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October 22, 2024 40 mins

In this episode of Smart Talks with IBM, Malcolm Gladwell speaks with Jason Kelley, GM, Strategic Partners and Ecosystems at IBM, and Kristy Friedrichs, SVP and Chief Partnership Officer at Palo Alto Networks. They discuss the challenges and opportunities that the rapid development of AI brings to the cybersecurity space. Jason and Kristy also underscore how implementing a zero trust strategy can help enterprises enhance cyber resiliency and simplify operations. Together, IBM and Palo Alto Networks are delivering fully integrated, open, end-to-end security solutions to enterprises.

 

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Episode Transcript

Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:04):
Welcome to tex Stuff, a production from iHeartRadio. Welcome to
tex Stuff, a production from iHeartRadio. This season on smart
Talks with IBM, Malcolm Gladwell and team are diving into
the transformative world of artificial intelligence with a fresh perspective

(00:25):
on the concept of open What does open really mean
in the context of AI. It can mean open source
code or open data, but it also encompasses fostering an
ecosystem of ideas, ensuring diverse perspectives are heard, and enabling
new levels of transparency. Join hosts from your favorite Pushkin

(00:45):
podcasts as they explore how openness in AI is reshaping industries,
driving innovation, and redefining what's possible. You'll hear from industry
experts and leaders about the implications and possibilities of open AI,
and of course, Malcolm glad Well we'll be there to
guide you through the season with his unique insights. Look
out for new episodes of Smart Talks every other week

(01:07):
on the iHeartRadio app, Apple Podcasts, or wherever you get
your podcasts, and learn more at IBM dot com slash
smart Talks.

Speaker 2 (01:18):
Hello, Hello, Welcome to Smart Talks with IBM, a podcast
from Pushkin Industries. iHeartRadio and IBM. I'm Malcolm Glappwell. This season,
we're diving back into the world of artificial intelligence, but
with a focus on the powerful concept of open its possibilities, implications,
and misconceptions. We'll look at openness from a variety of

(01:41):
angles and explore how the concept is already reshaping industries,
ways of doing business and our very notion of what's possible.
On today's episode, I'm joined by Jason Kelly, the global
managing Partner for IBM Strategic Partners and Ecosystems, and by
Christy Fredericks, the Senior Vice president and Chief Partnership Officer

(02:03):
at Palo Alto Networks. We discussed how their partnership in
a cybersecurity space helps strengthen enterprises by focusing on seamless
cybersecurity solutions tailored to meet the evolving threat landscape. By
leveraging AI and automation, this collaboration aims to modernize security programs,

(02:24):
improve response times.

Speaker 3 (02:26):
And produce risks.

Speaker 2 (02:28):
Jason and Christie both bring a tremendous amount of experience
and expertise to the subject. I think you're really going
to enjoy this one, Jason, Christy, Welcome to Smart Talks

(02:50):
with IBM. Thank you for joining me.

Speaker 3 (02:53):
Thank you, it's great to be here.

Speaker 2 (02:54):
We are here to discuss cybersecurity and the partnership between
IBM and Palo Alto net Works. But before we get there,
I wanted you guys to tell me a little bit
about yourself. Jason, let's start with you. I see on
your resume west Point, which makes we think there's some
interesting things going on there. How did you get to

(03:15):
west Point?

Speaker 3 (03:16):
West Point? West Point was the decision. First, it was
it was affordable back in the day. But I had
a sense of service. My father was a World War
Two vet, so I grew up on the weekends watching
World War two video. You know, he's army as well. Yeah,
and so I thought, oh, that'd be exciting, and I
thought I do some type of service. Went there and

(03:39):
now I have the biggest family, extended family I could
ever have. So it was very exciting. Played football lucked out,
meaning I wasn't recruited. I walked on and that kept
me there because it gave me something and out left
with all the other pressures. Defensive back I was. I
was great at knocking the ball down, not the best
at catching it.

Speaker 2 (04:00):
Yeah, and then you were a ranger.

Speaker 3 (04:04):
I was. I was privileged to be a US Army
airborne ranger station, but did most of my time in
northern Italy. We're part of the eighty second air martship post.
Oh yeah, that's what people say, seriously, like, you know
you were, you were northern. You're drinking wine and having
brad you know. But it was a part of a
NATO force there at the time. Yeah, so exciting.

Speaker 2 (04:26):
How did you get from there to IBM?

