娇色导航

[This transcript was auto-generated] Hello. Good afternoon, and welcome to 娇色导航Leadership Live.

I'm your host, Maryfran Johnson, CEO of Maryfran Johnson media and the former editor in chief of 娇色导航magazine and events since November 2017 this video show and audio podcast has been produced by the editors of cio.com and the digital media division of foundry, which is an IDG company.

Our sponsor for today's episode is Extreme Networks, a leader in AI driven cloud networking. This North Carolina based company focuses on delivering secure connectivity between devices, applications and users to 10s of 1000s of customers around the world.

By driving the convergence of AI Networking and Security extreme is aiming to transform the way businesses connect and protect their networks, enabling them to deliver faster performance, stronger security and a seamless user experience.

Visit extremenetworks.com to learn more, and now onward to today's guest, who I'm pleased to say, is Nabil Bukhari. He is the chief technology and product officer at Extreme Networks.

He's been in his current role since 2020, and Nabil is shaping the vision, the strategy and the execution of extremes, consumer centric businesses. He also serves as the General Manager to the company's cloud subscription business, and he reports directly to the CEO before joining extreme.

Prior to extremes acquisition of Brocade networks in 2017 Nabil was the vice president of data center products there at Brocade.

His career path has led him around the world for both entrepreneurial growth opportunities and tech leadership roles at industry leaders such as Cisco, Seagate, Sonic wall and Riverstone networks, an expert on technology and portfolio strategy, he has more than 20 years of tech industry experience across multiple roles, ranging from sales and engineering to product management and cloud operations.

As a futurist, a business leader and a humanist, Nabil is passionate about the democratization of technology and determined to contribute to a world where tech will have a positive social impact. Nabil, it sounds all very noble. Thank you for joining us today.

I'm glad to be talking with you, Maryfran. Thank you so much for having me here and and thank you for that wonderful introduction. I appreciate that. All right. Well, I'm afraid I have to say you've probably earned that introduction in all the work that you've been doing.

Let's start out with your perspective on what you hear.

You get out in the field a lot with CIOs and business customers, and I want and you hear a lot these days from them about the pace of technology change and what kind of an impact it's having on their businesses in these last few very disruptive years.

So let's start there. Tell us about your perspective on that. You said it, I mean the change of everything around us is so perpetual and intense at this point in time that I think everybody gets a bit blush because of that, right?

And that's really where the conversation really goes. Let's just kind of think about it like if, let's just say an average tenure of a 娇色导航is five, seven years. Let's just own that, and let's just see what happened in the last seven years, right?

Like seven years ago or 1015, years ago, it used to be like, okay, a new technology will come in. And like 710 years, that technology would percolate and slowly. And then, you know, there's a generational change after seven to 10 years.

And a lot of CIOs were like, Oh, I'll be retired by that time. So I guess just got to manage this one generational change in technology. But that wasn't quite enterprise enabled.

The CIOs were there to make sure that their vendors were delivering on their promises, and that eventually that the products, whatever they were, would grow with the enterprise.

CIO, CTOs, CPOs, and quite frankly, any CXO out there has to deal with, and the result has been pretty patchy, if you would, some Catholic maybe, yeah, exactly. That's a much better word. Some of them can wrap their heads around it a little bit better than others.

Some are a little bit more comfortable with the rate of change than others. Some of them are a little bit more comfortable in being in that ambiguous phase.

Quite frankly, a lot of them are not comfortable with the fact that the projects that they start will probably never finish. You know, it reminds me of that saying that art is never, never finished, only abandoned.

I think Da Vinci said that, which is kind of how tech is right now. Before you are done with one rollout, the other one kind of comes in and and starts again.

So just setting the background, you know, for what's happening with the change of face, and that is really the conversation that a lot of people have now coming to your next point. And I know you, and I spent quite a bit talking about it.

And this is something that I talk about very openly, externally as well, is that when you talk to CIOs out there, eight out of 10 their journey on AI started something like this.

It was either a CXO or a CEO or a board member, and they called and they said, like, hey, we need an AI strategy. And then what happened? All of a sudden, CIOs went out and they said, Okay, we need to find some AI to use, right, right?

If you were an enterprise or a corporate CIO, you were looking for AI to use so you could tell go back to your board and said, Look, we are using AI in all of these cases. I know what I'm doing. I have an AI strategy.

If you were a technology company that created products. What did you do? You were like, Oh, my God, I need to put an AI into my existing products. What's the best way to do that? Hmm, you know, what?

What if I add chat GPT to my products, and then a net result was the following, if, in the product space, all of a sudden, now there are 1000s of chat GPT like, you know, chat bot use cases, right?

Every SaaS application out there has a chat bot on top of it.

