Tech Innovators Spotlight - Transforming Tech with AI at Extreme Networks
(upbeat music) - Hello, everyone. Welcome to "Tech Innovators Spotlight." We have yet another amazing session queued up for you. I have a partner in crime today.
Let me introduce Jeff. He is my peer and he supports this guest. So Jeff, why don't you, in your words, introduce to our audience your work with Extreme Networks? - You bet. So my name is Jeffrey Bush. I'm an azure app innovation specialist, and I'm luckily to be joined today by Nabil.
He is from Extreme Networks. And so we're gonna learn a little bit about what Nabil and his team have going on at Extreme Networks, and we're excited to get into the podcast. - Awesome. Thanks, Jeff. Nabil from Extreme Networks, The Nabil, please introduce yourself, your role and a little bit about Extreme Networks. - Yeah, absolutely. Well, first, thank you so much for having me here.
I really appreciate that. And Jeff, as always, it's good to see you. - Likewise. - You've been on this journey with us for a while now. So a little bit about me. My name is Nabil Bukhari, I work for Extreme Networks. I wear multiple different hats there.
I am the chief product officer and in that capacity I have the engineering and product reported to me. I'm also the CTO. So in that capacity, I have the office of the CTO reporting to me. And because I don't have much to do, so I'm also the general manager for our entire recurring business. And in that capacity, there are multiple other teams, including sales and stuff that reports in to me.
So the good thing is that I have a good balance of technology and business so it keeps me honest on both sides. That's my role. I've been at Extreme for almost six years now.
Time really flies. I came in through an acquisition. I used to run the telco business at Brocade, and then through acquisition ended up at Extreme.
So a little bit about Extreme Networks. Now, I could take a couple of different routes. I could go and say that we are the largest pure-play enterprise networking company on the planet, but I'm not gonna say that.
I could say that we go all the way from enterprise data center into the core out into, you know, the branches and have every possible connectivity technology that you can imagine. But I'm not gonna say that either. I am going to take a completely different route, which is that the mantra for Extreme, the why for us is to really reduce complexity. We just believe that the world, there's just so much technology in the world and there are so many things that are happening in our enterprise customers or our customers as a whole, they kind of get bogged by that complexity.
Complexity in messaging. I mean, we are in technology, we love creating acronyms, you know, there's a whole alphabet soup that is out there. So complexity in messaging, complexity in buying, complexity in managing, complexity in operating. And that complexity really slows down innovation and it raises the cost of getting to the outcome. So at Extreme, everything and anything that we do is related to removing that complexity so that our customers, whoever they are, can get to their outcome faster, more efficiently and cheaper hopefully. And that's really who we are.
So that's how I would like to define Extreme Networks. - That's amazing. Thank you for that introduction. And it kind of also sets the stage for what we are about to talk when it comes to AI, right? The complexity, but also when you pair up networking and AI, right? Networking is one of the biggest, the most complex things.
I remember like my days when early on in Global Black Belt world, I was trying to evaluate some of the roles and it's like, okay, but don't start with networking. Like, start with something else, right? Because it is so complex to, you know, simplify, right? And in general, you know, we have so many complexities that it's just hard and especially when it comes to networking, it's even harder. So that kind of sets the stage when it comes to sort of how big of a problem that you have tackled now with AI. So tell us a little bit about some of the products, some of the launches.
Give us a little bit of flavor of what's about to come. - Yeah, no, absolutely, look, so you're spot on. I mean, you know, even like when you go out in the industry and you talk to your customers, they have this view of networking people, like, they go out in some dark cave and does some like black magic.
And yeah, it's not a very well-understood portion of technology, but at the same time, it is present everywhere. I mean, you can't have anything in the modern world unless you have connectivity, right? I always laugh at it. It's like, look, every age of humanity can be characterized by something. We have the Stone Age or the Bronze Age and the Iron Age, and then the steam engine age, and before that, the printing age, and then the Internet Age, and so blah, blah, blah. But currently we are living in the world, which is characterized by connectivity. Everything in anything is connected, from our daily lives to doing this podcast.
