December 2, 2025 • 12 mins
Cybersecurity giant Zscaler is a pioneer and global leader in zero trust security. Many of the world’s largest businesses, critical infrastructure organizations, and government agencies rely on Zscaler to secure users, branches, applications, data & devices, and to accelerate digital transformation initiatives.
The company says its "Zero Trust Exchange" platform is distributed across 160+ data centers globally, and combines with advanced AI to help combat billions of cyber threats and policy violations every day
Jay Chaudhry, Zscaler's Founder, Chairman and CEO, discusses his firm's most recent earnings as well as the landscape for cybersecurity as a service.
Jay speaks with Carol Massar, Tim Stenovec, and Mandeep Singh, the Global Head of Technology Research for Bloomberg Intelligence, on Bloomberg Businessweek Daily.
See omnystudio.com/listener for privacy information.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2 (00:07):
You're listening to Bloomberg Business Week with Carol Masser and
Tim Stenovek on Bloomberg Radio.
Speaker 3 (00:14):
Shares of the more than thirty nine billion dollar cloud
security and software companies z Scaler are easily outperforming both
the S and P five hundred and Nasdaq one hundred today.
The stock is up nearly forty percent year to date,
and yet we did see shares under pressure today, dropping
nearly four percent after Bernstein downgraded the software company to
market perform from outperform on growth concerns. Bernstein, by the way,
(00:36):
setting its price target on the stock to two sixty
for a share. That's a five percent increase from the
Friday close. I should put out that initially Bernstein when
the company reported earnings last week, they initially maintained their
outperform rating. So there's been a lot of movement allis
in general, tim a flurry of them weighing in, some
raising their price targets on the stock, others lowering them.
(00:58):
And we should point out the stock did drop about
thirteen percent last week. That was on Wednesday following their earnings.
Speaker 1 (01:04):
Yeah, the forecast was annual revenue that was only slightly
above estimates from one of the company were joined by
Jay Chawdry, founder, chairman and CEO of z Scaler. He
joins us from San Diego, also San Jose. Excuse me
also with us as somebody who knows this company very well,
Bloomberg Intelligence's global head of Tech research, Man Deep saying,
he joins us here in the studio, Jay, I just
(01:25):
want to start with you the growth concerns, the disappointment
over the annual revenue forecast that was only slightly above estimates.
Speaker 2 (01:31):
Is growth slowing, not at all. We had an outstanding quarter.
Our AIRR growth twenty six percent, revenue growth twenty six percent,
free cash flow margin fifty two percent, operating margin twenty
two percent. We beat all the metrics that Wall Street
was looking for. In fact, if you take our free
(01:54):
cash flow margin and add it to our revenue growth,
that's seventy eight percent. That beats the rule of forty
that many investors look for very very well. And this
is at scale of three billion dollars or higher. There
are only about five pure play enterprise SaaS companies that
are in that unique class, So you're done extremely well.
(02:17):
We are very proud of what we delivered and be
passed a meaningful beat. We did and raised our annual target,
So I think we're very pleased with it. I think
investors get it wrong from time to time. This is
one of those times.
Speaker 3 (02:33):
That's what's going to ask you know what, do you
think investors just got it wrong? Because I mean, thirteen
percent is a pretty big hit, So you think, I mean,
that's not like them wavering at all. They really wanted
more from you guys. I mean the expectations were certainly high.
Speaker 2 (02:48):
Look, markets do what they do. I have one focus,
keep on innovating and serving our customers. And those innovations
started with zero trust architecture with a chained the world
of old school firewalls and VPNs. And now as AI
security is coming, a security is becoming a big concern
(03:09):
and zero trust that we pioneered is the foundation of it.
So we have amazing interest from our customers. That's why
we're able to deliver these strong numbers. Over forty five
percent Fortune five hundred companies trust us, depend upon us,
so I'm very bolish about our future.
