26:53
thinking. Yeah, the convergence is
26:55
definitely there. And that that, that that's
26:57
really what excites me. You know, I've said this as long
27:00
as I've been in the Sprint, if you're, if you're feeling a
27:02
little UN inspired by tech, just just wait a couple years.
27:09
But what I'm actually more surprised by is that the
27:13
convergence of kind of smart assistants and AI has not
27:18
actually taken off faster. You know, I'm a big consumer of,
27:23
of Amazon's Echo product and, you know, I've been a little bit
27:27
disappointed and frustrated with their speed to getting more
27:31
intelligent AI into that platform because honestly, it's
27:36
a tremendous opportunity. And I think they're, they're
27:39
kind of, they're, they're really leaving themselves wide open for
27:41
someone else to come in there and, and take that business away
27:44
from them. Because, you know, I, I think
27:46
about my aging parents or, you know, people with young
27:52
families, there's so many use cases for that type of
27:55
technology within the home automation space and the, the
27:59
home assistance space where, you know, you can have a, a
28:04
companion to an elderly person who's living at home that's
28:08
reminding them to take their medicine or that's, you know,
28:11
keeping tabs on them to make sure they're OK.
28:13
And, and you know, and, and also just providing a, a certain
28:17
level of companionship for them too. 100%, it's so fun.
28:21
And this is not even to talk about Siri.
28:23
Oh my gosh, Siri. He's trying to get to a grocery
28:28
store and it's like, oh, that's going to take 72 hours to get on
28:31
a plane to Mabai, and you're like, dude, what are you talking
28:33
about? King Soopers?
28:34
Siri, let's go. Yeah, yeah.
28:36
Yeah. In comparison to like when you
28:38
kind of chat with GPT, you know, where I, I had to tone down like
28:44
kind of the sass on the GPT because I'd, I'd ask it
28:48
questions and it'd be like, OK, like, don't give it to me like
28:53
that. I'd be like, speak like Malcolm
28:55
Gladwell or something like give me.
28:57
Malcolm Gladwell, That'd be a good one.
28:58
Give me Ken Burns, you know what I mean.
29:02
But to your point, I mean it it it's it's coming quick, it, it
29:06
will be in a human form. I mean, for me, I'm more of an
29:09
R2D2 guy. When I see a robot that looks
29:12
humanistic, it just makes me want to hit it with the baseball
29:15
bat for some reason. I.
29:17
Think too much sci-fi? Yeah, you're just, you just got
29:21
to look at it and go, well, it has hands and legs and I know
29:23
what I could do with my hands and legs.
29:25
You know, what if this thing decides to turn on me, right.
29:27
R2 was always a little, you know, cute and and they had that
29:31
BBB 8 right from the other movies.
29:34
Yeah, that's that might be what the first one we get is to some
29:36
rolling little ball that goes around on the floor or whatever.
29:39
Totally. That would be great.
29:41
And then it can do things for you, but it's not like has some
29:44
like weird eyes that's like, and you know what's in the closet.
29:47
Like if it's moving around, I would feel comfortable, but if
29:50
it's like I know what's in the closet, just sitting there
29:52
waiting for something, you know? You don't want to wake up in the
29:55
middle of the night and this thing standing your doorway just
29:56
staring at you sleeping. No, absolutely not.
30:00
But, but honestly, we're, I mean, we're, we're on the verge.
30:03
I think this is, I think in many ways we're farther away than we
30:10
think, but in other ways we're much closer than we think.
30:13
And I know that's kind of a contradictory statement, but you
30:16
know, when I look at what's, what's possible right now, we,
30:19
we kind of overemphasize the, the ability for it to do some of
30:23
these things. But I'll give you like coding,
30:25
right? It's, it's having, it's
30:26
absolutely no doubt it's having a tremendous impact in that
30:30
world. But can it, can it replace your
30:34
entire developer team? No, not at all, not yet, right.
30:38
And so, but can it augment what your team does?
30:41
Can it do code checks? Can it help find bugs?
