Why Extreme Networks Says Executives Now Expect AI ROI Within Weeks

[00:00:04] What if the biggest challenge facing AI right now isn't the technology itself, but the growing impatience of the people funding it? After years of experimentation, boards are no longer asking what's possible. They're starting to ask what's delivering measurable business value. And they're also asking much sooner than they did before.

[00:00:28] So today I'm going to be speaking with Monica Kumar. She's the Chief Marketing Officer at Extreme Networks. And she's going to help explain why enterprise networking has become one of the first areas where AI is actually producing tangible results. And why the organization seeing the greatest success are building on strong digital foundations rather than chasing the latest AI trend.

[00:00:56] So we've got a lot to talk about today and some big stats as well and practical takeaways. So enough from me. Let me introduce you to Monica right now. So a massive warm welcome to the show. Can you tell everyone listening a little about who you are and what you do? Yeah, first of all, thank you for inviting me on the show. My name is Monica Kumar.

[00:01:20] And for the past, I would say, couple of decades, I've been fortunate to work at the intersection of technology, transformation and storytelling. I've helped companies like Oracle, Nutanix, Hitachi Ventura navigate growth and change.

[00:01:37] And today, as the Chief Marketing Officer at Extreme Networks, I get to do what I love the most, which is, again, driving growth, you know, simplifying complexity and creating meaningful connections with our customers and users of the technology. And then one thing I want to say that I really believe deep in my core is that technology is really there to simplify human lives and make it better. And so it's a means to an end.

[00:02:02] And that's why I firmly believe that the innovations are not just about the technology, but about what they can do, how they can make our lives better, create meaningful impact. Well, you're talking my language. I always say at the end of every episode that technology works best when it brings people together.

[00:02:20] And one of the reasons I was excited to get you on the podcast as well today was I was looking at your recent research, which set off my tech-spidey senses, where you said that or the research suggested that we've reached an almost AI inflection point. So to begin with, what have you seen change over the last 12 months that has convinced you that organizations have moved beyond experimentation and pilot purgatory and into large-scale adoption? What are you seeing here?

[00:02:48] Yeah, and definitely. So besides, obviously, our daily engagement with customers, which is leading us to believe in that direction, we conducted this study that you're talking about with the survey 200 IT executives to understand precisely how organizations, their organizations are using AI and specifically AI for networking. And the report revealed that AI has shifted from experimental pilot projects to core business operations.

[00:03:18] And with organizations now really focusing on measuring ROI and scaling those deployments. So if you think about 2024, it was a lot about experimentation. Of course, that's still continuing. But in 2025, we saw a shift to being specific. What use cases are you trying to deploy using AI? And now really, we see a big shift in organizations wanting to see demonstrable results from using the AI technology.

[00:03:46] Because they've made the investment, they need to show the ROI of the investment and scale them. And so as AI is becoming quickly part of our daily lives, both, of course, personally and professionally, and businesses need to stay competitive. There's an investment component of it, and you have to show the results from the investment. It's as simple as that.

[00:04:07] I'm glad you mentioned that investment side of things, because one stat that immediately stood out to me was 57% of executives now expect measurable AI results within weeks. So how is that changing the way tech leaders select, prioritize, and justify those AI investments? I've been to a lot of tech conferences this year, and I've seen a very clear shift towards measurable value, improving business outcomes. It seems like there is a change there. But what are you seeing?

[00:04:37] Yeah. And by the way, that stat, the 57% want to see, expect measurable returns, is actually up 16% from last year. So you can see more and more leaders and organizations wanting to see that impact. And even if you look at boards, are increasingly scrutinizing AI projects that fail to show that immediate value. And organizations are also getting, I would say, the time to show value is also shortening.

[00:05:05] No longer can you have a project that's going, you know, 6 to 12 months. Organizations want to see the results in 30 days, 60 days, and even less in many cases. So, you know, again, according to our report, the survey, we saw that technology leaders are focusing on AI investments that have fast and tangible outcomes with the impacts and benefits they can show.