Speaker 4 (03:27):
So talking about AI security, I mean, you have a
business model that's reliant on companies hiring more people and
you have a C based model, how does that change
with AI security? Because AI, you know what we are
seeing out there is more consumption based. So how does
that impact you and your business?
Speaker 2 (03:48):
It's a good question. So we started out with bringing
zero trust for users, so users can access applications without
being on the company network, and natural pricing for that
is user based. Then we move the model to our architecture.
The next thing, how about zero trust communication for workloads
(04:09):
cloud workloads that's actually based on number of workloads and
actually mount traffic, so it's not just user based. If
you think about AI security, there are many facets of
a security well. One of the biggest thing our customers
look for is as every company starts using a lot
of agents. These agents are some like people. They need
(04:33):
to access their applications, they need to talk to other agents.
So we are extending our zero trust exchange that are
designed for users and workloads and branches now to agentic
exchange so that right agent can talk to right agent
and right application. So obviously there's an opportunity for us
(04:54):
to secure that communication. Yes, the number of users may
not grow significantly, but I believe every company will have
scores of agents for every single employee and they need
to be secured and we are extremely well positioned to
handle that.
Speaker 4 (05:11):
And talking about agents, it sounds like one of your
biggest competitors is doubling down on observability and identity, especially
on the browser side. As an area of focus for
agent Tachai is that something you feel is very important
to roll out the agents.
Speaker 2 (05:30):
So some companies try to go and buy many companies
to create a collection of things. We are very focused
on what we want. We are focused on zero trust
and then we focused on AI. Regarding observability, we actually
do observability for the areas that matter to our customers.
(05:53):
We sit between the user and the application. So today
we have a size business, hundreds of millions of dollar
business with the product we call z Skinnar Digital Experience,
where we can tell our customers if any user is
having any performance issues as they try to access those applications.
It's integrated with a platform. While many companies have many
(06:18):
point products and they are separate, we like to have
integrated platform that serves our customers. So we not only
provide secure and reliable experience, we make sure that it
is fast and you can trouble shoot those things. But
I'm not going into broad observability, which has become a
(06:38):
broad area. We are focused on the areas that are
relevant to our customers.
Speaker 4 (06:44):
And identity is that something you care about? The identity
on the browser.
Speaker 2 (06:49):
Identity is important. Think about identity for users. We have
been working from day one with all leading ID provider
for users or whether it's Microsoft and oct and others. Now,
when it comes to identity of agents, I believe there'll
be many contenders Microsoft, Google, Aws octors of the world.
(07:14):
Our philosophy is to federate those identity providers use that
identity and we are the zero trust exchange, the switchboard
to make sure the right AI agent talks to right
agent in this world. I do not need to own everything.
I need to do some of the things I do
the best and integrate with partners with proper API integration
(07:38):
so our customers get the biggest benefit. We believe in
doing a few things, but do them extremely well and
partner with others.
Speaker 3 (07:47):
So I do feel like we're all learning as we go.
And of course man Deep and Jay, you guys are
ahead of us in a big way. But when they
talk Man Deep about zero trust is never trust, always verify.
I think about digital touch points thinking that there are
threats within an organization and outside, and you've got to
make sure there's security everywhere.
Speaker 4 (08:05):
Yeah, no matter where you are, and that's where you know.
Sase is a term that gets thrown a lot, and
z scaler is in the leading position in that magic quadrant.
So I have one other question Jay for you. So,
given the amount of data in the world of security,
and you know you guys generate trillions of data points,
(08:25):
will the security world have its own.
Speaker 2 (08:27):
Lell Yes, the answer is yes. We are actually working
on building our security focus LM, and I do not
need to have the large large language model. Security is
very focused set of high equality data. With over eight
thousand customers and forty five percent of Fortune fire and companies,
(08:51):
we generate over half for trillion transaction logs a day.