Now, if you were on the enterprise side, you ended up with 18 different or 18,000 different activities that are under the AI umbrella, and the governance of that became a nightmare, and that's in that context, is when I was talking to you, that reality is that we don't need an AI strategy, we need an outcome strategy.

So what do I mean by that? We discussed this with our customers. I've spoken about this. I call it the arc framework, and I'll try to describe it very succinctly here. How should an ideal strategy look like around AI for any company, it should look like the following.

Every company knows what they're doing right, their use cases, what they're delivering. You can define it as a use case.

You can define it as things to do, jobs to do, or you can define it as experiences to develop and provision doesn't really matter to your internal people, your external audiences, whatever the case might be. You can categorize these use cases into three broad categories.

Number one is stuff that you are doing, and you're pretty good at it, and but it takes a long period of time, so you want to accelerate it, okay?

Like, for example, you know, all the use cases around AI when I'm writing an email or I'm writing a marketing copy, or I'm writing a document, well, I know how to write it, but I would like to do it quicker and cheaper. Oh, great.

Like there's an AI tool for that. I can do it quickly, so accelerate that. So they're using a lot of companies I run into are using AI in their call center operations 100% right?

And same thing like, like, for example, there's very good AI tools that can route your call to the right person with all the background information, and you will hear KPIs like, oh, it it reduces the time for mitigation or completion by 70% or whatever the case might be.

These are all acceleration use cases. Now the second category is replacement use cases. Now, there are things that are happening in your company that you would much rather not.

It's a bad experience and you want to just replace it, not do it, taking the example of call center, you know, you and I and everybody, probably everybody that is listening has been on those calls where you call a support team and they say, like, oh, they have a list of 18 questions they ask you, do you have it plugged in?

Is the light blinking red? Have you turned it off and on and so on and so forth, right? And most of the time, it's a very frustrating experience.

And now, yeah, we have AI tools to replace that experience where you come in, and right at the get go, it knows all the information and can actually provide you a better experience.

So there's a lot of replacement use cases, and then the last one is things that you've never done before, and you want to create something new. So your use cases really fall into accelerate, replace and create. And we call it the arc framework. So.

It's the arc of the company. So first thing that you should do as a company, you know, our peers out there, the audience that is listening, figure out what your use cases are. You put your top 10 use cases and accelerate, replace and create.

Then you go about and saying, Okay, if I apply AI to it, which ones can actually provide value. Now this is where Maryfran, you and I were talking about it. Typically, CIOs go like this. There's a new technology. I'm going to sandbox it.

I am going to put it in a place where it can't screw things up. So I'm going to test drive it under the R and D kind of move, yeah, so this into production. Don't do that with AI.

If you are going to pick a use case that you're going to apply AI to pick a use case that people care about, a use case that is important enough. Why?

Because once you have done that, and trust me, it's going to take you longer and it's going to cost more than you think it would. But once you're done with that, you're going to go back for that next round of investment.

And unless you did a use case that your executives actually care about, they're not going to give you that money. So this is, by the way, one big difference in AI use case is start with the use cases that matter.

So once you apply that filter, okay, now your top 10 use cases are down to five use cases. Next thing, look at the use cases for which you actually have the data. There's no point in boiling the ocean.

There's no point like, oh, we need to fix our data before we can start the AI, none of that. Pick a use case for which the data is readily available.

Well, then maybe you are down to two or three use cases, then just simply go, pick one and start and go about and do that. And once you start doing it, you learn a lot.

But once you're done with it, you have delivered value, and you get the permission to go after the next one. Now, variation you, let me ask you, is the CTO there at Extreme Networks?

Have you directly applied the arc framework to projects and things you're doing internally at Extreme. Nabil, let me ask you about internally at Extreme Networks as you've been there, as you as we mentioned, since 2020, so you have been as the chief product officer in the CTO.

You've been experiencing all this inside on your own, with your own technology staff, with the other business users. Have you been through the A, R, C that we just talked about, accelerate and redo and create?

Do you have any examples of what you learned from that, how it worked? Yeah. So, Maryfran, absolutely.

And this is, by the way, I mean, the framework came after the fact, you know somebody, it was it was like an interview like this, where somebody was asking me, Well, how about, how did you guys do, about doing that?

And then I started describing that, and then we came up with the name arc framework, you know, on that, on that interview.

But so yes, and on both sides, because as a technology company, there is a use of AI on our product side, that is what we are doing on behalf of our customers.

And then there is the use of AI for our own internal users, which is us as an enterprise, us as a company, and we have actually applied this framework on both sides.

So just to give you an example, you know, a lot of times people would start from use cases. We got pitch use cases around marketing and around product documentation and stuff like that.