Speaker 3 (04:30):
A long path. As I came out of the military,
I started manufacturing retail housing and did a quick stint,
took a leave of absence from industry and did a
stint of yet again public service in the state of
Tennessee with economic development, and got a whiff of how

(04:53):
fun it could be to do things around data and media.
Started a small media firm what we would now call firm,
sold it, and so I wanted to go do it
again somewhere, but I want to go to a big company.
And the family at IBM brought me in and yet
to let me go.

Speaker 2 (05:11):
That was how many years ago, two decades?

Speaker 3 (05:16):
So I know I look amazingly young, but yes, you
must have and IBM was my fifth career, and and
and and I've I've enjoyed a since and that's what
I what I do. They build teams, grow new parts
of the company, and get to work with some of
the most brilliant people on the face of the planet,
as well as partners like like Christy that just keep

(05:37):
it exciting.

Speaker 2 (05:37):
Christy, you're I was delighted to learn that you are Canadian?
Yes here, yeah, But you so you were a consultant
for a long time a Bane Yes.

Speaker 4 (05:48):
Yeah. I joined Baine Consulting intending to spend a couple
of years there learn the ropes and then go get
my first real job. But the value personally to my
growth and development, and then that we were able to
bring our clients. I ended up there for sixteen years,
and then post Bain went on to another my first
product company, a new Relic, and then it's come full
circle at Polota Networks. But at Bain it was all

(06:11):
about bringing expertise across different industries to help our clients
improve whatever they needed to improve and bringing that expertise
to bear. And then you have the product lens and
you think, okay, we're going to build the absolute best
product to help our customers do what they need to
get done. And then I joined pal Alto about six
seven months ago in a partnerships role and I'm delighted

(06:33):
to be able to work with amazing consulting companies like
IBM where we bring both to bear.

Speaker 2 (06:37):
How long have IBM and Polo Alto Network's been partners?

Speaker 3 (06:41):
So we've we've been working together for quite quite a
long time, but we made it official, meaning we got
married as strategic partners last year.

Speaker 2 (06:50):
Oh I see, So what is it that each of
you bring to the table? What's each side special?

Speaker 3 (06:55):
So it's great that you asked that because it's about
a decade ago. Are now CEO Arvin Christen says, you know,
it wouldn't be great if we just had this one
focus with what does IBM do? And you have this
whole list, and he says, let's make it simple. We
are a multi cloud, hybrid cloud AI company. And so
when you say that, it sounds very simple, but then people,

(07:19):
what the hell is that? What your hybrid cloud? Well,
both of those two things have a lot of data involved,
and a lot of those mean that that data is
going to sit in multiple places and distributed environments. Well,
if you're able to tie those things together with multiple partners,
you also have to make sure that it's secure because

(07:40):
in the direction that we're going, where data is now
being consumed in many different places and it is the
fuel behind AI as we know, then you say, ah, well,
who does that well and who does it in a
way that's getting rid of seams, the seams that could
be across multiple products, multiple product SATs even And that's

(08:00):
where Powell comes in.

Speaker 4 (08:02):
I think the conventional wisdom in cybersecurity was always you
need all the new tools, right, you need it every threat.
It's like, whack them all. Every threat that pops up,
you get the tool that's purpose built for that specific thing. Well,
fast forward to the RSA conference this year. There were
four thousand vendors on the floor. You look at an
average company, there's hundreds of cybersecurity tools. It introduces a

(08:25):
level of complexity that is really hard to manage. You
as a user, query and application, right, that query can
go through a bunch of different pings from one cloud
to the next, It goes into and out of assaas application,
it may be running along a network, you may be
accessing it from your phone, which is an unmanaged device.

(08:45):
It's got to go in and out. And if you say, okay,
I've got to secure that phone, I've got to secure
the network, I've got it. Then all of a sudden
you've got sort of firewalls, software and hardwell flows popping
up everywhere. You've got cloud security, and it's you've probably
heard of this concept of zero trust, which is every
time you have to check and say are you allowed
in here? Are you allowed in here? The number of
places that can fall down it just becomes overwhelming. So

(09:08):
you end up with either alerts firing, you know, every
two seconds that you have to then go investigate in
most of which are false positives or you miss something right.
And so that was the conventionalism was we've got to
buy all these tools and now you've got overwhelmed CIOs
and CISOs with hundreds of tools. And Palo Alto strategy
has been, Look, we're going to create a platform where

(09:30):
everything can be stitched together, everything can speak the same language,
and we can sort of manage throughout the architecture and watch,
you know, this call as as it's passing through all
these different checkpoints, and we can do it in a
way that you still have the confidence that it's best
to breed right, so you're not making any trade offs.
But it's not so simple just to get from the

(09:51):
spaghetti to the seamless architecture. You need, oftentimes to re
engineer your business processes. You have to re architect your
digital environment. And so that's where we partner with a
company like IBM to bring that expertise and say, we're
going to help you not just deploy the best cybersecurity architecture,
but really get your environment ready to have this zero.