Those logs are anonymized, but they can give us an
idea of where the threats are coming from. We can
find a needly hoistag and help all of our customers.
So AI is only as good as the data that
(09:12):
powers it, and we have the best data and we
believe we can help identify some of these threats in
almost near real time and provide a closed loop system
so that the threats can't really exploit our customers and
provide them benefit at a much faster ways. That's why
we have focused on AI powered security operations, and our
(09:35):
acquisition of redcnnety is part of the strategy because they
build some very very good, egenic AI technology that we're
integrating with our platform.
Speaker 1 (09:44):
The use of AI to make the system more robust
certainly makes sense, but I got to tell you min
deeper and I are actually moderating some panels next week
at a Bloomberg Live event that's focused on cybersecurity, and
in the prep that we're doing for that, what I
keep hearing from these chief security office, from these chief
information security officers, is the concern about how AI has
(10:05):
made the attackers just more robust and the attacks more robust.
Can you point to specific instances where hackers have actually
used AI to enhance their attacks and did it work?
Speaker 2 (10:18):
Yes, there are many many examples. Let me give you
a few simple ones. Every attack starts by finding your
attack surface, who where you are and public IP address
is the starting point. Every firewall, every VPN, every application
portal is an attack surface. In the past, a hacker
(10:39):
may have taken weeks to identify it. Now you can
go to chat GPT and say tell me all the
firewalls and VPNs that have won abilities and give it
to me in a nice tabler format. Under sixty seconds,
you can get that now. The second part attackers would
do is these phishing emails. Now they can ask AI
(11:02):
to say, write an email that looks like a cfo's
writing style, no typos, make it very targeted. That's number two. Third,
hackers are using automation that AI provides. Once they are
on the network, automation can find the key applications and
try to encrypt that data. A lot of that is happening.
(11:23):
What does these kin do in this case? Number one,
we hide your attack surface. Your applications are hidden behind
our cloud. Bad guys can even find you. They can't
find you, they can attack you. And the second is
on the network. The biggest problem with firewalls and vpnss. Right,
they're trying to protect the castle, and we actually make
(11:44):
it zero. Trust.
Speaker 3 (11:45):
Jay, We've got to run. This was so informative and
so enlightening in terms of AI security. We so appreciate it.
Jay Toddray is founder, chairman's eeoz Scaler and of course
our own Mandi saying a va
Bloomberg Audio Studios, Podcasts, radio News.
Speaker 2 (00:07):
You're listening to Bloomberg Business Week with Carol Masser and
Tim Stenovek on Bloomberg Radio.
Speaker 3 (00:14):
Shares of the more than thirty nine billion dollar cloud
security and software companies z Scaler are easily outperforming both
the S and P five hundred and Nasdaq one hundred today.
The stock is up nearly forty percent year to date,
and yet we did see shares under pressure today, dropping
nearly four percent after Bernstein downgraded the software company to
market perform from outperform on growth concerns. Bernstein, by the way,
(00:36):
setting its price target on the stock to two sixty
for a share. That's a five percent increase from the
Friday close. I should put out that initially Bernstein when
the company reported earnings last week, they initially maintained their
outperform rating. So there's been a lot of movement allis
in general, tim a flurry of them weighing in, some
raising their price targets on the stock, others lowering them.
(00:58):
And we should point out the stock did drop about
thirteen percent last week. That was on Wednesday following their earnings.
Speaker 1 (01:04):
Yeah, the forecast was annual revenue that was only slightly
above estimates from one of the company were joined by
Jay Chawdry, founder, chairman and CEO of z Scaler. He
joins us from San Diego, also San Jose. Excuse me
also with us as somebody who knows this company very well,
Bloomberg Intelligence's global head of Tech research, Man Deep saying,
he joins us here in the studio, Jay, I just
(01:25):
want to start with you the growth concerns, the disappointment
over the annual revenue forecast that was only slightly above estimates.