And while those are all very interesting, the use case that we decided under the arc framework to go about first was, how does our sales respond to RFPs requests for proposals? Right?

Because what we realized was, well, obviously we as a company really want us to be able to respond to these RFPs very quickly. And actually, with a lot of you know thought around it. Now, our portfolio is very, very broad, so this was a huge thing for us.

So now also consider that this was a thing that is customer facing, because you are giving those RFP responses to your customer. So the first thing would have been like, no, no, this is too risky.

Let's not What if AI makes a blunder and oh my god, we're going to end up with an egg on our face and stuff. But that's the first use case that we picked up as an enterprise. Now think about. This way.

This was a process that we wanted to accelerate because it took too long to do an RFP.

This is a process that everybody in the company cares about, and also this is a process for which we already had the data, because it was about our own products and our own services. So it really satisfies the whole arc framework, right?

So you're doing it with your sales group, which that's, that's where the revenue comes from. Those are the rain makers.

Was there any Did you have any trouble like getting sales people on board, or the fact that, you know, when you came to them and said, Hey, we're going to apply AI to this, was there a general gasp of horror, or did they look at you and say, What a great idea.

We have some ideas for that as well.

So Maryfran, you are touching an extremely important part of any AI framework, and that is, how are you going to get your users to buy in good because you can actually create the best use case or best technology if your users don't believe in it and don't buy into it, then good luck.

They're just not going to use it. So how did we get around that? There were two things. One thing again, as I said, we picked up something that they cared about. Yeah. So, so getting it right was in their own interest, right?

So now already you kind of got the buy in into why this use case. Then the second part is, where is around AI literacy? Because if you talk about a consumer grade AI or a consumer market AI, like chat, GPT, you just go in and you do that.

Obviously, people have a certain amount of experience. It hallucinates. There's a lot of, you know, accuracy problem and stuff. So of course, that was their first response. Oh, well, what if it hallucinates and what is it inaccurate? And that's where AI literacy comes in.

And you talk to them about like, Well, how do you make this enterprise AI a lot more robust? What are the guardrails around it? What are the kind of rag architectures? What's the accuracy? And then you show them a lot of data.

I put all of that under AI literacy. So two things, number one, pick a use case that your user base actually cares about. Second thing is, educate them, you know, bring in that AI literacy. Third thing, keep them into the loop.

From day one, they were part of the process of us developing it. So by the time it actually came out, they were clamoring for using it, and they'd already been using it for a while. So this is a pretty nice way of introducing new AI use cases.

And I think this is a conversation that we have with a lot of our customers, and the ones that have kind of picked this up from us, they've actually done pretty well. Now I'm not saying this is the only way to do that.

I don't have that kind of hubris, but I'm sharing that this is something that has worked out really well for us as an enterprise and also as a technology provider, because we did the same thing with with our products and with our end users as well.

So yes, you could show that you are drinking your own champagne Exactly. Or, you know, I recently heard another term, which is like, eat what you cook. I really like that as well. That's so much better than the whole dog food.

One, yeah, no, I don't like the dog food, but eating your own cooking well, and a lot of the CIOs that I've spoken with and in recent months, you know, eventually, at some point, I feel like it's almost a federal regulation where we get around, where we start talking about AI, and I've heard a lot about the importance of having solid governance in place and paying special attention to the privacy and The importance of having really clean, accessible data, but you brought up something that I haven't heard much about yet, and probably more companies are tuning into it, about answering that question, where is the ROI where is the return on investment here?

Tell me more about why you're hearing more about that in the market and how you recommend, what advice you'd have for CIOs and CTOs to be ready with their ROI answers? Yeah.

So it's such an important question, because in the end, tech by itself, you you need to pay for it as well, right? So business and tech kind of has to go hand in hand.

So look again, going back to what was the look, there was a lot of AI washing, and we were at the top of the hype cycle, and everybody was like, Oh, we can give you 70% reduction in your cost or time and stuff like that.

And the reality is, then, when I talk to and I talk to 10s of 1000s of CIOs that are directly our customers, and then 1000s of them in the general industry where, you know, I'm pretty active around it, and the reality is, there is, and I'm going to make a broad statement, I'm pretty sure there are some exceptions out there, but they're hardly anybody who has come up and said, like, I applied AI and my budget actually went down.

Hmm? Actually what has happened is that as people are starting to deploy AI and AI enabled use cases, their cost is actually going up right now. Why?

Because they have not been able to completely mitigate the cost that they had previously, because there's very few companies that have transitioned entire functions or workflows over to AI, and also, as they start going down this AI art, they're realizing that there's so many other things that need to get fixed, around governance, around literacy, around data fabrics and stuff like that.