We are all in different places, you know, audiences are probably all over the world. Anything and everything that we do in our life rides upon this belief and this promise that everything is connected and that connectedness is actually lit over by networks. So it's present everywhere. You know, it's the steam engine of the 1800s where everything rides on top of it.
But anyways, so what is it that we are doing around it? So some of the bigger things for us, you know, I'm not gonna go deep down into the products, but I'll talk about it more from a philosophical, you know, and intellectual point of view. We really believe that there is a big shift that is happening in connectivity and secure connectivity. And that is to move away from the world of products into the world of platforms. And there's a whole slew of marketing jargon around it.
The what is the product and you know, what is a platform and stuff, but I'll describe it in simple English, right? So I am a 5-year-old and a 7-year-old. And trust me, like trying to, you know, tell them and explain to them what I actually do has helped me so much because then I can describe it the way. So recently my five-year-old, he's actually turning five next week, and he was asking me about something because he heard me talk on a call, right? And he's like, so he asked me, he comes and he ask me that "Baba, what are you talking about? "What is this platform thing," right? And I was like, "Oh my God, how do I explain it "to, you know, a 5-year-old?" And this was my explanation to him. So I picked up a toy that he has and I was like, "Look, this is a toy," right? And it was a little, you know, "Paw Patrol" thing, right? And I was like, "This is a toy. "You buy this toy, you play this toy "and it'll always be this toy."
And he was like, "Yeah, I get it." And I was like, "Here, you have this Lego set, right? "And this Lego set has all of these different blocks, right? "And you can make anything that you want out of it." And he is like, "Yeah, I get it." But I was like, "Tell me which one is easier." And he was like, "Well, of course, "this 'Paw Patrol' thing is easier for me to understand." But I was like, "Which one is more fun?" And he is like, "Well, this Lego thing is more fun for me."
I was like, "Now let's pick this Lego set, "which is actually made out of bricks, Lego bricks, "but it makes this car. "So you know that every piece that you need "to make that car is present in this and will go together "and will get you to make that car "no matter what your skillset." He's like, "This is awesome, "I can make this car." And then he goes on and he's like, "And then when I want, I can take another Lego piece "and put on top of it and add a person to it and stuff." And I was like, "You got it. "That's platforms."
Platforms are neither products that only do what they're supposed to do, they're neither like, you know, a set of Lego bricks where you can make anything with it, because that's difficult, right? It requires a lot of skill. It is a collection of curated Lego blocks that will get you to that outcome no matter what your skillset is. But as you grow, you can modify it. So it brings the best of ease of use and flexibility into one thing.
I describe platforms that way. And Extreme Networks is the first company in the networking world that has launched a broad-based platform where everything that we do is available as part of that platform. So it could simplify everything for you, but allow you to innovate on top of it when you are ready.
I'll stop there. That's my definition of platforms. (laughs) - It's like, you know, hats off. That's a great way to explain, that's a great way for our audience as well to follow, right? For anybody who's interested in just learning about AI, even if they don't have the technical skillset, it's like, "Yeah, I follow, "I understand what Extreme Networks does."
I know you and Jeff have worked very closely. - Yeah. - Jeff is very interested in kind of queuing up a few questions. Jeff, Go for it. - Yeah, no. And Nabil, we've talked about this before, like networking is not new. It's been around for, you know, decades.
But what was that turning in point in your time in Extreme when it was decided, "Hey, let's go build this platform, "let's leverage AI," can you recall that moment and kind of what the thinking went in behind that? - Absolutely, Jeff, and I know we've talked about this a little bit as well, 'cause I kind of described the platform and the platform really came from like, "Hey, our customers want ease of use "and that surety of outcome, "but they also want to have the flexibility "to mess around with it and optimize it a little bit." And that's where platforms came in. But another angle why we wanted to go to the platforms was really because of AI. So let me take a little bit of a swing back. When people ask me about wrapping their heads around AI, I take them all the way back to, you know, when these cell phones came out, the smartphones came out. And I was like, "So what happens?