Speaker 2 (01:31):
Is growth slowing, not at all. We had an outstanding quarter.
Our AIRR growth twenty six percent, revenue growth twenty six percent,
free cash flow margin fifty two percent, operating margin twenty
two percent. We beat all the metrics that Wall Street
was looking for. In fact, if you take our free
(01:54):
cash flow margin and add it to our revenue growth,
that's seventy eight percent. That beats the rule of forty
that many investors look for very very well. And this
is at scale of three billion dollars or higher. There
are only about five pure play enterprise SaaS companies that
are in that unique class, So you're done extremely well.
(02:17):
We are very proud of what we delivered and be
passed a meaningful beat. We did and raised our annual target,
So I think we're very pleased with it. I think
investors get it wrong from time to time. This is
one of those times.
Speaker 3 (02:33):
That's what's going to ask you know what, do you
think investors just got it wrong? Because I mean, thirteen
percent is a pretty big hit, So you think, I mean,
that's not like them wavering at all. They really wanted
more from you guys. I mean the expectations were certainly high.
Speaker 2 (02:48):
Look, markets do what they do. I have one focus,
keep on innovating and serving our customers. And those innovations
started with zero trust architecture with a chained the world
of old school firewalls and VPNs. And now as AI
security is coming, a security is becoming a big concern
(03:09):
and zero trust that we pioneered is the foundation of it.
So we have amazing interest from our customers. That's why
we're able to deliver these strong numbers. Over forty five
percent Fortune five hundred companies trust us, depend upon us,
so I'm very bolish about our future.
Speaker 4 (03:27):
So talking about AI security, I mean, you have a
business model that's reliant on companies hiring more people and
you have a C based model, how does that change
with AI security? Because AI, you know what we are
seeing out there is more consumption based. So how does
that impact you and your business?
Speaker 2 (03:48):
It's a good question. So we started out with bringing
zero trust for users, so users can access applications without
being on the company network, and natural pricing for that
is user based. Then we move the model to our architecture.
The next thing, how about zero trust communication for workloads
(04:09):
cloud workloads that's actually based on number of workloads and
actually mount traffic, so it's not just user based. If
you think about AI security, there are many facets of
a security well. One of the biggest thing our customers
look for is as every company starts using a lot
of agents. These agents are some like people. They need
(04:33):
to access their applications, they need to talk to other agents.
So we are extending our zero trust exchange that are
designed for users and workloads and branches now to agentic
exchange so that right agent can talk to right agent
and right application. So obviously there's an opportunity for us
(04:54):
to secure that communication. Yes, the number of users may
not grow significantly, but I believe every company will have
scores of agents for every single employee and they need
to be secured and we are extremely well positioned to
handle that.
Speaker 4 (05:11):
And talking about agents, it sounds like one of your
biggest competitors is doubling down on observability and identity, especially
on the browser side. As an area of focus for
agent Tachai is that something you feel is very important
to roll out the agents.
Speaker 2 (05:30):
So some companies try to go and buy many companies
to create a collection of things. We are very focused
on what we want. We are focused on zero trust
and then we focused on AI. Regarding observability, we actually
do observability for the areas that matter to our customers.
(05:53):
We sit between the user and the application. So today
we have a size business, hundreds of millions of dollar
business with the product we call z Skinnar Digital Experience,
where we can tell our customers if any user is
having any performance issues as they try to access those applications.
It's integrated with a platform. While many companies have many
(06:18):
point products and they are separate, we like to have
integrated platform that serves our customers. So we not only
provide secure and reliable experience, we make sure that it
is fast and you can trouble shoot those things. But
I'm not going into broad observability, which has become a
(06:38):
broad area. We are focused on the areas that are
relevant to our customers.
Speaker 4 (06:44):
And identity is that something you care about? The identity
on the browser.