So the costs are actually going up where the expectation was set to the CXOs or the CFOs and the CEOs that, oh my god, this is going to be the amazing thing, because we're going to reduce our cost now, this is a little bit of a mismatch of expectation in reality.

So that's where that ROI question is so important, because it should not be just cost mitigation. It should be a return on investment.

And anybody who has built a plan around that knows that most of the times, you know, companies come to their its and said, like, Oh, this is a new fiscal year. I want you to reduce your expense by 3% 5% 10% that's do more with less.

Yeah, that's close contribution. Yeah.

ROI, on the other time side is that a 娇色导航coming up to their board and saying that, look, I'm going to invest, like whatever, a couple million dollars in this thing, and it will generate a combination of cost optimization plus risk mitigation, plus, in the best of examples, some revenue generation, and combine that and that makes that investment worth it.

So on the on the on the AI side, follow the arc framework and the use case that you pick up, determine its ROI and do not go promise to your business leaders that all I'm going to do is mitigate the cost and reduce it, because that will not happen in the first phase.

And that's really the big mismatch that we're seeing an industry out there, and that conversation needs to get adjusted for 娇色导航to be able to continue to invest in AI.

Do you think one of the things we also talked about were all the complexities around cloud and cloud rollout, and now we've got AI, infusing into cloud, cloud is also one of those technologies it took the business side a while to understand what we were talking about, which is, I've heard it summed up, it's really other people's data centers, you know, and and it, of course, as usual, the tech industry promised it was going to save so much and be so easy for users.

And almost all of that was a whole different complexity to the truth of what it was like dealing with cloud and now you've got people. You have to hire specialists to manage all the different clouds.

Talk about where the AI products, whether they are accelerating or improving things or creating things, where are they fitting in with Cloud strategies? And is this even a good question? Is it necessary that CIOs understand how AI is slipping, slipping into cloud management?

Oh, Maryfran, this is such a broad topic we could sit here and talk. I'm going to count on you to narrow it down, though. Yeah, I'm going to try my level best.

So think about when, when we started talking about cloud, it was really about data, because think about whether it is privacy concerns or security concerns or regulations and all that kind of stuff, they are more applied to the data and not necessarily to the application.

And making a generalization here, but generally speaking, it is about the data right now. The thing that is common between the cloud and the AI is that data part, how do you collect data? How do you govern data? How do you secure your data?

What are the regulations depending on where you're operating, and then how do you essentially adhere to those regulations and stuff?

So the one good part is that if, as part of your cloud transformation, if you got a really good handle on your data, then you are a step ahead, so the AI will build upon on top of it.

So that's I wanted to give the good news first now.

Now the difficult part around this is that in terms of cloud, we were able to compartmentalize data, so we were able to say that, okay, well, this data is identifiable, or whatever regulation it is on top of it, so I'm going to make sure that this data is only available to this application, and this application might run in AWS and my local data center, you know, if you talk about hybrid.

So that was, that was something that people were able to wrap their heads around. Now where AI kind of blows that out of the water is the two competing requirements on here. AI is more valuable if you actually have more data available to that. Ai, right?

It has to keep learning.

Experience based on your job, whatever you if you're a net ops or a sec ops, or you know you are a marketing person, or whatever the case might be, and it's real time, it's your persona based access to all of the data that is part of your job and that you work with, and the platform needs to very quickly be able to figure that out in real time.

So it's a lot more than just our back. It is not about like based on your role, what things you can access. It is more about based on your role.

How do I serve up an experience to you in real time which allows you to do your job, and that experience includes data, dashboards, AI, yada yada yada, all of those things. This is pretty brand new. It is not, you know, very pervasive out there.

But a vendor that talks to you about platform but doesn't talk about these things probably don't know what platforms are. What they would do is that they will say there are multiple different applications, and then put, like some sort of a bundling around it and calling the platform.

So platforms will simplify your licensing, will simplify your metering, will simplify the way you buy into them. But just be careful that it is intrinsically simple and it's not just a packaging conversation, right? So that's the second part that you should look into this.

The third part that is absolutely critical is that the capabilities within a platform, they use common services. Now, what do I mean by that?

So common services from simple things like single sign on, which I've been around for a long period of time, to capabilities behind the scenes, single alerting and messaging, as well as single integrations and visualization and so on and so forth. Why is that important?

The reason why that is important is because that drives a multi layer integration between capabilities.

And I won't go too much into I promise you I won't go too much into the tech part of it, but the capabilities in a platform must integrate at three levels, and this is I'm just sharing with your audience what they should be evaluating against.

I'm not pitching any company to look for. Yes, exactly.

So the first thing that you need to look for is that the capabilities in that platform can be connected together in a single workflow, which means that you don't have to use APIs to bring them together, and you don't have to use your own automation to bring them together.