Speaker 3 (10:11):
Customers as well as all of those players that cross
that spaghetti, because you start thinking about all the other
partners that you work with. If you're you think of
an industry perspective, you're going to have an ERP. It
could be an Oracle, it could be an SAP. You're
not going to have one cloud, as I mentioned, it's
going to be possibly multiple clouds. You'll have some aws
maybe Microsoft Asure and then even even some Google in there,

(10:34):
and then your own that you've built in your private
over there, uh, IBM, some inn IBM cloud. You'll have
those multiple clouds, and then you also will have you know,
fit for purpose, Oh I need a I need a
salesforce in there for my customer focusing I need. I'm
doing some graphics, so I have Adobe, so I just
as I can name name name, all of those then

(10:56):
have to be re engineered. Seriously. I mean, Malcolm, you're
gonna sit there you think how long that would take.
So if you haven't done that before, you're going to
have to go to each one of those individually, or
you can work with a company that can tie those
things together, because we are also strategic partners with them.
So that's where you start to say, Okay, I see

(11:18):
how this comes together. You have to make sure that
your ecosystem is going to be stronger than your competitor's ecosystem,
and you have to be secure in what you're doing
because as you add more players or products, you create seams,
and you want to make sure there's fewer seams and
that there's zero trust across that capability you're building. And

(11:40):
that's why the compliment between the two companies.

Speaker 2 (11:43):
We'll take a step back from a moment before we
sort of launch once get into the specifics of what
you guys are doing. I'm curious at this moment in
twenty twenty four, how nervous should we be about cybersecurity?
So compared to five years ago or ten years ago,

(12:03):
are we are you less nervous than you were five
years ago or more nervous or all of changes going
on right now increasing vulnerability or decreasing it?

Speaker 3 (12:12):
I would say Christy also, I think we share the
point of view is that it's not necessarily being more nervous.
I think you should be more prepared because the amounts
of threat is increasing based on our dependence upon data.
And that's that's where I think the attention should be placed.

(12:35):
Is that more and more, especially with the importance of AI,
that you say, okay, then what's under all that? And
it's the data? As I said, So knowing that you
should be more concerned.

Speaker 2 (12:49):
Does the advent of AI and its rapid evolution help
defense more or offense more?

Speaker 4 (12:56):
I think it's I think it's like any mega trend
that we've witnessed both. Right, So you think about AI,
it's ninety nine percent great right in terms of what
it's going to unlock for productivity, for humanity, But it
also makes it a whole lot easier to build ransomware.
It's a whole lot easier to test different ways into

(13:16):
a system, right. But I think that's true if you
think about like the rise of the Internet, right all
of a sudden, everyone was putting their data online and
you had to think of new ways to stay ahead
and keep that secure. And I don't think AI is
any different. You've got companies like Palta, partnerships like Powell
and IBM that are constantly scanning the landscape for not

(13:37):
only the current threats, but what's next, what's coming around
the corner, what's after AI? And so I think taking
it seriously and being prepared is probably the right way
of looking at it, as opposed to because if you
think about it too hard, you'll just want to crawl
into a corner and stuff everything under the mattress.

Speaker 2 (13:54):
I am the CEO of a regional h spital chain,
big distributed healthcare system, so a ton of data. The
consequences of being hacked and help for ransom are.

Speaker 4 (14:10):
Life and death.

Speaker 2 (14:10):
Life and death littally when you come so you come down,
you sit down with me, and you chat with me,
walk me through the kinds of things you would tell
me about what I need to get safer. For example,
let's start with one. Is it likely that I'm spending
too little or am I spending money in the wrong place?

Speaker 4 (14:30):
Great question, It depends how you've broken it out. If
you are distributing all of your dollars across a whole
bunch of different tools, it's likely you're just spending the
wrong money. And in fact, you know, putting it all
in one place is a way of potentially saving money
but keeping your security actually higher. And I'd love to
hear Jason, how you would approach it. How we would

(14:51):
approach it, of course, is by saying, you know, what,
what does your environment look like? You know, do you
have the connected medical devices into your EMR? Are your
respirators and ventilators all online? Right? And so we would
talk about, okay, here's how you get coverage and how
the coverage of both the firewalls as well as the
detectors all feedback into your security operation center and you

(15:13):
can manage it and do your learning with AI and
keep yourself securing.

