AI in Networking: Benefits, Challenges, and How to Begin

In this episode of The Q&AI Podcast, Bob Laliberte from theCUBE Research welcomes Mathias Kokot from Juniper Networks to explore the opportunities and challenges of integrating AI into networking. Although the benefits of mature AI solutions—enhanced efficiency, productivity, faster issue resolution, and improved network performance—are undeniable, the path to implementation can be complex. Tune in as Bob and Mathias share insights on overcoming these hurdles and why now is the ideal time to embark on your AI journey.

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Key points covered:

AI-Native Networking Platform: Juniper’s platform supports high-performance AI workloads with predictive insights and rapid issue resolution.

AI’s Role in Operations: AI helps network operators manage increasing complexity from more users, devices, and applications.

AI Adoption Challenges: Barriers include skill gaps, high costs, complex implementations, and a lack of integrated solutions.

Deployment Hurdles: 88% of organizations face challenges, often due to the absence of a unified AI engine across network domains.

Accelerating Adoption: Juniper’s platform simplifies AI integration with a unified engine built on a decade of development.

AI Benefits: AI boosts efficiency, resolves issues faster, enhances customer experiences, and frees up time for strategic work.

Starting the Journey: With 97% of organizations ready to switch vendors for better AI, starting early is crucial for success.

Future of AI in Networking: AI will be a defining factor for networks prepared for growth and innovation.

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Find the transcript and show notes at:

Transcript - https://www.juniper.net/us/en/the-feed/topics/ai-and-machine-learning/the-q-and-ai-ai-in-networking-benefits-challenges-and-how-to-begin.html

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Where to find Mathias Kokot?

LinkedIn - https://www.linkedin.com/in/mathiaskokot/

Where to find Bob Laliberte?

LinkedIn - https://www.linkedin.com/in/boblaliberte90/ 

Website - https://thecuberesearch.com/  

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We hope you enjoyed this episode!

Chapters

• 0:00 Bob Laliberte introduces himself and Mathias Kokot
• 0:29 Discussion on Juniper's AI-Native Networking Platform and its impact on network operations
• 1:39 Example of ServiceNow's success with AI-Native Networking, including significant reductions in network-related trouble tickets and cost avoidance
• 2:41 Increasing complexity in network operations due to growth in users, devices, and apps
• 4:55 Common challenges faced by organizations in deploying AI, including lack of a single AI engine and skill gaps
• 5:59 Improved operational efficiency, faster problem resolution, and better customer experiences
• 6:41 Examples from healthcare and retail sectors showcasing the benefits of AI in network management
• 10:27 Emphasis on the need for organizations to begin their AI journey to stay competitive
• 11:46 Encouragement to visit the Juniper website for more information

Transcript

Bob: Hello. I'm Bob LaLiberte, Principal Analyst of the Cube Research. And welcome to this episode of the Q&AI. I'm joined by Matthias Kokot, the VP of Cloud Ready Data Centers. And today we're going to delve into the topic of blueprints for AI. Great to see you again, Matthias. Welcome.  
 

Matthias: Hey, great to see you, Bob, as well. 

Bob: Yeah, so why don't we get started by maybe doing a quick recap of 2024. It's been a pretty busy year for Juniper. You kicked it off by launching your AI Native Networking Platform. So, I'm wondering if you could discuss how AI is changing how enterprises are interfacing with networks today.  
 

Matthias: Yeah happy to really happy to, Bob. Our AI native networking platform is the industry's first platform, purpose built to assure the best operator and end user experiences. 

This platform represents a hugely forward for the AI and networking environments, but it also represents the quickest and most effective way to deploy high performance AI training and inference networks, predictive actions. And faster problem resolutions. The result is a smarter, more effective, network that drives immediate and sustained value for our customers. 

And by our ultimate vision of a hundred percent elimination of network-related trouble tickets might seem, to be a lofty goal. The reality is that we are already delivering game changing and quantifiable real time and real-world outcomes right now. So just as an example, ServiceNow is reporting a 90 percent elimination of network related trouble tickets, 50 percent faster deployment of the full stack wired, wireless and SD WAN solutions, and they have achieved an impressive 60 percent cost avoidance in network, CapEx and OpEx spending. And this is just one example to show basically the power of AI native.  

Bob: Yeah, I think those are all great examples, and they're certainly resonates with the conversations that I've had with your customers and really points to the fact that AI is changing the way network operations teams are interfacing with the network and because the reality is today, the network operators job is becoming a lot more difficult. 

There's, huge growth in the number of users, devices, apps that are all accessing the network and they're all highly distributed as well. So as a result, things are getting more complex. And we just did some research that validates that 80 percent of organizations on our survey came back and said, the network's either more or much more complex than it was two years ago. 

And a lot of that when we drilled down into why that was what we found is that there's a lot more traffic going across the network. Organizations have to deal with multiple management tools. And of course, there's that distributed nature of the network. The really fascinating part of this, though, is when we asked organizations about the importance of the network. 

Over nine out of 10 came back and said that the networks were really critical to achieving their business goals.  

Matthias: I think we all see the potential of AI, nowadays as undeniable. I mean it promises a huge, opportunities for, companies, economic growth, increase, productivity, job creation. 