30:44
Can it suggest improvements? Can it help those junior
30:48
developers essentially follow a better practices right and say,
30:54
well, you did forgot the comment stuff in here and you could
30:56
have, you know, put some error debugging lines in this part of
31:01
the code. But you know, to say you're
31:05
going to basically take, you know, the folks that work on at,
31:09
you know, one of the big Bing companies and just replace them
31:13
all with with AI. You know, we're not there yet.
31:16
I don't know if we'll ever be there.
31:17
Yeah, I don't know if we're ever be there because there is an
31:19
element of creativity that that and and humanness to these
31:23
things that it's going to be hard to replicate.
31:27
I'm not saying you can't. I'm not saying it's not going to
31:28
happen. I'm just saying it's going to
31:30
take a while. Well, in right now you need like
31:34
my job, I feel like interacting with some of these things is
31:38
getting the machine to be creative.
31:41
You know, it's like how creative can I be to get the most out of
31:43
the machine? And I think it spills over into
31:45
work in different ways. For example, I was recently just
31:49
dropped my daughter off at Mizzou and Mizzou is you know,
31:53
10 hours due EI mean straight. Shot east from Denver.
31:57
And so we're coming back and it this I'm an Old West fan.
32:01
So this is like AI 70 just follows that, that wagon trail,
32:05
you know, straight out. So you know, I'm, I'm chatting
32:08
with GPT and I'm like, tell me the story of Wild Bill Hickok
32:12
Hickok and Kit Carson, but use the, the, the wagon trail from
32:19
East Coast to to the the Front Range as, as like a guidepost.
32:25
Yeah, yeah. Yeah, it had like a 10 minute
32:27
story. It told me about like these
32:29
amazing forts and these like battles and the Indian wars and
32:32
all this. It was extraordinary.
32:34
So, you know, it's like the capabilities of some of these
32:37
tools, sometimes it, it's the limitation really is like, what
32:41
are you looking to get out of it?
32:43
So from a work situation, it's like, OK, I'm thinking
32:47
conventionally about how I might set up automations, but really
32:50
what I should be thinking about is like, what's the parameters
32:52
of what is even possible right now, you know?
32:55
And, and the answer to that is almost anything, right?
32:58
And that's part of what we try to get people that are
33:02
struggling with, you know, trying to bring it around full
33:04
circle here. We're, we're trying to get
33:06
people to understand and, and they haven't yet seen the
33:09
possibilities. Microsoft calls it the art of
33:11
the possibility. And once you brought the man and
33:14
started showing them some of these things, then you can see
33:17
the light bulb go off over their head and they go, oh, wait a
33:20
minute. OK, I didn't realize that, you
33:23
know, I could. I'll give you an example.
33:25
I live in a small village here outside of east out of Syracuse,
33:29
NY, and we have a lot of different historical sites.
33:32
And I know they do like historical tours in the city of
33:36
Syracuse. You can rent one of these little
33:39
players and you walk around and, you know, on your lunch hour or
33:41
whatever and you can return this thing like, well, I thought we
33:44
could do that for our little village here.
33:46
And so I, I asked it to, you know, write up a, a walking tour
33:50
of our village that would last. You know, you said they go from
33:54
point A to point B. It'll be a walking tour.
33:56
So you'd have to build the fill in the time.
33:58
And it did. It created a great narrative
34:01
about all these sites within our village that people could go to.
34:05
Now, if I take that to a notebook, LMMLMI can then
34:08
convert that to audio. I could just hand it over to the
34:11
village, you know, the municipality and say, hey, I
34:15
just created this for you. Go market it and say, you know,
34:18
if you come to come into our town, here's the little bit of
34:20
the audio tour of the things you want to see.
34:23
And so, but it's, it's kind of, you know, you need a, a certain
34:28
amount level of imagination to think of how can I use this tool
34:32
in this way? Because quite honestly, there
34:35
isn't much that can't be accomplished.
34:37
You know, on a, on a basic level that, that, that these tools
34:41
aren't able to do right, Especially since, you know,
34:43
multimodal is now in the, in the world here, right?
