Partnerships Unraveled
The weekly podcast where we unravel the mysteries of partnerships and channel to help you become more successful.
Partnerships Unraveled
Keith Norbie - Inside NetApp’s AI Partner Strategy
In this episode of Partnerships Unraveled, we sit down with Keith Norbie, Global Partner AI GTM Lead at NetApp, to unpack the evolving role of the channel in the era of artificial intelligence. With deep experience in partnering with global ecosystems and enabling partner-led digital transformation, Keith shares how NetApp is reshaping its go-to-market and partner strategy to help businesses harness the full potential of AI.
We dive into the challenges and opportunities facing channel leaders as AI reshapes customer expectations, partner enablement, and solution design. Keith details NetApp’s approach to partner readiness across the AI maturity spectrum, from born-in-AI innovators to traditional channel players undergoing transformation. He also explores the impact of AI on channel economics, partner business models, and what turnkey AI solutions mean for the future of B2B partnerships.
Tune in to learn how to make AI real for your channel, drive data-led partner outcomes, and seize the opportunity of a generation.
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Welcome back to Partnerships Unraveled, the podcast where we unravel the mysteries about partnerships and channel on a weekly basis. My name is Alex Whitford, I'm the VP of Revenue here at Challenge and this week I'm very excited to welcome our special guest, keith. How are you doing? Doing well, thank you. I'm excited for this one. Most of my audience knows that I'm an enormous AI nerd and we had a really AI nerdy preparation call, so I think our audience is going to get really into this one. Keith, maybe if the uninitiated you could give us an introduction about who you are and what you do.
Speaker 1:I work for Jenny Flinders in the Worldwide Partner Organization. I run Worldwide Partner AI, which basically means helping partners worldwide not only understand what NetApp does in an AI model, why we matter, but also how to, more importantly, help customers land business transformation and the results that I think organizations are looking for out of AI.
Speaker 2:Yeah, that sounds like a wildly fun and slightly complicated job, I think, half of which because AI seems to be a magical word that means a lot of things to a lot of people. So dumb it down for us. How do you make a partner AI ready? What does that migration actually look like?
Speaker 1:Well, it's a great question. There's really two spectrums of partners that are very resident in AI, that are experts that would be seen worldwide, both from NVIDIA and other places of AI expertise, as leaders in this area, and those partners. It's a different set of enablement than partners that don't have any AI capabilities that are looking to participate, and so NetApps put a portfolio together that really meets really any partner in any situation, including whether in cloud, whether they're just getting going and want to address the businesses that they serve, whether it be small businesses or departments in big enterprises, and we do that through both technical sales enablement, through offerings, incentives and ultimately, through PartnerSphere our program for all partners, and so one of the things that I think is very interesting I always take the lesson from M&A in terms of win the middle right.
Speaker 2:33% are going to be wildly excited, 33% are going to hate the idea, and really the job is to win the middle, or the great ones do. When you speak to partners and I imagine there's loads who sit there and say AI is a fad, right, it's a bubble, it's going to go away or it's just going to normalize really quickly how do you approach that from an education and sort of persuasive perspective?
Speaker 1:and sort of a swathing perspective. Yeah, it's not an easy task because you have partners both with a misplaced level of knowledge in the industry, like some that will say the AI decision gets made based on compute. In other words, I've landed so-and-so servers and so that's the AI architecture for infrastructure, or some will have misplaced understanding of NetApp. Overall, we're not important because we're storage. When the reality is it is as simple as this. Most folks would feel somewhat intimidated by AI, but they recognize, if they pull out their phone, that probably Chat, chat, gpt or Google search now has a Gemini feature and so they're all fairly able to use common language and prompts to use AI in real life. And what they can recognize is that when that AI experience has the data the user data to give you back a value-added response, it has a tremendously better result than if it doesn't.
Speaker 1:This is the number one reason why projects fail or succeed.