"Smartphone came out, "you made the call the same way, but what changed? "What changed was there's an app for it." - Okay. - Now all of a sudden you could put like hundreds and thousands of apps and yeah, it got a little out of hand and then we have thousands of apps on our phone and we use four of them. And we get that, but there was an app for that. Then when AI came out, and I'm talking specifically about generative AI because AI has been around for 50 years and our first AI product was about five years ago.
Now that was, you know, what we consider now as classical AI and machine learning and stuff. So we have productized AI for a very long period of time. So when now I talk about AI, I'm gonna talk about this whole transformation that happened post generative AI, just as a reference point. So then when generative AI came out, what happened after that? We went from, "There was an app for it" to, "There was a chatbot for it." - Right. - Every application,
kind of put a chatbot on it. And don't get me wrong, it was awesome, it was fancy. You could chat to it and responded like a human, and everybody was like amazed with it. But it has limited value to it. Why? Because if it's a chatbot on an app, then its scope is the same as the scope of that application.
So now, if you think about it, so we are applying AI on these inherent silos, so they can only have that much value to it. And we thought about it and we said that, "Look, the true value of AI "is when it has access to a lot of different data." But that is also where everybody gets scared of it, right? That's where, you know, data privacy and data governance, you know, becomes really, really important. And we're like, "What's the best way to do it?" And the first thought was like, "Okay, "well, let's just have all of these chatbots "talk to each other," right? And we have all been in app development and in technology.
Yeah, good luck with that. You know, every application is such a silo, and if you're gonna go over the top and have these chatbots talk about, it was so messy. And trying to provide governance and security and accuracy on that was almost impossible, right? So we said, "There's a better way to do that." And the better way to do that is we are already doing these platforms and these platforms bring all of these capabilities in a very structured fashion and all of the data that is related to it there as well. So now this data exists in this platform, it's a lot more easier, and proficient and efficient to govern it and secure it and, you know, categorize it and classify it and all of those different things. Now let's apply AI on top of it.
And that was the aha moment, that the true promise of AI will only be unlocked when you take the AI capabilities and the platforms and merge them together. Where AI is not a chatbot anymore. AI is not something that rides on top of it, but AI is one of the core services of the platform. And that was really, Jeff, the genesis of when we started working with you guys and we were like, "There's a better way to do AI." And now as, you know, we roll it out to our customers and our customers are getting exposed to it, they are starting to realize that AI is not something that you go to, you don't open a chat bot and go ask it a question.
AI is something that is available inherently in every workflow that you do. Now you can decide to use it or not because you gotta allow human the ability to do that. But that was the aha moment for us. Let's not build a chatbot on top of application. Let's take AI and build it as a core competency of a platform and then make that available to our customers. So you ask for the aha moment, that was a big, in hindsight, it's like, "Oh yeah, "obviously that's that way."
But in that moment it was a big wow, you know? - Right. - Something got unlocked. - You know, I mean, that's when we started working together about two years ago too, you know? And we've taken your teams across different product groups across Microsoft, getting introduced to different techniques and how to use AI and their products. And it's been really cool to see the evolution of what Extreme has done and will continue to do.
So I'm just curious, what does success look like for Extreme Networks with having this ability to use AI this way? - Oh, gosh. And I can define success from multiple different hats that I wear, but in the end, I'm a very human-centric person, regardless of all of the tech that we are building, I always believe that technology has to be in the service of humanity, you know, at that philosophical level. But that's true at the philosophical level. That's true at the business level, that's true at the product level. In the end, success looks like delivering value to the customer that the customer can see, imagine, perceive, quantify, and wrap their heads around, you know. If a customer has to, like, sit there and have to listen to, you know, 18,000 different messages and their eyes are rolling back in their head and they're like, "I don't understand it, "but since my neighbor is doing AI, "so I'll do AI," that's not value, right? - Right.
- Value is when it is tangible and you don't even have to explain it to the customer. The customer goes and says like, "Gosh, I used that "and look what I accomplished out of it." So delivering that value is success. And then from that value, obviously, comes, you know, ARR, and revenue, and profitability and all that kind of stuff, but success looks like delivering that value where customer sees it, adopts it.