They should be able to go into a single platform, or a single workflow within the platform. Why? Because if you have to do all of these things, then the cost resides with you and the risk resides with you as well.

So make sure that that is done by the vendor in the platform. That's first level of integration. Second level of integration, obviously the common services. Again, if the vendor doesn't do it, then you have to do it.

Don't look at vendors to say, like, Oh yeah, yeah, don't worry about it. Here are my APIs, and you can connect all of these things together, well, then the cost and the risk sits with you. Let the vendor do that for you.

And these are all important, because in the end, the data needs to be integrated. Remember, we talked about one of the biggest thing that AI is driving is that they're no longer data silos.

And all of this data has to come together in a data pipeline, Data Fabric, data warehouse, data lake, whatever term you want to use. But that data strategy, if a vendor cannot describe to you their data strategy as part of their platform, they don't know what platforms are.

And the last thing is look for platforms where AI is a core component of the platform and not a separate capability or a separate product.

If somebody has a product and then say, like, oh, we have a chat bot on the side or a co pilot, unless that co pilot is embedded into the core of the platform and applies to both the inner workings of the platform and the outer workings of the platform, it's not a core capability.

Now I know it will be the CTOs and the engineering staff that can tell you if that's a core embed. So that's where so let me finish the previous one, because this question requires a really thoughtful answer, right? So that's what a platform is.

That's what the characteristics of the platforms are. Look if, as a 娇色导航or a technology executive, you should be thinking about platforms, my belief is that the way we get around this proliferation of chat bots and more silos in AI is by marrying AI and platforms together.

Now this is at the early phase of it, so just something to keep an eye on. Now, coming back to your really interesting question, who is going to tell you about this?

Yeah, the reality is that a 娇色导航will have to be able to tell it himself or herself, and that is what is going to force the change in the role, and the definition of the role and the characteristics of that role. This is a touch.

Subject, as you know, but I believe that the 娇色导航role will evolve from being a procurer and operator to a practitioner and an actual developer. Now. What do I mean by that? Think about right now. What happens right now?

Most of the CIOs, the ones that I talk to, the best ones in the world out there, they spend most of their times in procurement.

How do I, how do I actually buy this technology, and what's the licenses, and how much cost is there, and how am I utilizing and then, oh, by the way, regulations on top of it.

I just need to make sure that I don't run afoul of the regulations in Europe and then in us, in Asia and stuff. So a lot of CIOs spend a lot of time doing that, which is really procurer, and then their IT teams are running these applications.

So that's the operator. Part where they need to evolve is a practitioner of technology, and they will eventually create internal products over these platforms for the use of their company.

So they are going to progressively broaden their mandate and take over some of the things that are traditionally thought to be part of a CTO or a CPOs role. Look, if you're a tech company, you have a CTO, you have a CPO, you have CIO.

Things are a little bit more well defined. But if you're a general enterprise, these they typically do not have CTOs and CPOs, right? They have CIOs, but these CIOs must start including those roles of internal CPOs and CTOs within them.

I believe that's the future, and that's why they need to be able to essentially look at these platforms and know whether these are core tax built the right way or not, because if you look at the marketing from every company, slides all look great from every company out there.

Well, yes, it's a glorious thing in the tech industry. Now, one thing that comes to mind right away for me is, and I'm thinking of, one of the most famous CIOs in the world probably is Charlie Feld.

You know, he's a well respected 娇色导航major big companies, Frito, lay and so forth. And he has referred to the evolution of the 娇色导航role as a chief integration officer. And he doesn't mean just integrating components of a bunch of software products, but he does.

It's that in that integration writ large that you're seeing there, and it also indicates that we were talking about pendulum swinging, and you believe they're swinging away from best of breed and toward platforms.

In terms of the 娇色导航role, is a pendulum swinging back toward the more engineering, back technical trained CIOs versus the MBAs and the MBAs and the leadership guys. And I know you have an MBA yourself, you know? Yes, I have an engineering degree. I have an MBA.

I also have a fine arts degree, just for the heck of it. But look, I'll make a statement which might be a little bit controversial, but I genuinely believe in it, in where we are going. Every leader needs to know technology. It's not just CIO.

And I think actually CIOs, CIOs that do not have robust technology background. And it doesn't need that they have a degree in it. It could be just experiential as well.

They might just be, you know, they don't need to have a degree, but they need to know technology at its core level. I think that is going to be an absolute necessity for a CIOs.

I would even venture to say that if you're a tech company, every one of your leaders need to be a technology set. If you don't have it, you're missing the point.

I would even venture to say that no matter what your business is, whether you're making satellites or shoes or anything in the middle, technology literacy is going to become a really core component of your leadership team, and I'm talking C suite here, even boards, for that matter.