Speaker 1:And when you think about it, then AI projects really are about data and the success of data.
Speaker 1:And when you look at Jensen himself, jensen Wong, the CEO of NVIDIA, about two years ago at a GTC, said half the world's files live on NetApp and that's why we're doing this integration with Nemo and was basically connecting, through Nemo, all of the files in the enterprise to the LLM models to improve the success factors of these projects.
Speaker 1:What it tells you is that not only is NetApp relevant we're not just storage, we're a data platform for AI but we have all the services and, most importantly, the incumbency that this is mostly where, across the variety of accounts worldwide, you're going to find NetApp, probably in most of the situations that house the user data for this AI success and so us revealing that to these partners, and that neutralizes whether they've made a compute decision or not. You know, dell, hp or whoever. That's inconsequential to what are you doing with the data structure? Have you prepared the data structure for AI? What are you doing for training it and what are you doing for deploying it or inferencing against it? And that's where NetApp really shines in those three areas, to be something that all partners can benefit from.
Speaker 2:And maybe one of the things that I sort of often come up against when I end up having sort of AI migration conversations, especially when I speak to large vendors about sort of what does AI in the channel mean from a program design perspective I often come up against yeah, yeah, no, we know what AI is and it's some version of chat, like they are using it for Googling something, but on steroids, as opposed to where I think AI is headed in terms of the world, either in parallel, in sequence, really comprehensive data analysis or egyptic workflows how do you?
Speaker 2:sort of practically explain that this isn't just hey, I can do smart search. This is, you know, a 10x factor difference to what really can create performance differences and competitive advantages of business. How do you actually contextualize and practice that information?
Speaker 1:Well, the partner is definitely in the middle of the success of a project, because they pull all of it together. Without the partner, the project goes nowhere, and that's why it's so important for partners to realize sometimes that it takes a partnership of partners to have success in that. Second point really is that you've got to work backwards. From what is the business success that people are trying to find Now. Sometimes that's known and sometimes that's unknown To this day. Even you know, I started this journey seven years back ago with a small group of folks within NetApp, with NVIDIA and some others, and what was true then is true now. Which is the best partners in the world deliver? One thing, that's clarity. If you have clarity about what AI can do, you solve a multitude of problems for people, including what is their business? What are they trying to do versus what can they do? What's the potential of things they can do that they're not sure of? And so if you look at things anywhere from yes, doing AI, chatbots, things through LLM engines to be able to give people greater success, Internal NetApp we have something called NetChat AI, which is a derivative of ChatGPT that we've internalized to secure our IP and things like that, and we utilize that to be able to do Chat, know, do chat GPT type things internal to net app.
Speaker 1:And other folks will have other things, like in manufacturing. They'll have something like a digital twin and Super impactful because a fraction of the cost and a massively improved digital agility for simulating a manufacturer floor iteration or a new product spec that they want to try out. Those are the kind of things, just at a small level there. And if you think sales and marketing, you think anything else from an industry perspective law and it doesn't have to be a wholesale thing by the way. Law and it doesn't have to be a wholesale thing by the way. That's the beautiful thing about a new emerging category called turnkey AI, where you start to see AI being packaged up in a turnkey offer for, say, departmental law, where you can go and you can target law parts of big companies or small law firms. You can deliver the results of what a turnkey AI system is for them to be able to show what the promise of AI is.
Speaker 2:Well, I was at Pax8 Beyond and Pax8 was talking about this sort of migration from managed service provider to managed intelligence provider and what that means for the AI and the SMB consumption. And I heard one question sort of repeatedly and I didn't have a good answer for it. It's do you build a specific use case and sell that use case, or do you come in as a consultant and say, well, what's keeping you up at night and how can I help solve that? And ai is a fundament to how we solve some of these complicated challenges. Is there a piece of advice? Or do you think that's so nuanced where it is very sort of partner specific or customer specific? Or is it much easier to scale a productized offering, a turnkey AI offer? Where you go, we know our ICP, we know our persona, we know our buying pattern, we know our deployment metric. My sort of sales fundamental says that's much easier to run and scale, but maybe it's less valuable.