[00:05:27] And that's precisely why, you know, us being in the networking space and network management is emerging as an area where AI investment can show results because networking is a critical infrastructure. And we can talk more about that and how AI can show tangible benefits in network management and security.

[00:05:46] And as an ex-IT guy, I've got to say another stat that particularly stood out to me was that 92% of IT leaders said that AI is now putting new pressure on network compute and bandwidth. And this is something I don't think gets talked about enough. So why has the network suddenly become such a critical factor in determining whether AI initiatives succeed or fail? Well, first of all, think about this, right?

[00:06:14] Network is the critical backbone. I mean, I want to say AI, but step back like of our society. I mean, we are so digitally connected at this point. I mean, you can imagine if the network goes down, nothing happens. I'll tell you this. Even my mom, who's 87 years old, is glued to her smartphone. And even she knows when the Wi-Fi is down. She'll say, oh, looks like the Wi-Fi is down. And all of a sudden, everybody is going like, how do we bring it back up?

[00:06:43] So networking is critical to AI. And, you know, AI applications require a lot of compute power and bandwidth. And so a fragmented legacy network will struggle to keep up. So think of network as the central nervous system of an organization. It's the foundation for the entire tech stack. And network is also a huge source of data. And AI relies entirely on data and compute to be able to function.

[00:07:09] And therefore, networking is emerging as a critical category where AI can really benefit network management and security. And also, quite interestingly, I think it was 74% of executives now define AI success in terms of operational efficiency rather than just technical capability alone. What do you think this tells us around how expectations around AI have matured so much in the last three years?

[00:07:39] Well, I think people are realizing there's a cost to AI, right? I mean, it was great to play around with the cool new technology and we all are still doing it. But ultimately, when you start using AI at scale in organizations, it's not free, right? We're investing in AI tools. Everybody knows about the cost of tokens and the unpredictable cost. The more you use, the more cost you rack up. And it's obvious as organizations, if you're going to invest, we want to know what it's yielding.

[00:08:07] So now the experimentation phase is literally over. The focus is on results. It's not just on technical capabilities. Leaders like myself, my boss, you know, our customers, they want to know. They don't just want to know what AI can do. They also want to know how it will impact the business. And one thing that makes me a little bit nervous, I'll be honest with you here, is the rise of AI agents from a security standpoint.

[00:08:37] But when I was looking at the report, one of the things that stood out to me was security concerns haven't disappeared. No. But 93% of leaders now believe AI-powered networking actually reduces security risks. So what's driving this growing confidence? And where does AI genuinely make that biggest difference? What are you seeing here from a security standpoint? I mean, if you think about this, you know, this has been an issue for a long time.

[00:09:06] Like the bad actors use technology, you know, the latest and greatest as well, including AI. And if you think about it, we don't have enough human beings to throw at the security problems. We have been, in the last, you know, many, many years, automating how we secure our systems and our data and our applications and the firewalls and whatnot.

[00:09:27] And now with AI, it's becoming even more, I wouldn't say easier, but it becomes more accessible to use technology to automate security protocols and procedures. And AI is fast. It's always on. It doesn't skip a beat. And like I said, the bad actors are also using AI. So the only way to keep up is for us to use AI in a way so we can secure our environments.

[00:09:55] And I would say as security needs evolve, IT leaders need solutions that offer 24 by 7 visibility, monitoring every user, every device, anomalies across the application, the systems, the network, any data access anomalies. And flagging it the moment they appear.

[00:10:15] So beyond and also beyond flagging, the ability to automate a detection, a threat detection before a threat happens puts IT a step ahead in terms of responding. So definitely what we are seeing is that AI is helping to automate a lot of the security posture and solutions that, you know, we just don't have the human beings to manually take a look at and do.

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[00:11:07] And I think nearly every organization, people listening will already have networking security and management tools all from multiple vendors. It's just the way it's kind of always been. But businesses now are favoring AI capabilities that are built directly into the networking platform. Are they all doing this rather than adding more standalone AI tools? What are you seeing here?

[00:11:33] Well, I mean, look, we all started by using standalone AI tools. And to be honest, we still are in some cases. But I think pretty quickly we realized that unless AI is integrated into your core business workflows, you will not see the impact. If AI is outside of your core systems, then it's in a silo. And it's very difficult to see the impact of it. Multiple tools add complexity. Complexity slows down the business, right?