So I really that that the pendulum is swinging in such a way that understanding of those capabilities, of the platforms, of those technologies are really, really important, because in the future, a lot of companies will take these capabilities, as well as these technologies, and create internal productization.

That's the beauty of platformization. It allows you a level of customization the product world could never give you. It's not about just throwing you APIs and letting you go and, you know, build a complete different layer on top fit.

But this is the, this is a next five year, 10 year trend. I'm not talking about tomorrow, but if you are a company that is thinking about, you know you're in.

CIO, or you are a young CIO, or doesn't matter what a 娇色导航you are, and you're thinking about the next five years in your role and stuff. These are things that you should be considering.

You'll come at your own conclusion based on your own industry and in your own company, but at least these should be things that you should be considering well.

And there have been, I know there's been stories 娇色导航magazine and cio.com have spent decades watching and, you know, advocating for the 娇色导航role and also watching how much it has changed over time.

I mean, consider this is a role that started out as the data processing manager, you know, and knew all about the wiring closets, you know, and could talk to, could talk networking, you know, until the cows came home kind of thing.

You remember they were like some other roles that kind of started developing.

There was a Chief Digital Officer role that some companies would and then there were some companies that had this data roles and stuff, and what happens they kind of, you don't really see Chief Digital Officers that much anymore, at least I don't.

So they kind of, that's just a way to evolve the 娇色导航role.

So what happens is that when your CIOs are not cutting it, you create a different role, and then over time, that capability emerges back into the 娇色导航role as the kind of, you know it, it kind of narrows down then, and expands again and then narrows down.

I think that's the undulations of a 娇色导航role. And I think in the next five years, there's probably be a major expansion in that role well, and I see a number of Chief Information and Digital Officers. So the and digital has been added in.

And I have one show coming up, a leadership live interview that is coming up. And I'm interviewing a very long time CIO, who has become, has become his very large company's chief AI officer. Oh yeah, that's another new role that is going to be really interesting.

So to me, the chief AI Officer role is very similar to what Chief Digital Officer was like when digital transformation was a new thing. It's just kind of like a new thing. So you put like an exec that is 100% focused on this.

My opinion, Chief AI roles will merge back into the 娇色导航role over the next five years. That's my opinion. Well, this is if the 娇色导航community kind of progresses to that level.

Because, you know, as you were saying earlier, I think last time, when we were talking, that this is a role that everybody likes to scare, right?

We like to scare our CIOs all the time, because you're like, Oh, my God, this new transformation, the CIOs are going to go away. They don't know anything. The reality is that the role just expands to take on all of these capabilities.

I think chief AI role, in my view, is just another aspect of a modern CIO.

And there are several major research companies who we all know who they are, so they will remain unnamed, but they've built their fortunes and their own history around scary projections about what's happening with CIOs, and always assuming that CIOs don't understand what's going on and, you know, putting out, you know, like magic quadrants and that kind of stuff, all the rating and ranking that goes on, and those are usually aimed right at the business executives who want to feel more at home with where technology is heading.

And maybe they will now that AI has so driven its way, driven its big truck into the general consensus and the mindset of ordinary people. Do you find that there is more of a respect and a realization for the complexities of technology that AI is coming along?

Are you seeing that in the customers you talk to, where there is an appetite for trying more things with technology, for understanding that the 娇色导航or CTO role is indeed integrating all these different needs together with some sort of technology as a hope, a hopeful answer, I would say, yes.

I think there's a lot more realization around how fast tech goes and how pervasive its impact is.

The generative ai ai obviously has been around since the 50s, but the generative AI phase that we were sitting in, it has just made that abundantly clear that it is not a tech to be held in a certain silo. It is going to be pervasive.

It is a it is a technology. It is a capability. It is a product. It is an agent, co pilot, and soon enough, it will become a co worker, which is an entire track on the AI side.

And I think that realization is kind of setting in the CXOs and the C. Suite as well as in the board. I think yet to be seen. How they will respond to it.

Now, my hope is that they will respond by there being more tech literacy and AI literacy in the C suite and in the board, but that's our hope. We'll see, yeah, but that's yet to be determined. If you're a CIO, and you report directly into the 娇色导航CEO.

Push for that, push for that, AI tech literacy for the rest of your peers and the C suite, as well as for your board. It will make your life easier, and it will hopefully fix the gap between expectation and reality.

This is where we started with on the ROI side, talking about ROI exactly, if people read like media and media is like, oh, half the jobs are going to go away, and then the CFO turns around. Oh, great.

I'm not going to have half the cost, just not reality, right?