34:48
And being able to to actually reason about the the world
34:51
around you, not only in 2D but in 3D.
34:55
Yeah, I mean, it's so exciting. You know, it's like now thinking
34:58
about tech solutions, IT solutions is weaving in like,
35:02
what can we do? And honestly, nobody really
35:05
knows. That's another kind of fun
35:06
thing, as you hear, you know, Sam Altman's like, I don't know
35:09
what GPT 5 can do. Let's find out.
35:12
Right, Yeah, yeah, we built this thing and we are not even sure
35:15
it's because we haven't thought of all the possibilities and we.
35:20
It also keeps changing, right? If it keeps getting better and
35:23
it, you know, the, we, we, the models keep getting tuned and
35:29
fine-tuned. And at some point there's going
35:31
to probably be a shift. And you know, LLMS are not going
35:35
to be the only thing that we're going to use to be able to, to,
35:38
to have AI in our lives. I mean, it, there was AI before
35:41
LLMS, right? There will be other types of AI
35:45
after LLMS. And it'll be interesting to see
35:49
how those technologies really at the end of the day, I think it's
35:52
going to be a combination of these technologies working
35:55
together. Or you might have machine
35:57
learning doing one thing. You might have business
35:59
intelligence doing one thing. You might have, you know, an LLM
36:02
doing another thing. And together they kind of unlock
36:05
this, this what we what we assume is going to be artificial
36:10
general intelligence, which they're now calling it kind of,
36:13
we've kind of moved past it already somehow.
36:15
And now they're calling it super intelligence.
36:17
Super intelligence. What is super intelligence?
36:19
You know how? How do we know when we've
36:20
reached the Super intelligence? Yeah, I mean, open AI was able
36:25
to like really capitalize and might have been the most
36:27
explosive growth tech company has ever seen as far as
36:31
adoption, largely because they simplified just to chat.
36:36
It's just chat just bub about ask it whenever and it took off.
36:39
But to your point, like it will change, you know, do you think
36:42
the next one will be like Alexa and Siri?
36:44
Like it'll be more voice prompted.
36:47
So then when you're just talking to your robot, you know you're
36:51
pleading with them not to strangle with you, strangle you
36:53
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defining together. I I want to believe it will.
38:17
Be but I do have a little bit of a hesitation there because yes,
38:24
we've we've seen this movie before and these tech companies
38:27
have tried to get us to use voice to control our computer,
38:31
to talk to our phones. And it's been a very slow
38:35
progression, quite honestly. And maybe just because the tech
38:39
has let us down a little bit. And if we can get the voice to
38:42
be more human, more relatable, the to have to have more of a
38:49
human conversation where you can interrupt and it still keeps its
38:52
train of thought and picks up and then can interject because
38:56
human conversations don't follow a linear pathway all the time,
38:59
right? They kind of go, you know, left,
39:02
right, you know, but AI wants to do it very rationally.
39:06
And as much as that's informative and, and, and tend
39:11
be a great way to learn, it's not necessarily the way we like
39:15
to to interact with each other as human beings.
39:19
And so if someone can nail that, you know, where Alexa all of a
39:25
sudden comes on and goes, Hey, it's good to see you're home
39:29
today. Do you want to talk about
39:30
anything? You know, that's kind of creepy
39:33
yet kind of human, right? That's kind of the things that
39:37
creep us out are the things that are more are more human like.
39:40
I'm hopeful. I'm hopeful that that it will be
39:42
like I said, I'm I'm very big into home automation.
39:45
I've wanted Amazon to get. There a lot.
39:49
Sooner than they have I think they're they've really are
39:52
really missing a big opportunity and you know Sam Altman is
39:56
working with Johnny. I've now does it's not going to
39:59
take much to to to steal that Thunder really fast if they
40:03
don't get their act together soon.
40:05
Totally. I know, it's so true.
40:07
I mean, it's only a matter of time before there's a robot that
40:10
looks like Brad Pitt that will put my wife's hands in his, look
40:14
her in the eye and be like, how was your day?
40:16
And then I'll be irrelevant forever.