Speaker 2 (06:49):
Identity is important. Think about identity for users. We have
been working from day one with all leading ID provider
for users or whether it's Microsoft and oct and others. Now,
when it comes to identity of agents, I believe there'll
be many contenders Microsoft, Google, Aws octors of the world.
(07:14):
Our philosophy is to federate those identity providers use that
identity and we are the zero trust exchange, the switchboard
to make sure the right AI agent talks to right
agent in this world. I do not need to own everything.
I need to do some of the things I do
the best and integrate with partners with proper API integration
(07:38):
so our customers get the biggest benefit. We believe in
doing a few things, but do them extremely well and
partner with others.
Speaker 3 (07:47):
So I do feel like we're all learning as we go.
And of course man Deep and Jay, you guys are
ahead of us in a big way. But when they
talk Man Deep about zero trust is never trust, always verify.
I think about digital touch points thinking that there are
threats within an organization and outside, and you've got to
make sure there's security everywhere.
Speaker 4 (08:05):
Yeah, no matter where you are, and that's where you know.
Sase is a term that gets thrown a lot, and
z scaler is in the leading position in that magic quadrant.
So I have one other question Jay for you. So,
given the amount of data in the world of security,
and you know you guys generate trillions of data points,
(08:25):
will the security world have its own.
Speaker 2 (08:27):
Lell Yes, the answer is yes. We are actually working
on building our security focus LM, and I do not
need to have the large large language model. Security is
very focused set of high equality data. With over eight
thousand customers and forty five percent of Fortune fire and companies,
(08:51):
we generate over half for trillion transaction logs a day.
Those logs are anonymized, but they can give us an
idea of where the threats are coming from. We can
find a needly hoistag and help all of our customers.
So AI is only as good as the data that
(09:12):
powers it, and we have the best data and we
believe we can help identify some of these threats in
almost near real time and provide a closed loop system
so that the threats can't really exploit our customers and
provide them benefit at a much faster ways. That's why
we have focused on AI powered security operations, and our
(09:35):
acquisition of redcnnety is part of the strategy because they
build some very very good, egenic AI technology that we're
integrating with our platform.
Speaker 1 (09:44):
The use of AI to make the system more robust
certainly makes sense, but I got to tell you min
deeper and I are actually moderating some panels next week
at a Bloomberg Live event that's focused on cybersecurity, and
in the prep that we're doing for that, what I
keep hearing from these chief security office, from these chief
information security officers, is the concern about how AI has
(10:05):
made the attackers just more robust and the attacks more robust.
Can you point to specific instances where hackers have actually
used AI to enhance their attacks and did it work?
Speaker 2 (10:18):
Yes, there are many many examples. Let me give you
a few simple ones. Every attack starts by finding your
attack surface, who where you are and public IP address
is the starting point. Every firewall, every VPN, every application
portal is an attack surface. In the past, a hacker
(10:39):
may have taken weeks to identify it. Now you can
go to chat GPT and say tell me all the
firewalls and VPNs that have won abilities and give it
to me in a nice tabler format. Under sixty seconds,
you can get that now. The second part attackers would
do is these phishing emails. Now they can ask AI
(11:02):
to say, write an email that looks like a cfo's
writing style, no typos, make it very targeted. That's number two. Third,
hackers are using automation that AI provides. Once they are
on the network, automation can find the key applications and
try to encrypt that data. A lot of that is happening.
(11:23):
What does these kin do in this case? Number one,
we hide your attack surface. Your applications are hidden behind
our cloud. Bad guys can even find you. They can't
find you, they can attack you. And the second is
on the network. The biggest problem with firewalls and vpnss. Right,
they're trying to protect the castle, and we actually make
(11:44):
it zero. Trust.
Speaker 3 (11:45):
Jay, We've got to run. This was so informative and
so enlightening in terms of AI security. We so appreciate it.
Jay Toddray is founder, chairman's eeoz Scaler and of course
our own Mandi saying a va
Hosts And Creators
Tim Stenovec
Carol Massar
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