Speaker 1:Well, I think a partner will approach 10 different customers and find 11 different use cases, or maybe twice that. I think you come both with use cases in mind as well as the open mindset to understand how to discover the use cases that they're trying to land on. A good partner always is question-based to understand what's the customer trying to achieve and how does the partner unlock that. And so NetApp's role in that partner is to really co-innovate, co-sell and co-deliver on those things to help enable the partner for success. So, as they go in, it's not just all technical, it's financial, political and operational. So there's a lot of factors on how things succeed or fail. In AI especially, the stakes are at a magnitude level higher than anything before. It's come previous.
Speaker 2:And I think it does come from that MSP world right. We heard a lot about born-in-the-cloud MSPs and they sort of revolutionized the unit economics of being able to serve customers in a very different way. And by changing their unit economics they changed the cost structure of serving customers and therefore were able to radically build a different price model and that sort of spearheaded the migration into cloud. I'm now hearing Gordon AI partners. I don't know what that actually means. I don't know if it's real. Are you seeing this? Can you contextualize any of that?
Speaker 1:Well, it's funny because the folks that have been on AI a long time will say there's no such thing as born AI partners. But I've seen it for myself. They are born AI partners. There's also partners that have transformed themselves in AI to refocus on just AI or to add AI. All of it's good in the sense that, you know, ai is an opportunity and it's an opportunity like none I've seen in my several decades in this IT industry, back to the Windows 95 days. This is the most massive opportunity any of us have had in our lifetime. No-transcript going to be a three to five year run and maybe longer. And you know it's our, it's our position to go get that opportunity, depending upon whether the partner wants to remake themselves and add AI, align with someone that's that, I think tries to make AI easy, like NetApp, or is born in AI. There's definitely organizations that have been born to just do AI.
Speaker 2:I can see, keith, on your face optimism. I think that's one of the things that freaks people out right. I think there's a lot of Terminator, doomsday view around what AI actually means. I think both in our prep pool and here, I can hear real optimism in your voice. Talk me through what you think, maybe at a more humanitarian level, what AI is going to do to change what we are as a species yeah, I mean, there's all kinds of upsides.
Speaker 1:There's also some downsides, you know. Upsides are things like that could cure diseases, um, could make life incredibly more dynamic. Uh, it's the upside is really hard to imagine it. It's a bit like back when I first experienced the internet and, for one night, a web browser. None of us understood what the potential of Google was, or social media or any of these companies that had Wall Street and the world economy. So, you know, we don't know.
Speaker 1:We don't know yet, but what we do know is that there are going to be a lot of change that comes with this, just like back when the agricultural workers had to go to the factories, back, you know, many decades ago. This change will happen. Everyone thinks it's going to displace workers, but you know, the world's population has to do something. Ai is just going to liberate the ability for us to do things more dynamically, the way that we went from rail cars to airplanes. So I think we just have to have a perspective on that and be patient enough not to have too much anxiety on the things that we don't know, and there will be adjustments, and so I think the upside is that we'll do a bunch of dynamic things on curing disease and finding new technology.
Speaker 2:I like your optimism because I hear a lot of what you just said and I hear it in a much negative skew, but I usually think we seem to do okay Talking. Then, at a more practical economic standpoint, I believe partners and channel are going to have to change and fundamentally it's because the skill sets are going to change. I find it really interesting to see some of the hiring practices that have changed very recently. Right, as soft dev and coding has become less of a priority, which three years ago that would have been impossible to even imagine. Right, it was the most highly sought after role and actually now I think what's going to happen is much more EQ and consultancy is going to become highly rated because actually the practicality of coding ones and zeros is going to become less relevant. We see products like Lovable doing amazing things, as you were able to vibe, code and create technology. Really, really simply. What do you think that's going to do for the key players in the industry? How's that going to change who we hire and how we train?