40:19
But then I I suppose I'll have a robot that will be like, hey,
40:22
Ryan, I know you still want to talk about robots and aliens.
40:24
You want to want to chat about that Like, yeah, actually, I
40:27
really down on the couch either. Well, that's.
40:29
You know, sci-fi theaters. Yeah, this has been awesome.
40:33
I want to go to the lightning round.
40:34
You ready for the lightning round?
40:35
Yeah, let's do it. What?
40:37
What's a? Product or a service that
40:39
Microsoft really gets right? And where are the haters of
40:43
Microsoft also, right? So I think the.
40:46
Thing that they really get right.
40:48
That they don't get enough credit for is their security
40:50
suite. If you look at the Gartner
40:52
chart, yeah, they're way out there.
40:53
They're I think, you know, cross spec has caught up with them a
40:57
little bit, but it is such a comprehensive platform that
41:01
covers all aspects of the business and it provides so much
41:07
value as well. I think is relative to some of
41:10
the other tools that are out there.
41:11
And if if you're in the M365 or the Microsoft 365 universe
41:16
already, you know, it just integrates really, really well.
41:20
Some things they don't do right. Well, I, I told you I'd use
41:24
Microsoft products my whole, you know, my whole I've I've owned a
41:26
Zune. I used to own multiple Windows
41:29
Phones. Zooms weren't awesome, by the
41:31
way. They were.
41:32
They are awesome. I had the.
41:33
Zune HD, which is just a beautifully designed product
41:37
too. Allocate the nice weight to them
41:39
I love. The Zune, Yeah.
41:42
So I think. That's really where they, they
41:44
get a lot of where they struggle is in the consumer space, not so
41:48
much on in gaming. I think they, they've done some
41:51
great things with Xbox, but you know, there's, there's, you
41:55
know, people just love their Macs and they love them because
41:57
they, they, they make them feel great, right.
42:00
When you use a Windows PC and I use Windows PCs and I have an
42:04
iPad, but they, they don't come across as warm and cuddly,
42:09
right? They come across as very
42:10
business focused and it's an area where, you know, they
42:16
continue to try and, and, and play in that space.
42:19
But to a certain extent, I think they realize that they're only
42:24
ever going to go so far. And you know, after the whole
42:27
Windows Phone debacle, they, they really said, you know what,
42:31
we're a platform company. They do do, they obviously do
42:35
devices, but that's not really their their focus anymore, you
42:39
know? Yeah, they're happy.
42:40
They're happy to make $4 billion a year on devices.
42:44
Yeah, they really. Tapped out.
42:45
I mean Apple. Ate their lunch 20 years ago
42:47
with those ads where I was like, hey, I'm Apple the cool like
42:50
young guy and then I'm PC and he has the the the ill fitting
42:54
suit. Not Hodgman.
42:55
Yeah, yeah. That's great.
42:57
Yep, Yep. OK, so let's.
43:00
Assume that you have the same vision of the future, but you're
43:03
entering college as a freshman. What would you study?
43:07
Yeah, that's a great question. I actually.
43:09
Have a, my youngest is a sophomore at Kinesis University.
43:13
And So what I would say is, and, and I actually just wrote a
43:17
LinkedIn article about this is actually, there's going to be a
43:19
couple coming out soon about the, the, the impact to position
43:25
jobs and, and roles. I would say definitely make sure
43:29
that whatever you go into cannot be disrupted by AI.
43:33
You know, there's a lot of things in the creative space
43:36
that are going to have some serious impact.
43:40
My son's girlfriend is thinking about going back to school to
43:45
taking a little bit time off to do interior design.
43:48
And I, I look at that space and I, I, I, I want to caution her
43:52
that it's important to understand the, the, the
43:55
fundamentals of design, right? But also that you better
44:01
understand the, the AI tools and technology because I, I can now
44:06
just take a picture of my living room and show, say, show me
44:08
something in the mid the mid century style and it will design
44:14
a whole living room for me. So, you know, if you have that
44:18
capability, what value are you bringing as an interior
44:21
designer? You have to figure out what you
44:23
bring to the table that the AI can't bring.
