Insight ON Why ‘Good Enough’ Infrastructure Fails in the AI Era

Audio transcript:

Why ‘Good Enough’ Infrastructure Fails in the AI Era

Hilary Kerner: (00:02)

I've heard you say that data strategies from even just 18 months ago may already be obsolete, um, against this massive pressure that AI is putting on infrastructure. What's happening under the surface that's making good enough infrastructure a riskier bet than maybe it used to be?

Tim Coogan: (00:20)

Yeah. So it's tricky and it's, it's, I, I, the way I look at it is that you could be just good enough in the old world, and then that old world isn't that long ago. But if you don't have the right infrastructure to support, you know, AI at scale, cloud at scale, uh, there is no good enough, uh, either works or it doesn't. And I think that really changes the game in terms of the way you plan.

Jillian Viner: (00:42)

Welcome to Insight On, if you're making technology decisions that impact people, budgets or outcomes, you're in the right place. Hi, I am your host, Jillian Viner, and it was our second episode ever when we had Insight CMO, Hilary Kerner join us and give us a preview of what was happening in marketing with the impact of AI. Hillary's back today to give us a brief update of what's been going on with marketing and their AI initiatives, and gives us a little sense of how the market's feeling, what other challenges were leaders facing? Then first, now what's the sentiment of AI progression? And she tees up a conversation that she had recently with Tim Coogan, senior Vice President of Global Partner Sales at Cisco. Alright, let's go. Hillary, welcome back.

Hilary Kerner: (01:25)

Thank you. Thank you for having me back.

Jillian: (01:26)

It's been about six months since we've had you during that time, six months just feels like forever ago in the world of ai. It

Hilary Kerner: (01:34)

Is forever in tech in general. Yeah. Yes,

Jillian: (01:37)

Yes. And I wanna say during that conversation, you had so much optimism because there was so much going on in ai, especially in our marketing department with a lot of experimentation. People that you were talking to were exploring use cases. Again, it just seemed like there was a lot of opportunity. And I'm curious, six months later, what's the tone these days?

Hilary Kerner: (01:57)

Well, I still have that optimism, but it's becoming increasingly clear how quickly these things are changing and how rapidly we as marketers need to evolve. The good news is that we set really ambitious goals for ourselves. I'm really proud of everything that we achieved. Um, and I'm also really proud of not just the goals that I set, you know, from a tops down, but from the bottoms up organic use cases. I think I said in our earliest co earlier conversation that some of the best use cases are the least sexy ones that are coming from teammates who are trying to solve a problem that is like creating that soul sucking part of their jobs. Mm-hmm . And freeing their time up to focus on the part of marketing that that brings them joy. And it's really awesome to see how far along some of those use cases are and how much our team has really embraced using these tools to make their lives as marketers better.

Hilary Kerner: (02:55)

Um, I'm pleased with how we've been able to achieve scale. So, um, we were able to do more for our partners. Um, we were able to bring our clients more value. I think because we are, it's easier to replicate and personalize things at a, a scale that maybe we couldn't in the past. Um, and I'm really pleased at some of the non-traditional use cases, so marketers who are experimenting with AI to build things. Yep. Which is really, really cool. Um, so love it. But at the same time, you know, every day there's a new tool every day the tool is better. It can be kind of, um, daunting to keep up with the new model releases. I really love how Insight has made the latest and greatest models across all of the different vendors available to us, because that not only one gives us access to the latest and greatest, but it gives us credibility when we're talking to our clients because we have experienced personal experience using all of these different tools. Yeah,

Jillian: (03:52)

Absolutely. And in the six months since we've talked, I remember at the time you mentioned you were talking to other CMOs who were kind of like, Ooh, what are you guys doing? And you've, you've also talked to business leaders outside of marketing, different titles, different, uh, leaders from organizations in healthcare or finance. So in that broad spectrum, when you think back at the conversations back then compared to today, how would you rate the progress that they're making? Are the challenges the same or are they coming to you with different questions?

Hilary Kerner: (04:22)

Well, you know what's interesting, I think by this point everybody's done something. Yeah. Everybody's zero. Yeah. No one's at zero. Everyone has dabbled. Everyone has a pilot. Everyone has like a starter project. I think now. Um, they're grappling with the very real questions of scale and enterprise value. So it's, it's gone beyond, you know, I've, I've did this project, I tried this out. They're seeing now that the kind of enterprise value, like the real promise of ai, um, is coming up against like, some pretty real obstacles. You know, one of them is data. So in order to have more widespread enterprise value, um, you, you really need clean data. We've all heard, you know, garbage in, garbage out. Um, this is a problem for CMOs, um, because sometimes our customer data is sitting in a bunch of different places, but it's, it's true for any business leader who uses data to do their job.

Hilary Kerner: (05:17)

So data strategy comes up again, um, culture comes up a lot actually. So how do I work through kind of the cultural barriers to adoption, whether that's fear, uncertainty, and doubt, or, um, you know, where should the mandate come from? How do I drive organic adoption? The kind that we've seen be so successful in our, in our own company. Um, we have like very real infrastructure problems. And that's everything from, you know, what's on your tech stack to what are your enterprise apps, because the real value of AI is gonna come from very real change, and nobody's starting from zero from a tech perspective. You're not building that from scratch. You've got something you're working with already mm-hmm . So, um, I hear CMOs that are frustrated with these things, but you know, it's a business leader problem.