Speaker 3 (15:18):
So yeah, and I would say Christy and I would
go to the same point because if you get under
what she was just asking, it is your data on
prem and when it's on prem, how active is it
across the enterprise, and so that begins the basis for
the start. And then often you're going to say, well,
we actually take in data from outside and then we

(15:40):
also have the circumstances. There's a lot of PII and
so that personal is the personal information, right, Yeah, And
so now you're saying, okay, now how are we securing
that and where are we securing it? And so you
have to start really thinking about the different areas within
that hospital chain. Are you sharing that amongst your hospitals?

(16:04):
And now you start to think of if I'm saying
no to a lot of that, it's like, well, then
are you as efficient as you want to be? So
there is that trade off of you know, am I
so tightly walled that I'm not productive? And so that's
where we would start to say, what's the outcome that
you're trying to get to? Right, Maybe you're good, Maybe

(16:24):
you're you're good with your five locations and you don't
need to go any further, but maybe you want to
expand to fifty and by the way, you're going to
go crossporder, you're going to be in Toronto and in
New York. Okay, well, then how do you do that?
And so I think that it's very easy to start
jumping into any of the typical situations. But the first

(16:45):
question that you have to ask you, as the hospital CEOs,
what's your objective? What are you what are you trying
to do? Because too often what we see is that
there's some bright, new, shiny thing that everybody wants to
put in play. You know, it's a sandwich looking for
lunch and you go, but what is it that you
want to do as this Are you doing research? Are

(17:08):
your research hospital? Are you more consumer oriented? So those
are the questions you start to ask because they start
to then tell a story in line with what Christy questions.
And I think that that's where the again the compliment
is that instead of just saying, oh, well, that's thanks
for telling me all this, Malcolm, here's your ten page strategy,
go find somebody. We have the benefit in IBM, and

(17:32):
it's probably why I'm still there is you know, we're
very unique. We're the only company on the planet that
has a consulting business at scale inside of a technology company,
and so we have, you know, the left brain, right brain.
We're able to do that and then we're able to
say okay now, which partners are going to be most

(17:52):
valuable for our clients. What's going to work for you
isn't going to work for the manufacturer down the road,
isn't going to work for the consumer or CpG company
across the river. Those things are very specific. The threats
and the scenes that I was talking about are very specific.
So that's where it becomes very valuable to make sure
that I'm not just giving you some strategy that's generic.

Speaker 2 (18:17):
But everything. As a healthcare CEO, everything I have done,
almost everything I've done over the last ten years, has
it had the effect of increasing my vulnerability. I want
to digitize data within the hospital used to be on
pieces of paper. I want doctors to go home and
to be able to seamlessly hook into stuff at work
because they got to do all their paperwork. I want

(18:39):
to make sure the diabetes people are speaking to the
organ transplant people. And so isn't that everything I have
done to kind of keep up with the revolution in healthcare?
Isn't that also making me more and more vulnerable to
a bad actor.

Speaker 4 (18:53):
It's such a great question because think about the quality
of healthcare delivery right, So, now doctors aren't filling out
forms they're spending time with pay and so the quality
of care is improving and the vulnerability is improving, right,
And so I think that's where having a strong cybersecurity
strategy actually enables all of that. One of our products
is our sas product, and we tested it with some

(19:13):
business applications, and oftentimes the wrap is, oh, security is
going to slow you down, right, Like you have to
add a firewall, you have to checkpoints. Our product actually
increases the velocity of your ability to use that application
because of the way that it is queried through our
system as opposed to just through the regular network. So
it doesn't slow it down and in fact, it makes
it run more efficiently. That's just one minor example. But

(19:38):
back to the healthcare question. I, as a patient want
my doctors accessing all the technology and talking to each
other and connecting the dots behind the scenes. I also
want my data to stay private, and so having both
a consulting partner who understands how to ask questions of
the environment and of the applications you're using, and who
understands the industry inside and out, and a technology part

(20:00):
that builds and stays ahead of all of the different
threats come together and advise you. I think is super important.
When you bring in a partner like IBM, with a
platform like pal Alta that covers, you know, all the
different parts of your environment, you're able to say, look,
where where are the vulnerabilities in the system, Where are

(20:21):
the different endpoints that we need to have covered, and
then just make sure you get that breadth of coverage
and then you're better able to so, yes, you've increased
the risk, but then you've mitigated it.