That's really what success is for us. - Yeah, right. - That's amazing. Well, you touched on a couple things that I wanna kind of go deep dive into.
One of them is sort of bringing that customer problem-solving skills, right? Like, that's sort of at the forefront of whatever you build. And this goes back to something that Satya says as well in a broader term of like, "Hey, "we should be adding GDP to the world, "to the countries." Like, that's sort of is what really drives, yes, it is about our bottom line, and yes, it is about our products being successful and all of that, but the core infrastructure kind of lies around that, right? Like, that's where we wanna build, is to make and empower other people and empower other companies. And I think it's very similar to what you're saying is like, we want to make sure that it is useful.
Whatever we build, solves that problem for our customers, right? And when it comes to this particular platform, which is Extreme Networks' Platform ONE, right? Like, that's what we are talking about here. What is that problem that, you know, AI will solve with this big launch for our customers that they were not able to do it before? - Right. So, Vrushali, that's a great question. And look at me, I'm a big fan of Microsoft. I'm a big fan of Satya, and I think he gets it.
And so when he speaks about it and it resonates with us because we are kind of very similar, the thinking process, very similar, it's all around that value, right? And we also... So, you know, to answer your question, what is it that it solves for the customer? So we have hundreds of thousands of customers globally, right? And who's who of the world is a customer. And I talk to all of them. I spend a lot of time external and you know, so all of these executives at these companies, the senior most leaders, they ask me, like, "How to think about AI." And I always tell them, the best way to think about AI is to not think about AI.
And as a business leader, you shouldn't be thinking about AI. And then they're like, "Wait, "well, what do you mean by that?" And so we kind of, and through conversation and then trying to explain this to other people, we kind of came up with this kind of fun methodology. And of course, as I said, we are technology people.
We love to create acronyms. So we call it the ARC framework, right? And we say like, "Look, it's an ARC." And they're like, "What do you mean by an ARC?" We're like, "Look, so A stands for augments or accelerate, "R stands for replace, and C stands for create." So don't think about AI, think about in your business, what is it that you want to accelerate? What is in your business that you want to replace because it's unefficient or inefficient and you don't want to do it, or everybody hates it.
And people say like, "Oh, shit, this sucks, "but you know, I have to get it done" and blah, blah, blah. So that's the replace part. And then eventually the create part, and I think that's what Satya is talking about, like adding GDP to the market. And that's really the ARC. And then you go about, and you start adding these use cases into these three buckets, and that's it. That's your roadmap for AI.
Start from the accelerate part because that's slightly easier and to understand and stuff. And that's the way to think about AI. And that is also how we think about the value that we are delivering through Platform ONE. Platform ONE with the whole AI part in it, it's core purpose is to accelerate things that you already do and you want to continue to do.
As an example, if it takes you, you know, 10 days to generate an analytics insight report, now it takes you 10 seconds to do that. You know, if it takes you months to design a network, you can go in with our AI and it'll design for you in minutes, right? We are massive in stadiums and venues and stuff. If you go to a sporting event in the United States, chances are 90% of the time you're connecting to our networks, right? And these stadiums and these venues are complex or airports, we have big airports and stuff, these are complex environments. People spend years optimizing the RF, you know, in these environments, the Wi-Fi in that environment, with AI, you can do it, like, within days. You can run hundreds of iterations and figure out what's the right one in your dock, right? So this is the acceleration.
There are thousands of use cases in networking that can be accelerated. And that's the first category of use cases that Platform ONE delivers. The second category of thing that platform delivers is things that, honestly, we have had to do it, but we don't need to do it anymore. For example, who wants to call support and sit and listen to that elevator music for 15 minutes, right? Nobody.
And then who wants somebody somewhere in the world to come up and say like, "Oh, well you have this problem, "can you check if it is connected? "Did you turn on the power button?" And like, they're reading through the script. I don't blame them at all. That's the script that somebody did. But these are experiences that nobody wants so you can replace them.