So helping bridge the gap between the two, that will help CIOs in also, I think this is a great opportunity for them to be more than just a cost center by maneuvering themselves at the center of the technology strategy of every company.

And the reality is, every company is a technology company, whether they know it or not well, and people have been saying that for a number of years now, whether that's really sunk in and the top executives believe it, you know, if they're a shoe company, you know, they understand how important technology is, but you'd have a hard argument with the CEO, who probably doesn't even do email all that well, you Know.

So it's not necessarily pervasive. I want to pivot over to talk about the size and scope of your own technology team.

I know you wear a couple of different hats at Extreme Networks, Chief Technology Officer, Chief Product Officer, how do you have all that structured to deliver the greatest value to the company with the technical talent that you do have, yeah, And that brings us to the organizational structure.

I think there's going to be a lot of experimentation that happens in that space for us, policy, the engineering talent that I have, there are about 15, 1600 people, but they're not all in what we typically consider as a 娇色导航group enterprise, it, I would say, is in more than 100 people range, right?

Which is a little bit more normal, but that's really where it is going.

I think there's going to be if you're a tech company, which means that your products are technology focus, then the overlap and the lines between your product teams and your IT teams are going to blur passively to a point where, especially if you have cloud ops, then the difference between your cloud ops and your typical enterprise IT, they're going To start blending together cloud ops.

You mean cloud operations, correct? So think about customer facing, or, yeah. So think about like, for example, at extreme, we have so many SaaS products which run on so many different clouds.

I mean, we were one of the original companies that were the poster child of hybrid cloud or cloud agnostic. I remember that so and how did we do that?

One of the key components of being able to do that was that we had an amazing and we still do have one of the most robust and forward looking cloud operations group, which really allows us to function at all of these clouds at its same time.

So that's really cloud ops and all of our public facing products, as well as a lot of our internal products, they all run on cloud. So our cloud ops team really is the one that operates them on a day to day basis.

Now in that team and your enterprise, IT team, they will start merging together if the following two things happen, number one would be, if you are going to use AI based or AI native products in your internal enterprise, it then perhaps the team that is most adept at data governance is your cloud ops team.

So it is in your benefit to start kind of pulling them together. That's the first condition that needs to happen.

The second one is you are a company where, in your enterprise, it you believe that the AI use is going to force you towards a hybrid cloud deployment, which means public cloud and local cloud, which, by the way, is a big thing right now, right?

Yes, you heard, you know, the Dell, Michael Dell, talk about it. You heard Broadcom talk about it. You talk, you know, Nvidia talk about it. So I would not take a side on that argument. The point is, if you are a company for which this localized, AI.

Is going to be important than it is. So that's the second factor. Start bringing your enterprise IT and your cloud ops team together. So that's one of the changes that I think is going to need to happen in your organizational structure out there.

The second one, I would say, is also that the way the it has to move, is that more and more, and this is I'm seeing a trend that I'm seeing is that the companies believe that your central IT team are the ones that are going to satisfy those data governance requirements, that your data is governed properly, there's privacy and, you know, regulations and stuff, and that is not necessarily a skill that central.

It was really good at. Maybe in some cases they were, remember our conversation from earlier, that problem is just blowing up. So I think it or CIOs really need to start kind of this is where they need to work closer with their legal teams.

I was just thinking that this sounds like this sounds like a job for the legal office, exactly, but think about like for us, my cloud ops team, my IT team and my legal team. They essentially sit together and work together on this, because they COVID Exactly, right?

So they're, what was the word that people used to use. They're tied at the hips. I don't know how we sounded, like one of those races like, you know, where you put your foot in a bag and run, yeah, three legged races, right? Yes, yes, yes.

But this is the organizational shift the CIOs must start thinking about it.

Remember, I was saying that, look, you that literacy to the rest of the C suite is so important because more and more and more you're going to rely on functions that are sitting with some other C suite leader.

So that organizational structure is going to change for me, and now I'll give you my view on this.

Some of the ways to do it is that do not go by functional roles and processes and policy, but transition over to frameworks, because frameworks are the one that allow you the description yet flexibility to be able to deal with these things out during the organization, rather than everything coming up, you know, through the totem pole into into the C suite.

So I'm a huge fan of frameworks, and I think as the platformization continues, the frameworks will become the main operating mechanism of companies out there, and CIOs could drive this if they really wanted to. That would be really good for their future.

Well, and stop and give us a, you know, kind of a general description of when you say a framework, you know, you're not an architect. We're not talking about the framework of a house. Or maybe we are a data framework, data? Is it a data architecture?

When you say framework, what do you exactly mean? So you know, in a surprisingly simple what I mean, but it is surprisingly difficult to actually implement it. Okay, think about simple, simple things like this.