Speaker 2 (20:31):
So to give so before I retire my healthcare analogy,
because I was thinking about just trying to understand the
importance of this idea of having a single platform. So
if this muddle healthcare network is typical, I've acquired a
whole series of over the last ten years. I bought
a hospital over here, some I've got some physicians things

(20:53):
that I snapped up over here about a diagnostics company,
and so I have all of these legacy systems and
I had, like you said, maybe I got some stuff
in the cloud with one company, some stuff with the cloud.
And what you're saying is the first step is to
kind of rationalize that put it on a single platform
so you understand where your points of weakness are as

(21:15):
opposed to being blind to your points of weakness.

Speaker 4 (21:18):
There's yes, although anyone who's done any kind of M
and A knows that that's a long journey, right. So
I think the first step is just understanding where everything is.
And then you get on a path and you say,
where's the biggest risk. Let's let's neutralize or mitigate that
risk one at a time. The thing about open end Secure,

(21:39):
you know Palo Alto. We keep touting the benefits of
the platform. Everything on Palo Alto. Your risk is going
to be mitigated and you're going to have the full visibility.
But you can't get there overnight. And so we've got
you know, thousands of integrations with other technology companies, including
our partners, to make sure that we can capture and
have visibility into those those endpoints and those systems as well.

(22:01):
And so I think step one is just figure out
where everything is. Just get the scan, so politize a
couple of products where you can kind of deploy and
get a view of your attack surface. I love the analogy.
Just like a digital environment is a house, right, and
so like you have your front door log. Of course,
because probably they're going to try the front door first,
But that's not all you're going to do, right, You're
going to make sure the whole you know, the windows

(22:21):
are locked and there's an alarm system and all of that.
And I think that's how you have to think about it,
is just how do we cover the whole service?

Speaker 2 (22:29):
So everyone lay people like me have been bombarded over
it seems like over the last year with one thing
another about how quickly AI is moving forward and how
big of a deal it is suddenly is going to
be in the economy. What is the impact of that
dramatic change in AI's capabilities on this cybersecurity question? So

(22:52):
what does it mean if you're defending somebody that you
now have these sophisticated AI tools you suppose?

Speaker 3 (22:59):
I think that becomes the force multiplier for cyber to
think about cyber Before it was just locking your doors,
locking the windows, and if you were really good, you
had an alarm system.

Speaker 4 (23:14):
You know.

Speaker 3 (23:16):
Now with AI, you can say, well, I can predict
what's going to happen. I can see around the corner.
I know, I can leave my windows open upstairs and
it's fine, and it's okay.

Speaker 2 (23:27):
I mean, because why because the AI is running a
million simulations.

Speaker 3 (23:31):
It can, and that's exactly it. It becomes the intelligent
part of that AI. It's not artificial, it's augmented. So
you now have this new capability to see around corners
and so you're able to do the jobs of yesterday
more effectively. And the queries that you were doing, and

(23:52):
that's all you're really doing, now you're doing them, you know, faster,
You're able to access even more data and you're able
to to then make it more secure. So that's why
AI becomes a force multiplier.

Speaker 2 (24:06):
Yeah, and just talk about the faster part. What does
faster mean in practical terms? If you're trying to defend
an enterprise against a cyber attack, what does speed matter
in that environment?

Speaker 3 (24:18):
You're always trying to find a place through I go
back to you. We brought up the army. You always
how do you break the line? How do you find
a penetration point? And when you think about you know,
pin testing, penetration testing, where are those? So if you're
able to do that faster than the bad guys, and
not only faster, but you're picking more probable points. This

(24:39):
is back to the intelligence. I could waste time doing
penetration testing someplace where. That's why I mentioned leave. If
they can't get in the second story windows, why are
you spending time trying it? So that becomes more effective.
So that's when I think of speed. That's what I
think of because with not just speed, I think it's
also what's effective.