So, you know, in our Platform ONE, the Platform ONE, through its inbuilt core AI, finds the anomalies itself, troubleshoots it itself. If it can fix it, it'll fix it and send you a ping that, "Hey, "this problem happened, I fixed it." And if it cannot fix it, it will open a ticket automatically for you and tell you that, "Hey, by the way, "I opened a ticket for you." That's a great experience, right? It's not rocket science, but from a human point of view it replaces a lot of pain, you know, out of it.
And the last one is then obviously the create part, where, you know, the limit is your imagination. So we think of the value that we deliver through Platform ONE in that context of, "What can we accelerate, "what can we replace, or what can we create, "which is brand new and wasn't possible before?" And there's hundreds of examples in each one of them, right? - Just the breadth of the, I would say that not just the use cases that it touches, but also the lifecycle of those use cases that it touches, right? - Yeah. - And it enhances every time that it goes from there. So if you pick sort of some customers who are running things on-prem and now you have this connectivity and this availability and ability to leverage Extreme Networks and AI and how fast they can scope from one set to the other is something that's just very profound, right? Like that makes AI so much more, I would say, exciting.
And also that's why you see the scale that you see with AI it is because you can do the things that you were not able to do previously. And now with AI, you are able to do - 100%. - all of those things rapidly, right? Without a lot of investment, right? Without sort of thinking through, "Oh, "now I have to plan for a couple years, right? Go ahead. - So that is the magic word that you just mentioned, right? You know, and I give talks on AI all the time and people ask me like, "Oh, "what's the most transformative point around AI?" And people expect that I'm gonna talk about some LLM, this or that. And now technology is amazing, but the most transformative part of AI is that it reduces the barrier to entry.
Think about this, right? There used to be like, "Oh, I wanna do this, "but gosh, it takes too much investment, "too much time to build this, "or, you know, train people" and stuff like that. With AI, it reduces the barrier to entry, which then spurs innovation in itself. Now, I'll give you an example of that, right? Think about, and again, taking a completely non-technical example here, what's one of the... So again, going back to our customers and we go around the world, you know, one of the biggest challenges that technology and business leaders talks about, they talk about the availability of talent, right? They're like, "We wanna do that, "we just can't find people to do it," right? Okay, well, if you can't find people, then you need to find people that are not the right ones and you need to train them. And that takes a lot of time and cost and stuff. - Yes. - You know,
on average, I'll give you a simple example, for one of our partners, for example, it could take weeks to train a new employee on the technology that they sell. Now that is three, four, seven, eight weeks that they're not doing, they're not in the field, they're not selling, they're not productive. Similarly, you go to a customer and the customer says like, "Oh shit, you know, "my amazing network engineers, "they are retired now," first, the new kids don't want to get into networking. And if they get into networking, they're like, "Wait, what the hell is this? "I don't want to read through 18,000 protocols "and stuff like that.
"How do I become valuable really quickly?" Now these are real-world problems. They might not be sexy, but they hit your top line and your bottom line, right? Now with AI, what can you do? We can make a high schooler that comes out of high school, has no understanding of networking and getting them to a point where they are designing and operating pretty complex networks within days. And how do you do it? - Wow. - You do it by fundamentally rethinking it.
The knowledge does not need to sit in your head, it needs to sit in that agent or in the Microsoft world, that Copilot that is always with you. If you can find that information instantly at any given moment of time perfectly, then why do you need to remember it? You don't, right? - Yeah. - It's a fundamental change. So these are the things that we have built into Platform ONE.
And the other part, Vrushali and Jeff, that I would point out is that, look, not everybody wants to interact or interface with AI the same way. Okay, conversational interfaces are one interface, but there are other ways interfaces, right? So we introduce Extreme AI Expert, which is our conversational interface, and you can chat with it, right? You can either do it or you can do it with your voice or whatever. It's just typical, just like any other chatbot, it's a conversational interface, but it's a conversational interface to that core AI that is platform wide. But there's another interface, sometimes... Let me take another example. You know, in the world of business, you know, and this is funny, so, you know, where a lot of companies spend and waste a lot of time is generating insightful reports.
- Yes. - People go in and like, "Oh, I'm gonna take this data from this system "and this data from." I mean there's entire industries that are built just solving that problem.