Jillian: (06:02)

Yeah. So it sounds like a little bit of, maybe not frustration across the board, but it does feel like there's a sense of being stuck

Hilary Kerner: (06:09)

There. There's a very real set of questions that need answers before somebody can move further. Yeah.

Jillian: (06:14)

So what is the answer to those questions? Like what do you, what do you tell a business leader that's been trying to push AI that believes in it and is feeling stuck? Is there something that like they hear or that you tell them that like, lights up and kind of changes the course of their belief?

Hilary Kerner: (06:30)

Well, there's not an easy answer. Um, I think one of the biggest things, um, that companies are seeing is that they need a different kind of partner. So in the past where maybe you'd be stuck and you reach out to like a consulting company for help, um, you know, a traditional aside that's gonna come in with a bunch of, you know, like a really, even just, you know, beautifully well-developed strategy that is not gonna do a whole lot for you. You need somebody who's gonna roll up their sleeves and like, get into your environment and help mm-hmm. Um, and if I, if you look at like the traditional ecosystem, there's no like one partner model that, or type of partner that's really set up to help companies navigate that change. Um, I think the channel owes it to our clients to become a new kind of partner that's gonna be kinda one part consulting around the, the business process, understanding the business process and understanding of the tech stack, have the actual technical expertise to get, you know, hands-on keyboards and kind of get in. And we talk about that, like the forward deployed engineer model. Um, you need both, you need kind of all those, those types of experts and the expertise in the tech itself. So not just the infrastructure, but the ai, the models, the environment within which you're working the data. Um, it's really challenging, um, us to step up and be that new kind of partner.

Jillian: (07:53)

You were hitting on something that came up in a recent conversation you had with a leader at Cisco, Tim Coogan. Is there something that he said that really stood out to you during that conversation?

Hilary Kerner: (08:02)

Tim's role is really interesting because he has a front seat to what's happening in infrastructure. Um, that's one of the things that, that Cisco does really well. And, um, he's seeing this pattern emerge among clients who are kind of facing this very same type of obstacle.

Jillian: (08:19)

Let's hear that conversation. Thanks, Hilary.

Hilary Kerner: (08:22)

Why don't we start to invite you telling me more about your role at Cisco. What do you do? Great.

Tim: (08:27)

So, um, it's great to be here, by the way. I'm, I'm thrilled. So I'm the senior vice president of, of Cisco's global partner organization. And so it's a relatively new role for me. I've been at the company almost 26 years, but only in this role for six months. So I bring a maybe a little different perspective, but, uh, working with our partners each and every day is very, very rewarding.

Hilary Kerner: (08:44)

So in 26 years, you've no doubt seen a lot of change on the, uh, enterprise infrastructure side from web to mobile to cloud. How is AI different?

Tim: (08:57)

Well, so AI is different. I, I think back to my early days at the company, you know, customers bought for a very specific need in a very specific timeframe. Uh, that is, that is being challenged by ai. And the way you need to build out for AI is very, very different than that. It's, it's not a point in time. It's a decision to begin a journey in a very unique way, thinking about the restraints that are put on us, not just, not to mention supply chain, power, cooling, all of those things. So AI requires a, a very different approach to planning.

Hilary Kerner: (09:26)

So you're watching enterprise clients place bets? Yeah. Um, where are they placing their bets? What are they spending money on? Yeah,

Tim: (09:33)

So I think they're, they're placing their bets in two places. One is they're getting their infrastructure ready, uh, whether they're ready to dive into the deep end of AI and use it in, in terms of inferencing case, you know, use cases, for example. But they know their networks need to be ready, their data centers need to be ready. So that's kind of the first bucket. The second bucket are those customers that are really leaning into changing the way they go to market based on leveraging ai. There's obviously been lots of talk about what AI does to jobs. Mm-hmm. Um, I don't necessarily believe that AI is a job eliminator. It's a job changer. And I think some of our customers are really, really leaning into that piece of it.

Hilary Kerner: (10:09)

What about the customers who aren't seizing the moment or are hesitating to act what's happening with them? Yeah,

Tim: (10:15)

I, I hesitate to be dramatic, but there will be, as with any transition, those that either don't believe it's real or take far too long to act on it. Um, and I, and I don't necessarily like the comparison of winners and losers, but there will be winners and losers, and I think sometimes if you don't thoughtfully plan for the future, there's a negative side effect to that.

Hilary Kerner: (10:36)

I've heard you say that data strategies from even just 18 months ago may already be obsolete, um, against this massive pressure that AI is putting on infrastructure. What's happening under the surface that's making good enough infrastructure a riskier butt than maybe it used to be?

Tim: (10:54)

Yeah. So it's tricky and it's, it's, i i, the way I look at it is that you could be just good enough in the old world, and then that old world isn't that long ago. But if you don't have the right infrastructure to support, you know, AI at scale, cloud at scale, uh, there is no good enough. It either works or it doesn't. And I think that really changes the game in terms of the way you plan.