Speaker 4 (25:00):
Put a fine point on it. So I found a
way in. Okay, Now what I don't know where the
jewelry is, so I have to look around and see
if there's any hidden gems and try to find my way.
That used to take a week, two weeks sort of
seven to fourteen days. Now it's hours, right, So they're
in and they can actually expeltrate data within less than
a day. The metric we use in the security operation

(25:21):
Center is meantime to detect, so to see anyone's there,
meantime to respond and remediate to get them out right.
That used to be also you know, seven eight, nine,
ten days. Now it needs to be less than an hour,
and with our AI based security operations platform, it is.
Now you've got one tool that's whether it's all peloton

(25:42):
networks or whether it's just you know, hoofringing data from
other places, then you're able to see it all together,
so you actually get fewer alerts. So you get from
thousands of alerts down to one hundred alerts, right, and
you can investigate them and you investigate them using AI too.
And AI is is today it's today's threat, but it's
you know, you think about an opportunity to think about
what's next. You always have to be kind of evolving.

Speaker 3 (26:03):
And you have to think. We talk about threat and risk,
and you know, we didn't tell you know, what is
the cost of cyber some type of penetration. It's typical
costs is about four and a half million dollars and
that's just in labor and remediation. If you think about
reputational risk as well, our Institute for Business value to

(26:26):
the study and found it in twenty twenty three and
they were thirty nine banks that we watched that suffered
a reputational risk market value of one hundred and thirty
billion dollars. And so you start to think, wow, that's
just reputational risk. So that's what's at stake here, and
it's only that is only going to get bigger.

Speaker 4 (26:49):
So one of the piece we haven't talked about about
AI that I find super interesting because we've been talking
essentially about like the terminator, the robots fighting robots, right,
Like whose robots are quicker? Like I'm designing attacks and
I'm defending against attacks, and I think that's that's super important.
But we recently launch and our working at IBM on
our AI security product to actually secure the use of

(27:10):
ALI because it also opens up another set of threat factors.
I'll give you an example. I'm a marketing executive now
for your hospital. So I work for you, and you
want to announce the launch of a new center, and
so I upload all the information about all the patients
and our you know how we do things into chat
GPT to write the PR for me. Well, I've also

(27:30):
just uploaded to chat GPT a whole bunch of secrets, right.
So it's how employees are using AI because I think,
you know, some companies are sort of building their own
language models and their own AI applications that they want
to keep secure. Others are just curious about how their
employees are using AI applications on the shelf, and so
we announced in May a product where you can actually

(27:51):
scan and see how AI is being used in your
enterprise and within we made the announcement with the GA
was last month, but we made the announcement in May
and we had immediately thousands of CIOs signing up because
just understanding you know who's using what it's another open
question because you know, we talk about AI enhancing productivity
and all the benefits it's going to bring, but it
brings it brings risks, not just in how it's being

(28:13):
used by the thread actors, but also you know what
other vulnerabilities.

Speaker 2 (28:17):
That exc It's the eye that you does that system
tell you what's a problematic use.

Speaker 4 (28:24):
It does, so what what it does, and you've got
to train it right. But what it does is say
this is this is outside of your policy. So CIOs
will set policies on here's what is acceptable and not
acceptable use. So we'll be able to scan and say
these these falling uses are outside of policy, and then
it'll punt and say I think this is too restrictive,
I think this is too permissive, and then you can
sort of update your policies from there. That's just sort

(28:45):
of the visibility piece, and then there's the run time piece,
which will actually stop you from using it. So you
go and say, okay, here's all my patient's social security numbers.
I'm going to upload them to chat GPT to you know,
get an understanding of like where they all live. I
don't know what why you were possibly do that, but
let's say you are and then you know it. Don't
note that looks like a social security number. You can
upload that into your prompt so.

Speaker 2 (29:06):
It will stop you before you Yeah, thoughtful voice over
your shoulder, just to remind you not to do something
silly exactly. But this is just talk a little bit
more about adding AI into this mix. You say it's
a force multiplier. It's really interesting dig into that. What
other other instances of what that means? How does the

(29:29):
balance between AI and human expertise work in the kind
of next generation of cybersecurity?

Speaker 3 (29:38):
I think the the common way to look at as
it back to the force multipliers, It's not going to
be is your AI better? But can you use it better?
Can you ask your AI the right questions? Are you
well trained? So the competition really becomes your use of AI?
And are you pointed it in the right direction? You

(30:00):
have fifty people, can they do the work of two
hundred and fifty? And can they do it in a
safe and secure manner? So you're not opening up more
risk based on or too much risk is your risk
tolerance in order to get the outcome. So that's why
I think there's the opportunity. And so you see this
truly as a force multiplier because the first thing people go, oh,

(30:22):
you're going to get rid of people, Oh, the people
portion is still still going to be just as important
because they're doing that other piece of work.

