Hello, Manoj.
Lovely to see you in Davos.
Likewise, Vaishali, pleasure to see you.
Fantastic.
It's an honor to have you today.
I'm going to ask you a couple of questions, and of course the
topic is AI and GenAI.
I wouldn't have guessed.
So first, how has AI shaped Juniper's business?
We would like to think of ourselves, our company, as a
company who is the keeper of the Internet.
We build routers and switches.
We've been part of the Internet revolution, you know, which
happened about 25 years ago, Internet and smartphone
revolution.
We powered the networks, which made all of this possible.
And now I believe AI is that next inflection point, in some
ways even bigger than the Internet revolution.
So for Juniper, we've been investing in AI for the last six
to seven years.
We had invested in AI Ops specifically with one thing in
mind:
The networks are too complex.
You know, it doesn't need to be, you know, so you don't need a
PhD to manage a network.
You don't need to spend like years to manage a network.
It's got to be simple.
So about six to seven years ago, we acquired a company called
Mist and then we 'Mist-ified' the entire Juniper portfolio
with that company.
And what they did was an amazing thing, a cloud-native, fully
microservices-based AI cloud and an AI engine together which can
look at all aspects of the network.
You know, Day Zero.
You just scan the barcode, QR code, and things are up and
running, and then the whole network self-discovers.
And then the best part is when it operates, it's a self-healing
network.
I was just thinking self-healing actually, yes.
And the self-healing comes because we are able to collect
about 15 to 20 data points on a per-second-basis from each of
the Wi-Fi equipment, the LAN equipment, or the WAN equipment,
and put them all together and the AI engine starts learning.
Over a period of six to seven years now, we've become so
proficient that 90% of the problems can be solved before
they happen.
ServiceNow is one of our largest customers, 90% of the trouble
tickets have been eliminated and that's one of the sea change
which is driving this evolution of Juniper.
So Juniper has been in the midst of AI and now GenAI
puts that into, you know, over speed.
Over speed, exactly.
Wow.
I had actually no idea that, you know, you were so much along in
the journey and actually what you're talking about is simply
fantastic to hear.
So I'm going to ask you, if you've done so much.
It definitely has had an impact on your workforce.
Can you talk a little bit about that or also how are you using
technology to impact operations?
Love to, I think I'll start with customers always, you know,
start with customers first.
If you look at our customer base, you know it starts over
with, you know, even something as simple as like you cannot
connect to the network.
You immediately blame the Wi-Fi.
Wi-Fi sucks.
That's what people say, right?
But it may have nothing to do with Wi-Fi.
It may have something to do with the faulty cable.
It may have something to do with the switch, it may have
something to do with the Internet connection to the
service provider.
So we realized, OK, what we need to do is make things easy for
the customers, easy to operate, and for the end user like you,
Vaishali, or your Zoom, or your team's call, it should be
flawless.
It doesn't matter what the problem is, we should
self-correct it.
So with that vision in mind, our customers found it like, wow,
you know, things just work and if there's something going
wrong, you're going to fix it itself.
Which means that I have time now to do important things.
Previously I was doing the mundane work, now I can do
important things.
Similarly for employees, our engineers, they're spending less
time debugging stuff because they have all the
self-correction and auto-correction happening.
And even in cases where it's something new that's happening,
they can figure it out and train it, and the next time they don't
need to worry about it anymore.
And for product managers, it's amazing because you know when
customers are using a particular feature, when customers are not
using it, what's useful, what's making lots of money, what's not
making lots of money.
So the cycle is reduced to such a short time, you know what to
build much faster.
You don't need to wait for customer feedback and surveys
and all that stuff.
So it speeds up innovation and development and last but not the
least, you know, eat your own dog food or bring your own
champagne, right?
And it makes it super easy.
Our entire network is running on you know, our stuff.
And now with GenAI coming, there's a lot more new
frontiers.
You know, we can do Copilots, you know, to speed up
development, testing, lots of things to be done.
So we're just embracing AI in a full way.
And from legal documents, to running networks, there's a lot
of stuff to be done.
Wow, that's impressive.
And to bring the, you know, employees along this journey,
because I'm sure it would have required upskilling, retraining
as well.
I'm sure you did all of that too.
Correct?
We're still in the process of that.
You know, I think, you know, this is new to everyone.
Like one of the things which you have a dearth of is, you know,
AI analysts and data scientists and whatnot, but everybody's
trainable.
I think one of the good things about in smart people is that
they can move from discipline one to discipline two if you
provide the right amount of training.
So investment is important.
So you're not going to be left behind.
You don't have need to have any fear of missing out.
You just need to have the right attitude and the aptitude.
I like it, the right attitude and the right aptitude, I like
that a lot.
So maybe in conclusion, any learnings for you know other
companies to take away, you know based on in the fact as you
said, you know, you're doing everything from what I call
productivity in the back office, to really your own product
suite, to beyond.
So any learnings, I mean if people are just starting this
journey, what would you recommend?
I think at a minimum, people should automate
processes—whether it's you know, code to cache, things from the
back office to the front end, chat bots for customer
service—automation is number one.
Once you do automation, I think using AI insights to proactively
solve problems, reduce all this workload, and actually improve
productivity.
And also, if I may say one thing, it's actually good for
sustainability too, because if you solve these problems, you're
avoiding the truck roles.
So it's good for a better planet, too.
So start small, but start with automation, engage in AI, GenAI,
and the world is wide open.
So start small but have a bigger ambition.
So absolutely.
So thank you Manoj.
That was very insightful and really good to have you here in
Davos.
And enjoy the snow.
Thank you, Vaishali,
it's a pleasure to be here.
Thank you.