[00:12:02] And when everything is unified, AI, networking, security, it's transformative for IT. And again, I think the whole point is we've gone through the cycle in the last two years of having siloed AI implementations that didn't work because they were not really impacting your day-to-day business. And, you know, adding AI into your networking and security solutions is the way forward. You know, that's what our customers want.

[00:12:29] They don't want these complicated swivel chair management tool, you know, tools for different systems. They want it all consolidated into a single system so they can then automate the most time-consuming manual tasks. So, for example, they can troubleshoot using AI. They can remediate using AI. They can predict the next actions using AI. They can look at the asset management using AI.

[00:12:55] So, it's just easier to manage when AI is integrated into your core workflows and day-to-day business applications and tools. And I suspect for many people listening, there is that much noise and in some circles, a lot of hype that surrounds AI. One of the things we try and do on this podcast every day is really bring to life very real-world examples of how technology is making a difference.

[00:13:19] So, on that side of things, are you able to share some maybe practical examples of how you're seeing AI already helping IT teams simplify operations, reduce manual work, and improve network performance in ways that really deliver that measurable business value that we're talking about here today? And are there any examples that spring to mind? I mean, as I said earlier, enterprise networking is emerging as one of the few areas where AI is already delivering immediate impact.

[00:13:49] And so, let me talk about some of the top use cases that we are seeing in terms of adoption across our customers and also the survey respondents. It's around performance monitoring of the network. So, making sure the network stays up at a consistent performance. It's about network insight analytics. What applications are using the network the most, what devices, what users, and being able to manage and load balance as needed during different events and activities.

[00:14:17] It's about doing predictive analytics on the network, about troubleshooting, about compliance checks. It's about capacity planning. So, those are some very specific examples of use cases within networking that we are seeing being adopted. Now, in the survey, for 90% of the organizations that reported ROI for AI deployments, the most common benefits were improved productivity. 77% said they saw improved productivity.

[00:14:46] 52% said they saw cost savings across the network management because they deployed AI. And about 66% said they saw improvements in end user experience, which is very, very important. And about 60% said that they saw an improved security posture. So, you know, and I can throw more stats on and on, many saw compliance benefits as well. So, overall, we have many examples and I'll give you a couple.

[00:15:15] In fact, there's one from the UK. We have Middlesbrough College, who's a customer. By the way, this is a published external case study on our website. So, you and the listeners can go view it as well. And Middlesbrough College said that they saw a 90% decrease in time spent troubleshooting. Wow. What took them five hours to track and do in terms of firmware updates now takes them five minutes.

[00:15:42] So, think about the magnitude of the savings here for this network manager. Five hours to five minutes. And networking teams are often very small and stretch thin. And they have a lot on them. So, this is quite a bit of savings in terms of doing this additional manual work. Another customer we have is the name is Bridgeport Public Schools.

[00:16:09] They went from regularly responding to wireless related trouble tickets to really getting any complaints whatsoever. So, literally went from a huge number of trouble tickets down to literally nothing. And this was all possible because of the AI capabilities in the network management stack that we provided them. And another last example, we have a customer called Sight and Sound Theaters.

[00:16:33] They can easily now manage their network across theaters and studios without any compromise on performance and security. So, again, it gives a very small network team access to a large estate of networking devices and users and applications and the ability to easily manage it. Well, there's some big, big stats there.

[00:17:00] And for anybody listening inside organizations that are looking for AI to become more of a competitive advantage rather than just another expensive tech project, what should they be doing to first to ensure that their network is ready to support the demands of AI and what those demands will place on that network? Any advice that you would offer to those people listening? You know what? I think one thing we probably, we know this, but it always in the back of our mind, we don't

[00:17:30] think about this, that it's really not just about AI. It's more about the data. Think about this. Because without the data, AI can't really help us. Without accurate data, without real-time data, without current data, and without clean data. So my, you know, one advice, and this is through our learnings and through talking to our customers, that we need to make sure that the network is unified and the data, the sources that they're

[00:17:59] using is all unified through the network and that they're organizing the data, the data is not in silos, cleaning the data, there's data hygiene practices in place. Otherwise, it's harder to manage and impossible for AI to use. So I'd say focus on having clean data on accurate source of data. That would be number one. Number two, I think look at your networks.