Speaker 4 (30:30):
One of my favorite statistics is that there are now
more bank tellers in the US than there were in
nineteen sixty before the ATM was invented. Right, So, but
it used to be you would go to your bank
because you had to. I remember doing this. You go,
you fill out your deposit slip, you hand it to
the teller and they give you your cash. And then
ATMs are invented, and it's like, oh no, what's going
to happen all these jobs and now there's more, Right,

(30:51):
but you're not withdrawing money from a bank teller. You're
now doing more sophisticated transactions. And so I think it's
similar with AI. Right, you want people doing things that only.

Speaker 2 (31:01):
People can do. The human element remains absolutely central in
all of this. How do you make sure that your
cybersecurity folks are equipped to handle high value tasks, are
ready for this increasing responsibility.

Speaker 4 (31:17):
There's a couple of ways to answer this, but I
think the more you're able to automate the routine and
the mundane tasks. For example, the bulk of cybersecurity happens
in the security operations center. There's analysts who are sitting
in that center. If they're spending all day either configuring
alerts or responding to alerts, they're not able to do

(31:38):
the advanced sort of threat hunting and analysis work. And
so I think a big chunk of it is just
freeing up their time to be able to do the
more advanced strategic work. And a lot of the automation
tools based on AI, like our cortex XIM product, is
it's designed to free up their time in order to
be able to do that.

Speaker 3 (31:56):
And from our perspective, is making sure that it's a
requirement to make sure that you have the qualifications because
people can easily get used to doing what they've always done.
I know this, and that's that's what I do. You say, Well, no,
all the threat actors are learning on fly. They're trying
to always outsmart you, so it's in your best interest,

(32:18):
our best interest, our client's best and partners best and
that you are on the front leaning edge of that
learning capability.

Speaker 2 (32:26):
If you're talking to a client he once to develop
a kind of unified cybersecurity strategy. What's the best single
piece of advice you can give them?

Speaker 4 (32:37):
You should have a single platform. It's hard not to
answer that, but it is true. I mean all joking
aside having you know the best of breed solutions that
are all talking to each other and able to stitch
together and identify threats before human might be able to.
That's number one, and number two is making sure you
have visibility on all elements so you're able to cover

(33:00):
or your whole environment and understand how people are accessing it.

Speaker 3 (33:03):
I'd say think like a bad actor. Yeah, always think
outside in because you get comfortable the other way around.

Speaker 2 (33:12):
You guys work together with a forshing envioutrial company, and
I'd love for you to talk a little bit about
use that as a kind of case study for what
this collaboration between the two your two companies looks like.
When you work with a cloud.

Speaker 4 (33:27):
It really was, you know, IBM leading on a digital
transformation for this client that wanted to move their applications
into the cloud, and so you're asking a lot of
questions about how does AI increase the risk and the
surface area. Those same questions ten years ago were asked
about the cloud, and we're still on the journey where
companies are migrating to the cloud. We're not anywhere near
finished that yet. And so there's two pieces to a

(33:48):
cloud migration. One is just refactoring for the cloud to
make sure the application works effectively in the cloud. And
the second is security. And then you built in security
by design using power does prison of cloud products to
make sure that not only did you have the visibility
so our cloud product you can scan and see where
the vulnerabilities are. And then there's also you know, cloud
firewalls essentially that will keep bad actors out and keep

(34:11):
the cloud instant secure.

Speaker 2 (34:13):
If we sit down and have this conversation five years
from now, which I actually hope we do, be fun,
pretend is twenty twenty nine. Tell me what are you
happy about in twenty twenty nine, And.

Speaker 3 (34:26):
I think twenty twenty nine quantum computing is mainstream. I
think quantum computing is now quantum safe, where we're using
quantum computing to make sure that those bad actors aren't
as bad as they used to be back in twenty
twenty four, and that we're seeing around the corners and

(34:50):
that we're empowering our Palo Alto relationship. That in twenty
twenty nine is the premiere type of capability that that
people are looking at when they think of what used
to be AI and now is quantum capability?

Speaker 2 (35:06):
Yeah, yeah, I think.

Speaker 4 (35:09):
For AI, everyone's just using it as part of their job.
The way email was an innovation in the nineties, the
way you know cloud was an innovation in the twenty tens,
and we thought, how are we going to use this?
What impact is it going to have on productivity? All
these people who are spending their days typing up memos,
like what are they going to do? We're going to
be past that fear and we're all going to understand

(35:30):
that it is this like truly positive force multiplier. For
you know, every employee is able to do their best
work and spend their time on the things that only
they can do, and then the AI is doing the
rest of that for them.