Not that I'm trying to take away their jobs, but you know, that's reduction in speed and that's complexity in the process, right? So we were like, "Okay, well, how do we do that?" So we created Extreme AI Canvas and what that is, as it sounds, it's an empty canvas and you ask questions to your conversational thing, it responds and you drag and drop it onto the canvas. You are building that picture that you want. And once you have built that picture, you can save it. And by the way, it's a live picture because anytime when you look at it, it will be updated to that point with real-time data. Now all of a sudden, it's not just conversational, it is that visual and it is also that reporting and analysis and stuff.
So that's the second way you can interact with our, and obviously then, I mean, like, I would be remiss if I don't talk about agents, right? - Right. - And so the third is agents. And what is agents? So I recently gave this talk in New York and people ask me like, "Hey, how do we think about agents?" I was like, "I don't start thinking about agents "as AI agents. "I start thinking about agents as job descriptions." I was like, "How do you go and find human employees?" You write a job description and then you say, like, "This is what this job title will do." And then you go find the person that does it. How do you define agents? You define it exactly the same way.
You say, "This is the job to be done" and then you create an agent with it, right? And now the beauty of the agents is that agents are these well-defined roles with tasks and stuff. And that is yet another way of presenting, you know, AI. And I actually believe that there's amazing technology behind the scene and Jeff is helping us with that a lot in bringing this out to the market. But from a business point of view, it solves that problem of the ROI, right? Because right now, a lot of the times you go out in the market and people are like, "Oh, "well, we have invested a lot of money in AI "but you know, maybe we are struggling "with defining the ROI and stuff."
But if you start by defining the job, then you already know the ROI for that job. You don't go and say that, "Hey, you know, "I went out and I hired a CTO," or "You know, and I hired Nabil "and I don't really know what the ROI "of having him in the company is" because you define the ROI when you define the job. - Right. - So if you start thinking of agents that way, it will solve the biggest hurdle that we have or one of the biggest hurdles that we have in proliferation of AI and enterprise, which is a very crisp definition and determination of ROI and agents will help with that massively. And I think agents, the packaging of agents with the platform-wide AI, this is going to be the watershed moments of adoption of AI, outside of the typical use case of writing an email or a marketing campaign and stuff. We understand those, but going into your critical systems and stuff, that is going to be the watershed moment.
And with the help of, you know, Jeff and the team at Microsoft and know we are engaged at such a broad level with you guys, we expect ourselves to be the first ones in the networking world to get there, to that watershed moment. So it's exciting, you know. - It's very exciting.
And I mean you just talked about the Platform ONE, but are you able to share some of the things that are coming or you guys are working on in the next 6 to 12 months as the speed of innovation is happening so fast. So I'm interested to hear what's on your guys' roadmap that may be useful. - Yeah, absolutely, Jeff. I mean, you are right. A month in today's world is like five years - Right. - in the previous world. It moves so fast.
Look, so we talked about Platform ONE, we announced it and it's actually going to go limited availability pretty soon out here. And as part of this, I talked about it, the Extreme AI Expert and then Extreme AI Canvas, and then the rest of the stuff is more around the agentic AI. And I kind of gave you a little bit of an idea that we think about agents more in terms of jobs to be done. We think about them as almost human jobs.
And of course the idea is not there to replace all human jobs out there with agents. That's neither the goal nor, you know, that can happen. But the idea is to augment that and there are multiple ways to augment this.
One way to augment is that here's a job description and here's an agent that is attached to you to make you more proficient. So this is also, without announcing stuff before announcing it, but I was giving you an idea where we are going. So those are one kind of agents, the other kind of agents is that, "Hey, "now this function can be fully contained in an agent, "but now this agent need to interface with other agents." - Okay.
- Just like humans do. - Right. - You know, you have an engineer, you have a product manager, you have QA person, you're have service support person, you have a sales person, they all have to interact with each other to make a business successful. That is exactly how agents will have to work. They will have to cross-work with other agents in there. So you can think of, like, we'll definitely bring an idea there.