So I'll give you a story, because I love telling stories, and I'll highlight what the problem is. So most of the companies, most of the C suites that you talk out there, where will they start from?

Most of the time, they start from the strategy of the company, right? Oh, they went on an ELT off site, and then they went to this fine, nice, you know, fancy hotel.

They spent three days and outcomes, like off of the topic, oh yeah, they came back with a strategy right now. The reality is that strategy should never be the first step off the framework.

The frameworks, which is like, what the company needs to do, they really should start from an outcome, because a strategy for what right. And the reality is that there is no company out there that has a single strategy.

You have a different strategy for every outcome that you want to deliver, right? So that's kind of like so that's what the framework does, identify the outcome, select a strategy, and then the next step. And essentially, I'm sharing what are the key characteristics of a good framework.

By the way, I believe that companies should just go write their own frameworks. Anything that was written like more than three or four years ago, don't use it. It was, it was meant for a different world, a different age altogether.

Write your owns they're not that difficult to write. But it must define outcome. It must have a selection process for strategy, it must have a way to define an operational plan and an execution plan.

If there's somebody in the audience thinking that, hey, operational plan and execution plan are the same thing, all the more reason that you should have frameworks, because they are not. They are two very separated thing. Now the other part also is the beauty of framework is that it.

Doesn't rely on titles. No. Framework is like, oh, framework has to start from a C suite or stuff. No. Every single person in the company should have the flexibility and the air cover to define their outcome and build a framework for that.

And as you know, I'm a massive fan of decentralization of authority, right? Because, well, that somehow people sitting in the C suite actually know what they're doing. You know that that's a question mark.

Maybe sometimes they do and sometimes they don't, but the company as a whole generally have a very good idea as to where it should go, and that requires people from every portion of the company and every level of the company to have the ability to define the outcomes and run a framework around it.

Now, obviously you have to have a way so that this is all kind of directed in a direction, but that should be a top down mandate.

So these are nested frameworks topic for another probably conversation, but I believe that the organizational future of companies is more likely to lie in the direction of frameworks than anything else. Okay, fair enough. And I know you're it's, it's a fascinating topic, and you're very passionate on it.

Now, as we wrap up here, tell us just as briefly as you can. What have you learned about leadership? I mean, you may not be a huge fan of centralized authority, but you have two chiefs in your title.

You're a chief product officer and a Chief Technology Officer, what have you learned about leadership, about driving the kind of mindset and the mental framework that you need your teams to have for helping the company move forward? What have you learned over the couple years?

You've been doing this at Extreme Networks Since 2020, so you have some experience at this. Look, I have learned a lot of ways how not to do it. Well, the first thing because, you know, you're trying new things, and then you learn that, oh, this doesn't really work.

But just generally speaking, these things that I talked about, you know, the requirements for frameworks decentralized authority. Look, I don't really believe in the cult of the leader. I actually believe, although I have to see titles, but I actually believe that the future is a lot more decentralized.

I think the more, the more we are dependent on the decisions of one or two or three or four people, the bigger the chance the difference between good and bad will be massive.

I feel like that's one thing that I've learned as a leader, is I that decentralized authority and decision making, you're better off doing that. The other one on a personal level, what I would say is, look, it's a continuous loop of inspiration and information.

As a leader, your your role is to both inspire and inform, and at the same time, your role is to be inspired and be informed.

So it is a continuous loop of inspiration and information, and the more freely this loop is running in your organization, the better off it is for everybody. And I'll leave it there. Yeah, that's a good place.

No, that's a good that's a very good summary, and it leaves it open to lots more discussion in the future, especially for the CIOs and senior IT leaders who may be listening today. So thank you for that. Well done.

Well, it's easy to answer when the questions are really nicely put, and they're very good. Thank you. I do worry that my questions get a little lengthy and rambling, so you've been, you've been very good about answering them, in fact, doing them real justice.

So thank you for that, too, and thank you for joining me today. This has been a really enjoyable conversation, Maryfran, thank you for inviting me. This is, this is fantastic.

You know, it's always good to be able to think about these things, because most of the times, we are just running from one issue to another to an usher to another, and it's good to just step back and actually think about this as more of a philosophical thing, rather than just, you know, a to do list on a day to day basis.

Thank you. Totally agree. Totally agree. Well, great. Well, thank you so much. I hope that if you're watching and listening to us right now, I hope you enjoyed today's conversation with the chief technology and product officer at Extreme Networks, Nabil Bukhari.

This episode is the latest addition to our extensive and I hope permanent on the web library of 娇色导航Leadership Live podcasts, which includes more than 150 in depth interviews with prominent CIOs, all of them available on CIO.com and on 娇色导航s YouTube channel, as well as all the popular podcast platforms.

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