44:27
Similarly, you know, I look at things like photography.
44:32
I was on a a networking call a few weeks back with this woman
44:38
who introduced herself. She says I do corporate,
44:40
corporate headshots. Into the back of my mind I go,
44:43
why? I hope she still.
44:44
Has a job. I still hope she has a job in
44:47
three years. I mean, she's a lovely person,
44:49
but these tools are amazing. I've, I can create for $45.00 a
44:54
150 different headshots of myself and go in and modify them
44:59
on the fly and don't have to go to a photography studio and
45:04
don't have to change my outfit 15 times.
45:06
And if I put on weight or lose weight or shave my beard or take
45:09
my glasses off, I can do all of that in minutes.
45:12
And so that is extremely disruptive to that type of
45:15
business. And I wanted to say to her, we
45:17
didn't have a lot of time to, to talk, but I wanted to stay here.
45:21
Find the something else in photography that you can also do
45:24
besides corporate because that's going to go away soon.
45:29
I know. Let's see if we can with this
45:31
episode. If we can stretch the boundaries
45:34
of photo editing with ChatGPT, because we're going to, I'm
45:37
going to need to put your face on the thumbnail.
45:39
So, Jim, there you go. What?
45:40
What should I include? You want to be a superhero?
45:43
Do you want to be what? What do you want?
45:44
You want to be a punk in a punk band?
45:48
Sure. Yeah, why not?
45:49
I'll go back to my punk days. I don't, you know, unfortunately
45:52
I was, I had a very, I wouldn't say strict upbringing, but a
45:56
very conservative family. So even though I was in the punk
45:59
band, I could not look like half my other bandmates.
46:01
They had the dyed hair in the Mohawk, you know, I, I could
46:05
have long hair that was dyed black.
46:07
So that was my that was my rebellious statement there.
46:12
It's cool man, but there was probably.
46:13
An era where like the look now is kind of punk rock.
46:16
If you look at like Phil Collins, like he looked like IT
46:19
support, you know what I mean? He took the ice for sure.
46:22
Tucked into some. Khakis.
46:23
You're like, oh man, he's ready to go.
46:26
Yeah, that. Just shows you how things
46:27
things, right? That's cool.
46:32
Amazing. This has been awesome.
46:34
Jim, what's the best place for people to connect with you
46:36
online? Sure.
46:38
Yeah, absolutely. I am extremely active if you
46:41
just ask my Co workers. I'm extremely active on
46:43
LinkedIn. I post probably three articles a
46:46
week. I just started my own newsletter
46:49
called Control Alt Innovate and I do a lot of webinars for our
46:56
company. We're actually doing a, a
46:58
webinar on Windows 10 to Windows 11 using Intune in September,
47:04
September 10th. So they can go to
47:07
www.proarc.com. And pro arc is spelled PROARCH
47:13
always. Everyone always pronounces it
47:15
Pro Arch. That's on us though.
47:17
We always have to make sure we we identify that it's Pro Arc
47:21
because it stands for professional architects.
47:24
But yeah, LinkedIn is probably the best place to define me and
47:28
commenting and and absorbing all of the vast knowledge that's out
47:32
there from my peers. So yeah, you're you.
47:36
You put out. So much content which is
47:38
amazing. Why is that important to your
47:40
career? I know.
47:42
I've always liked writing. I've always, I've always felt I
47:45
had something to share. You know, I, I don't, you know,
47:49
fancy myself as a writer per SE, but I, I have a perspective that
47:54
I want to get out there and, and, you know, it's easy to, to
47:59
have those conversations with your colleagues And, and I do,
48:02
believe me, they get, they get to hear all of this stuff as
48:05
well. But I enjoy, I enjoy writing.
48:08
I enjoy putting a good argument together, you know, making a,
48:13
making a case and also getting feedback from others about, you
48:17
know, what's their perspective, Because, you know, I, I don't, I
48:21
don't subscribe to, you know, black and white, you know, this
48:23
is good, this is bad, this is right, this is wrong.