The third part is there will be no one company that will write to all of the agents. That's a non-starter, right? Which means that now these agents could be first-party, like, which I mean, like, written by Extreme in our context or in your context, you know, productized by Microsoft or it could be second-party, which in case would be your agents, - Yep. - you are a partner for us, so the things that you have, they are considered a second-party, you know, agents for us. And then there'll be a third-party which the customers will write themselves.
So now that opens up the questions, how do you organize them? Now think about this way, all of a sudden with agenetic AI, now you're thinking about org structures again. - Sure. - Just like we think about org structures in humans, right? So I'm kind of, again, without announcing thing, I'm kind of giving you ideas of where we're headed. - No, that's great. That's great feedback. - We'll get to the place where entire organizations can be built between first, second, and third-party agents. And then of course they will always interface with humans out there as well.
It is just mind blowing what is possible, right? And actually, the funny thing about AI is that, and I was actually talking to somebody this morning where I said like, "Do an experiment. "Pull eight people in a room, "put a blank sheet of paper in front of them, "walk into the room and say, 'You can draw anything. "'You have 60 seconds.'" I can guarantee you, half of the people will draw nothing. (Jeff laughing) Because it's human. When you can do anything - Right.
- then you get stuck in doing anything, right? And that's the nature of it. And I think that's where we are with AI. You walk into an enterprise, customer is just gonna, "What can I do with AI?" "You can do anything." All right, that's the end of the story. (laughs) - Right. Right.
- You know, and then you can come back in six months and they would've figured out what they want to do. So we wanna get past that hurdle and these first, second, third-party agents with inbuilt, you know, org structures and stuff, that will really fast track that stuff. So we are pretty excited about that. - Sure.
- And we are not talking years here. - Right, Right. - We are talking weeks and months here.
So lots of exciting stuff. Yeah. - Tha.t is incredible. The pace with which you are moving is just mind blowing, right? And you touched upon so many things, which goes back to how you introduced yourself. So let me ask you this, because when companies have C-suite execs, they have CTO roles, CDO role, CSO role, CPO role, right? Like, all of these, you wear several of those hats as one person. Talk to us about, you know, behind the curtains when it comes to these projects.
How is it helping you move fast? Because we are clearly seeing you're moving fast, right? Does that play a role at all, because now everything is like, okay, it all boils down to this one team and the dependencies are very clear and we have a clear line of sight of the ROI and the deliverable that's ahead of us, right? Because there are so many companies who also have that complexity of the org structure. So tell us a little bit about that. - Oh gosh, that's a big topic, Vrushali. (all laughing) I can- - Just a little bit. - Yeah, I can speak for days on this and I can be very controversial on this, but look, my thing is like, I just wanna share how I feel and what has worked for us. I'm not in a place to pontificate and tell people how they should do it.
They're the ones who'll figure out. But in my view, - Yeah. - things like AI that will force a fundamental change in the way we organize companies.
Because companies, if you think about this, are generally organized by function, right? They're functional, okay, here's the engineering team, here's the product team, here's the sales team. Some organizations have evolved a little bit and there may be an operational mode, right? What I believe that the organization of the companies will have to evolve towards an outcome-based organization, which will be very fluid, right? Where we will go back and I laugh about is that the time of the Renaissance person is coming back. You know, we are kind of fast moving away from specializations, these deep specializations and the people that will be successful, they will know a little bit about a lot of different things to be able to then bring this AI to bear and bring value. So we are gonna go back to this Renaissance person, you know, in terms of organizations.
Now, the human side moves much slower than technology, so I'm not gonna say that this change is gonna happen in the next two years, but I would say when we look at org structures in another five years, they're going to look very, very different. And a lot of it is going to be forced by these fast-moving trends like AI. Because think about, - Yes. - yeah, in AI, what's the moat in AI? It's a very relevant question and I don't wanna get into the broader news cycle here, but the moat on AI is velocity.
There is no other sustainable moat when it comes to AI. Money is not a sustainable moat. The next best LLM is not the sustainable moat.