Speaker 1:Well, like you said, everyone's got to go through an adjustment in this process and, like long range weather forecasting, the vast majority of those folks are probably more wrong than they're right. Majority of those folks are probably more wrong than they're right. And with this technology, there certainly is going to be displacement of things that are either mundane or just things that don't matter, but there will equally be a level of liberation for those that understand how to use those tools and I think that's the re-skilling you got to remember. Every time this makes a shift, there's also a shift to either new businesses starting up or new roles starting up, and it's that pivot that I think presents the opportunity.
Speaker 1:Now, am I all upside? Am I all just ducks and bunnies? And there's no downsides? No, I'm equally weighted between upside and downside. I'm equally weighted between upside and downside, and so I've certainly been talking from a level of optimism and you know, trust me, there's a lot of stuff that's going to go through that I'm sure will be heartache for a lot of people that have to do these adjustments. Nobody likes this level of changes. Nobody likes going through, say, a level of school for jobs that get transformed and they've got to figure out how to go reskill themselves.
Speaker 2:But that's just part of life. Yeah, and I'm hoping the internet was revolutionary. My personal belief is AI is going to be the biggest change to humanity, even industrial revolution, and internet, I think it's going to be a factor even above that. But those were net wins right, while complicated in the moment. Um, maybe. Then zooming right back to our core audience, we speak to channel leaders and partnership leaders all the time. Um, and I hear them. I hear often our customers, our partners, talking around and they've been giving an ai mandate right, go and work it out. Go and work out how to implement it. It is important, it's going to create change, and they sit there and go. How? So, short question, how, keith? What's the framework they should think about?
Speaker 1:Well, again, the how is in the art of the possible. I think there's a lot of super easy tactical ways to land AI. As we mentioned, the chat GPT, the chat bot thing, is the easiest thing to land, whether people have or don't have an internalized private GPT. They should because you shouldn't be exposing your code out to the public. Same with, probably, intellectual property. And there's easy ways to privatize. You know those GPT engines, so that's an easy one right there.
Speaker 1:There's also several other, depending upon if it's an industry that's got, you know, say vision or robotics or any other acoustics, or, you know, analytics around data. There's tons of ways that you can apply old and new school AI techniques in the models to find the easy things that need to get transformed. That's where the opportunity for the partner isn't just technical, isn't just bringing infrastructure, isn't just bringing a total, you know, package. And what NetApp, again, I think, presents out to the partners is that opportunity to say you know, we have a data platform that gives you the ability to reorganize the data, escape the silos which are one of the problems you have in making AI successful. You know, and then, as you get into the opportunities at these business levels, these industry opportunities. You know we have one of the more robust and broad-based ways to succeed, no matter which way the customers got preference to adopt.
Speaker 2:Awesome, Keith. I think it's both exciting in the medium to long term, but I actually think maybe even more exciting in the short term to watch how businesses and individuals are able to make that change. We also experience change on this podcast, which is why we like to cheat. We always ask our current guest to recommend our next guest. Keith, who do you have in mind?
Speaker 1:I have so many people I could recommend. We've got Russell Fishman as the first person I could think of in mind. He's been my partner in crime since almost the very beginning Seven years ago. He runs solutions within AI solutions and other solutions within NetApp. He'd be fantastic. Vinning runs the AI alliances at NetApp. Ray White, who is my partner in crime doing this AI mission within NetApp, and the Worldwide Partner Organization. Tony Chidiak, who runs our worldwide go-to-market for AI. Don Foster, our CTO. I got several. I got a list a mile long of interesting people both at NetApp and outside of NetApp that I can give you.
Speaker 2:Awesome, Keith. Well, look, we appreciate the network advice and also the advice. Thank you so much for sharing your wisdom. It's been awesome.
Speaker 1:Thank you.