But we've seen that, with, let's say, many disruptions and, any major technological shift. It also brings its own set off, challenges, whether this would be, skill gaps, complicated implementations, deployments, the leg actually off you know, trusted, solutions, overall, and then also the, the adoption costs that for, many enterprises, many businesses is probably hard to overcome.  
 

Bob: I assume there's some variation based on skill set and knowledge, but I'm wondering if you could just share from your experience about, roughly how long should organizations expect to get through, especially some of those early stages, which is the knowledge and testing and all that. 

Matthias: No, it's a great question, Bob, and I think it totally depends on the customer, to be honest, they usually it's like the science, the size of the customer, their experience with AI, overall.  

Bob: It's been fascinating because, when we did the research, we asked about deploying AI and challenges around deploying AI. And it was interesting that the number one challenge in organizations, well, first of all, almost everyone had challenges, right? Almost 90% I think it was 88 percent of organizations said we had a challenge trying to deploy AI. But the number one challenge was that it was the basically that lack of a single AI engine across all of the domains across the network. 

I think that's just as important, and especially when you're getting into something new like AI and you're going to be growing it maybe starting in one domain and expanding to others. It's going to be really important for organizations to have that flexibility and that predictability and also obviously the ability to save some money while they're doing it as well so they can gain the benefits in additional domain. 

So, that was great. I love those examples as well. That brings me to the fact that, as I just mentioned, there are a lot of organizations getting started, right, just beginning their AI journeys. They're going to lack the requisite skills or the knowledge to be able to design and implement a solution. 

Well, certainly, that sounds like you, you've really thought this through, and it's a comprehensive approach to how to accelerate the adoption of these AI solutions. One of the things that the research that we did highlighted was some of the benefits that organizations got from deploying these, these AI solutions for networking, things like better operational efficiency, faster times to find and fix problems, better customer experiences.  

Matthias: It's really relatively easy to understand why, businesses, today are looking for ways to work smarter, not necessarily harder. And our platform really helps them, just do, that. Um, a huge benefit of our platform is the faster problem, resolution. 

We ask for, some, examples there. So we've had, customers, especially in critical industries like healthcare increase basically availability and the reliability, of the network.  Significantly, one of, one of our customers, it's healthcare, organization. 

Shared with us with, Juniper AI, they were able to find and fix, network disruptions in minutes instead of hours or days, enabling, them to deliver, better patient, care. User experience is another area where we see, big wins, for example, one of our retail, customers improved their Wi Fi and overall network, reliability across hundreds of stores. 

Making the in store experience, better and smoother, not only for, the customers, but, for the employees as well. And perhaps the most exciting part is that these improvements in operational efficiency, give IT teams, more time, to work on strategic projects. 

One large enterprise customer of ours reduced their manual troubleshooting by more than 70 percent with our AI automated routine network, task, catching, issues before they become problems that takes actually much out of the daily network management of our customers takes it basically off, their plates so they can spend more time on strategic, areas, expanding into new markets. 

Pushing forward with their own, digital transformation, efforts, when you look at it, from, from that angle, it's not just about, making today's networks, better it's about setting the stage for future growth and innovation.  
 

Bob: But the hard part is you can't get those benefits unless you get started on your AI journey. And so I'll share another little tidbit of research from our survey that we did, and it was really fascinating because. We asked the question about, would you switch network vendors if they had better AI capabilities? Typically, when we ask these questions about just different types of technical capabilities at most, we might see 50 percent say they would. 

Interesting in this survey about AI, 97 percent said they would be willing to switch their network vendors if they had better AI capabilities. Certainly, as you mentioned at the beginning, Juniper has been working on this for about a dozen years now, uh, or 10 years now, I guess it is. And so, you're seeing some real results from the actual mature deployments that you have. 

I'm wondering if you're also starting to see this shift in organizations recognizing the value of AI and wanting to start their AI journey, regardless of who they currently have in place today.  

Matthias: No, absolutely. Absolutely, Bob. I mean, organizations, definitely are recognizing the value of AI, driven solutions, and they do, act, on it. 

And your stat that, 97%, would switch actually vendors for better AI really highlights how critical AI has become in networking, decisions and you know it. I actually, I believe it's an exciting, time and we actually believe we are at the forefront of this AI journey. 

And we recognize that leveraging AI is filled with both, immense, challenges and tremendous opportunities. And, I believe, if organizations aren't embracing, AI in their networks, now, they're risk falling behind. AI capabilities are what will set hard networks today as the ones that are ready for, tomorrow. 

So my advice, just don't wait. The benefits are real and measurable, as I, pointed out, earlier with, some of the examples, that I gave, the longer organizations delay, the more they miss out on better overall user and operations experiences. So start the AI journey now, start them, with us in order to future proof your network for, tomorrow. That is really my advice.  

Bob: Yeah, I think that's great advice. I often, what I give as well, you have to get started in order to get those benefits. Once you get started, you'll realize the value it can bring to an organization and it will become more widespread and more widespread use. So you can work on more of those strategic initiatives and be of greater value to your business as well. 

Again, thank you everyone for joining. I'm Bob Laliberte, Principal Analyst at the CUBE Research. And I also want to thank my guest, Matthias Kokot from Juniper Networks. If you have any questions or want to learn more about these solutions, please visit the Juniper website.