Speaker 3 (35:43):
Right, AI, it's fun to enable many things to work together.
It won't be just one language model. We won't even
think about. It will be the difference between you know,
Malcolm having a fax machine, stereo and a telephone and
a memo board. Now it's in your pocket and it's

(36:03):
all one thing and you don't even call that, you know.
I said, walk them into my kids the other day
and they're like, what's a walk man? So I do
think it will. It'll be part of the past and
it's it will be the thought of the seamless connection.
That is secure, seamless connection, of HR, of finance, of distribution, logistics,
of billing, all of those will have a capability to

(36:27):
work together. Yeah.

Speaker 2 (36:30):
I have to do some social quick fire questions you
guys ready, all right? What's the number one thing that
people misunderstand about AI?

Speaker 3 (36:39):
The reliance on data? What do you mean by that?
I think that it's just assumed that it's happening and
it can just go out and grab data anywhere. Yeah,
you have to have good data, reliable data, and access
to the data.

Speaker 4 (36:55):
I mean people are too afraid of it.

Speaker 2 (36:57):
Checkbox and image generators are the biggest thing as consumer
AI right now. What do you think is the next
big business application? Jason?

Speaker 3 (37:04):
I think it's the tying together of multiple capabilities. I'm
hinted towards this earlier that I think tying together the
disparate systems that sit in different parts of the organization
front office, back office, making it one office and tying
together those different functions, that's it.

Speaker 4 (37:19):
I mean, it's workflow automation. I think back to your
point on the reliance on data seems easy. It's a
lot harder than you think, because you have to have
everything set up in exactly the right way to get
all of your systems automated and the sort of the
more boring jobs taken care of so that humans could
do the strategic ones.

Speaker 2 (37:36):
How are you already using AI in your day to
day life?

Speaker 4 (37:41):
I mean I use it at work all the time,
and then I've found right now I go to chat,
GPT instead of Google to look things up. I like
having a conversation.

Speaker 3 (37:52):
We have a wonderful capability in our consulting business called
our consulting the system and insulting advantage is the proper
name for it. But I look at it as that
assistant and it's a force multiplier for me. So if
I need to pull together content proposals with the teams.
We go straight to that we.

Speaker 2 (38:13):
Are one more. We hear so many definitions of open
related to technology. How do you define it and how
does the concept help you innovate?

Speaker 4 (38:22):
By definition? In cybersecurity, you don't want to be too open, right,
So I think we enable openness with this concept of
zero trust and saying like everyone's invited in as long
as you have the right credentials, right. So that's one way,
and then the other way is just making sure you're
connected to all the different systems in order to be
able to have that visibility and see what's happening. Because

(38:43):
if you are blind, that's the minute you have that vulnerability.

Speaker 3 (38:47):
Yeah, and I'd say it's moving quickly with security, it
sounds contradictory open. Oh, then it means you're not safe. No,
you are safe and you can move faster. Yeah.

Speaker 2 (39:00):
Thank you so much. It's fun.

Speaker 4 (39:01):
Thanks a lot, Thank you. Great. We'll see you in
five years.

Speaker 2 (39:04):
In five years, man, I'll be old in five years.
Thank you to Jason Kelly at IBM and Christy Fredericks
at Palo Alto Networks for that fascinating conversation about the
threats and opportunities in cybersecurity today. As Jason and Christie stressed,

(39:24):
AI can be a force multiplier for enterprise across industries.
When you're working with multiple products and have your data
in distributed environments, you need technology that will work across
your organization, and with Palo Alto Networks platform, you can
enhance cyber resiliency and simplify your operations. Through their collaboration,

(39:48):
IBM and Palo Alto Networks are charting the future a
fully integrated open, end to end security solutions. Smart Talks
with IBM is pretty by Matt Romano, Joey Fishground, Amy
Gains McQuaid, and Jacob Goldstein. We're edited by Lydia Jan Kott.
Our engineers are Sarah Brugaer and Ben Tolliday. Theme song

(40:11):
by Gramoscope Special thanks to the eight Bar and IBM teams,
as well as the Pushkin marketing team. Smart Talk with
IBM is a production of Pushkin Industries and Ruby Studio
at iHeartMedia. To find more Pushkin podcasts, listen on the
iHeartRadio app, Apple Podcasts, or wherever you listen to podcasts.

(40:32):
I'm Malcolm Glaphom. This is a paid advertisement from IBM.
The conversations on this podcast don't necessarily represent IBM's positions, strategies,
or opinions.

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