None of this is sustainable moat. The real moat is velocity, right? And if you think about, if you generally look at it, there is no velocity problem in technology when it comes to AI. Actually it's moving too fast, if you would. Where we will see the biggest hindrance in velocity around AI is going to be the way, one, how information is organized within companies, and second, how companies are organized themselves. And then so now think about, here is this wave which can be fundamentally for humanity.
Forget about just businesses and here are these things that are going to slow it down. So what is going to happen? These hindrances are gonna have to be changed. There is no chance, and I want you never make these kind of sweeping statements, but I feel confident enough that I'm gonna make it, there is no stopping the transformation that AI has started and will bring in. There is no stopping it.
- 100% yes. - There is directing it and managing it. And that will require us to go and take these hindrances out. And the organizational structure of companies is one of those hindrances. Now before all of my peers - That's very well put. - send me like flaming messages, (all laughing) I'm not trying to change anybody's job description and stuff, - No, this is very well put. - but just thinking
about how to get to a point. - Yes. (Jeff speaking faintly) - Yes. Because everybody's thinking, that's why I wanted to ask, right? Like, it's a perfect example. So thank you.
Last question from our side, if our customers want to go experience AI Expert, Platform ONE, all of the capabilities that you have, what's the best way for them to do so? - Yeah, so that's great question. So we announced Platform ONE and Platform ONE is going to be limited availability in another eight weeks around here. And at that point, the best way to know about it is to experience it because that's another thing around AI, it's very difficult to describe AI, right? It's easier to understand that - Yeah. - or just experience it to be able to understand that.
And this will be, you know, limited availability in the next eight weeks. And then, we will actually be in Paris at our Connect user conference. Actually Microsoft will have a big role in there as well. Just like last year, you guys will be standing with us on the stage.
That will be a great place for people to know more and experience. And then after that it just goes GA, right? And that's the path. - And everybody can get their hands on it. - That's the path.
Exactly. Exactly. - That's amazing. - Yeah. - Well, thank you so much both of you.
This was a fantastic conversation. - Yeah. - Yeah, thanks, Nabil. - Yeah. - Yeah, this was- - Vrushali, - Yes.
- I'm gonna ask for one second because I wanna say something. - Yes. - And I know, - Yes. - you didn't ask me that, but I wanna say that and which is I want to give a massive shout out to the entire team at Microsoft, Jeff and his team and my dear friend Eduardo, I don't know if he is gonna be listening to this or not, - Yeah. - but look, and the reason why I'm saying is because if you are a product company out there and you wanna get to this AI journey so you can productize it and get ahead of the market and stuff, you cannot find a better partner than Microsoft and to all the audience, no, Microsoft did not pay me to say that.
(all laughing) Look, they have great technology and so does everybody else. I think from a technology point of view, there are a lot of technology providers that are out there. But I will highlight this human aspect of it.
I mean like the kind of collaboration that Jeff and his team had with, you know, on our side, Marcus's team. And the way Eduardo kind of, like, leaned into this as well. It really, truly felt like we were not talking to somebody else but our own internal teams. And we credit a lot of the velocity of our thinking and our execution to that partnership. So I wanted to just give that shout out because - Thank you.
- AI is one of those things, you can't do it alone. It takes a village. You know, and if you wanna build a village, you'll be hard pressed to find anybody better than Microsoft to be in that village. (laughs) So I'll hand it back to you, Vrushali. Yeah. - That's amazing. Thank you.
Yes, we did not pay, but I really, really appreciate you and Jeff, of course, the rockstar that he is. - Yeah. - This is fantastic. Thank you. Thank you everybody for listening and dialing in.
As you know, this episode will be launched sometime soon and so we will put all the assets in for our audience to kind of go and explore all of the new products that you have on the docket. And until next time, see ya. (upbeat music) - All right, thanks, Nabil.
- Thanks for listening to the "Tech Innovators Spotlight" podcast. If you enjoyed today's episode, be sure to subscribe, rate and review us on your favorite podcast platform. Wanna learn more about the AI innovations discussed, visit techinnovatorsspotlight.com for more resources and insights from Microsoft and our technology partners. Stay tuned for more episodes where we continue to uncover the stories that are shaping the future of AI.
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2025-02-17 23:43