[00:18:23] I mean, if you have old, outdated legacy networks, they may not have the bandwidth and the necessary coverage you need to make AI work for you. So it's important to also look at your infrastructure because what may have worked for you back then may not work for you now because the demands on the network are a lot more intense because of the massive use of AI in organizations. And so those ones I would say, and, you know, obviously, if you find that it's time to upgrade

[00:18:52] your infrastructure, you know, then look for the right partner to help you do that. And then last but not least, I think AI literacy in the organization is very important. I'm a big proponent of that. Even within my marketing organization, but Extreme at large, we are making sure all of our employees understand how to use AI the right way for your functional areas and get the benefit out of it. Wow.

[00:19:18] And as for yourself, what is your big focus at Xtreme Networks right now? And what excites you about the road ahead? It sounds like it's going to be an incredibly busy time for you, but what excites you right now? What's your big focus? Oh, my gosh. Our big focus is really to help our customers adopt AI in a way that they can see big advantages from it. And really, I mean, this is what Xtreme has been about. We are always about our customers.

[00:19:47] We have this tagline. We say we go to extremes for you, you being our customers and partners. And that's where we are. That's where our mindset is. How can we help our customers adopt AI in a meaningful way so they can see the results in their businesses in terms of growth, better customer experience, improved efficiency, improved productivity? And then I would say from my organization perspective, I'm all about having a learning mindset.

[00:20:16] You know, for my team is continuous learning. There's so much coming out there every single day in the world of AI. How do we embrace what's applicable to us and keep learning new ways of doing things and doing things differently, doing things better and differently using AI and other technology innovations? Well, I absolutely love chatting with you today. And we've covered so much around how enterprise networking is emerging of one of the areas

[00:20:45] where AI is already delivering those very real measurable results that businesses are seeking right now. And for anybody listening that would like to dive a little bit deeper into the research we mentioned there, we've got the use case example in Middlesbrough here in the UK and everything else or contact you or your team. Where's the best starting point for all things Extreme Networks? Well, Neil, it's definitely our website, extremenetworks.com.

[00:21:12] And of course, you can also join us and follow us on LinkedIn, where we are very active in putting out all these examples of what our customers are doing with AI, as well as all the great innovations coming out of the company. But also, we are about also learning from our listeners as well, our listeners as well. So yeah, please engage with us on LinkedIn and go to extremenetworks.com. Awesome.

[00:21:40] Well, as you've said today, I think boards are increasingly scrutinizing AI initiatives that fail to show fast financial results. And as a result, leaders are prioritizing use cases with fast ROI. And we have seen so much there today on that subject around enterprise networking and the measurable results that it is delivering. So I will have links to everything you mentioned, including LinkedIn, et cetera. I encourage people to check that out. But more than anything, Monica, thank you for sitting down with me today and bringing this

[00:22:10] topic to life. It is something we don't talk about enough. And thanks for sharing it today. Really appreciate your time. Absolutely. Thank you for having me. I think today's conversation highlighted just how quickly expectations around AI have changed. Yep, success is no longer measured by impressive demos or technical capabilities alone. It's now measured by better productivity, stronger security, improved customer experiences and outcomes

[00:22:39] that leaders can clearly quantify. And Monica also made an important point there that applies to every organization. AI is only as effective as the data and the infrastructure supporting it. This is what makes investing in the right foundations more important than ever. So I'd love to hear your thoughts on this. As always, is your organization focused on experimenting with AI?

[00:23:07] Or is every investment now expected to prove its value in measurable business terms? And if you are, how long has this been happening? Let me know. TechTalksNetwork.com. We've got lots to talk about there. So please, let's keep this one going. Other than that, I'll be back again tomorrow with another guest. Hopefully, I will speak with you all again then. Bye for now.