48:27
So I always want to kind of help myself grow by getting feedback
48:31
from others, by putting my thoughts out into the world and
48:34
seeing what, what everybody feels about them.
48:37
And sometimes, you know, they, they help me evolve and involve
48:42
my thinking as well. So cool.
48:45
And now to wrap things up, I wanted to see if you had a step
48:49
by step process that a founder or CEO or leader in their
48:53
organization can make when they're trying to qualify how to
48:57
begin implementing AI work, work flows.
49:01
Sure. Yeah, absolutely.
49:03
The first thing to do is to really think about your business
49:08
pretty deeply and understand the challenges and pain points that
49:14
exist within the organization. To ask yourself the question, if
49:17
we could solve for this problem, what would that mean to the
49:21
business? Could we sell more?
49:23
Could we help more people? If you're non for profit, could
49:27
we write more grants? You know, if you're a government
49:31
agency and at that point, you know, define your your business
49:35
use cases and then engage with trying to figure out where AI
49:43
can fit and actually help you with those.
49:46
And you know, that's when you can kind of start thinking
49:50
about, well, because you don't want to roll this out to your
49:52
entire organization. You know, all at once there is
49:55
an education that needs occur to occur.
49:57
There needs to be some development of those use cases
50:02
and actual Rd. mapping of how what you see, how you see those
50:07
use cases progressing over time. And you know, if you do that,
50:12
that's kind of the, the, the right way to do.
50:14
I see a lot of organizations that kind of go backward way.
50:16
They put the technology in and then they try and figure out how
50:18
to develop use cases for it. But develop the use cases, make
50:22
sure you have a solid AI usage policy that can clearly define
50:29
what is it, what is and was not acceptable.
50:32
If you're not sure just yet, you know, be very clear.
50:35
We're going to only allow this one tool for this purpose until
50:38
we get a better handle on how we're going to proceed in the
50:41
future. You also can't assume people are
50:44
going to understand how to use this technology inherently.
50:48
For some of us, we picked it up very easily.
50:51
You know, we're great communicators.
50:52
The better, the better you are communicating and and trying to
50:55
get in context across the, the more value you get out of these
50:59
tools. But not everybody does that.
51:01
You need to train them on prompting.
51:03
You need to give them the skills of how to use the tool that
51:07
they've been provided too many times.
51:08
I'm an educator, right? It came out of technology
51:11
education as an MCT for nine years.
51:15
And even admins, you can't just say, OK, here's the new version
51:18
of Windows Server. They're going to use the three
51:20
things they know how to use and they're not going to explore all
51:23
those other capabilities. So it's important that they have
51:26
a knowledge center and a hub that they can go to to look at.
51:30
And I also, I would say you have to develop someone within that
51:34
organization that's going to lead the charge, that's
51:37
passionate about it and that understands it and can be able
51:42
to, for the organization, define what success looks like, you
51:48
know, return on investment and return on value.
51:50
You don't have that. You're just going to be kind of
51:52
adrift if you, if you don't have that outsource it, right?
51:56
We've just actually created a new service, which is a virtual
52:00
chief IAI officer. So if you don't think you have
52:03
that that talent in house, hire an organization that can bring
52:07
that talent to you and help you on that journey and realize
52:11
you're not going to get return on investment right away.
52:14
It's going to take determination.
52:16
It's going to take, you know, the establishing good metrics of
52:19
things you want to actually measure for and then repeatedly
52:23
going back to your users and reinforcing this is no longer a
52:27
nice to have. It's what we are using to drive
52:31
business forward. And it's going to become part of
52:34
this workflow flow and that workflow and this workflow.
52:38
And soon you'll won't be able to distinguish, there will be very
52:41
little distinguishing between something that's produced by
52:44
your human employees and something that's been created,
52:48
Co created. I like that term better.
52:50
Co created by AI alongside of your of your employees.
52:57
Brilliant. Jim, thank you so much.
52:58
For coming on the show, Sure, no problem.
53:02
Great being here, hey? Founders, let me ask you.
53:06
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