Hilary Kerner: (11:16)

So it's such an interesting conversation to me because, you know, people talk about ai, like the biggest challenge is gonna be actually getting the deployment up and running, when really there are so many different infrastructure considerations that need to be thought through before you can even begin to make progress.

Tim: (11:30)

Yeah. It's, I've, I've heard it, you know, referenced that, you know, in the, again, I'll use that old world cliche, which I don't like, um, but you could make a, a decision in at a point in time, I'm gonna build this data center to this capacity. AI is different. It's gonna come incrementally. Uh, we're gonna, we're gonna use that power in central locations like data centers, but AI will be a feature at the edge as well. Mm-hmm. So I think it requires us to look at things very, very differently.

Hilary Kerner: (11:55)

So let's talk about the leaders who are skeptical of AI timelines. They're not convinced that AI is gonna transform their business anytime soon. What would you say to that leader about their infrastructure, regardless of where they land on ai?

Tim: (12:08)

I'm, I'm gonna be a little cheeky here. Um, I think those leaders need better advisors. They need it. They need people that are, that are opening their eyes to the fact that this is now. Now it doesn't mean that you have to do it all at once. We've talked about that, but I think you have to be thoughtful and start the planning process. Now, this is the, the, this is, if you don't think it's coming, I, I think you're not, you're not getting good advice.

Hilary Kerner: (12:29)

Um, I talk a lot about how I think this moment demands a new kind of partner, um, because it, there's so many things that are different about this moment, but you have a front row seat to that as well, because you see what all the partners are doing across, uh, Cisco's ecosystem. What patterns are you seeing? What, how is the channel changing?

Tim: (12:46)

Yeah, so it's, it's a, it's a great question. And, and I'll say again, the Cisco that I joined all those years ago, you know, there was a transactional element to our relationship with our partner ecosystem. That's not a negative, I don't mean that in a bad way, but it was, I need to buy this in this quantity and I'll execute it through this ecosystem. Partners are now responsible, quite frankly, for, for weaving together the various elements of a solution in a way that is much different than transactional. It is more outcome, and it is more solutions and value oriented. And I think that that ability to knit together the fabric of solutions today, uh, that burden is, is squarely on the shoulders of our, of our ecosystem partners.

Hilary Kerner: (13:25)

That's no doubt what makes us such a great partner.

Tim: (13:27)

Absolutely.

Hilary Kerner: (13:28)

Um, tell us some cautionary tales. What should we be thinking through? Yeah,

Tim: (13:32)

I think, I think the cautionary tales are something that are the same. I think it's, it's the, the, the, the, the, the, the, where I get reserved is if you move too quickly and there is some possibility to move too quickly. I think everybody wants everything now. Uh, but you've gotta be balanced. And I use that word quite a bit. Uh, I'd rather move a little too fast than a little too slow. So I think the cautionary tale is to make sure that your business is prepared for whatever direction you decide to go

Hilary Kerner: (13:56)

Smart. Um, the same way that, you know, we can't have a conversation right now without talking about ai because it is everywhere. What is something that's not getting enough airtime that should,

Tim: (14:06)

So I, I think it's the outcome of, and I'm gonna, I'm back to that word outcome. Mm-hmm. I think it's the outcome that AI delivers. Uh, you know, having a thousand GPUs in the, in the compute power and the server power behind that is good, but what are you using it for? I think that I'd like people to be a little bit more thoughtful about what am I gonna get from how am I gonna deliver a competitive advantage or a different experience for my end user by leveraging ai? Because, uh, you know, I, like many people not that long ago, was using AI as advanced search. Nothing wrong with that, but it needs to become part of the way you strategize, part of the way you go to market. And I think that's something where I think folks could spend some more time.

Hilary Kerner: (14:44)

Um, similarly, I mean, I heard you talk about data center capacity, you talked about cooling. Yeah. What's something from the infrastructure perspective that clients are not thinking about enough in your, in your opinion?

Tim: (14:53)

Yeah, I think it's back to that timeframe. It's, it's, uh, you used to be able to outbid somebody for, let's say, just use power as an example, but we require not just in, in the United States, but across the world, a redefining of how we invest in power infrastructure. That's not a couple year journey. That is a couple decade journey. And I think that we need to be mindful of the fact that it's gonna take time to get where we all need to be.

Hilary Kerner: (15:18)

I think a lot of vendors talk about how important the ecosystem is, but how does an enterprise leader evaluate whether a partner is genuinely adding value?

Tim: (15:26)

Yeah. So I'm gonna, I'm gonna be a little, I'm gonna be the Cisco guy for a minute. Uh, we've just introduced a, an ability for our customers to do a thoughtful and meaningful search around what a partner can bring to the table through our partner locator. Um, it's a way to understand the capabilities of a partner, maybe their experience, their work that they've done in the past, and really match the capabilities of a partner to the requirements of the firm in a way that's very different than the traditional RFP process.

Hilary Kerner: (15:53)

So for the, uh, the leader who's listening to this conversation and it is hearing themselves, what should they do next? Who should they call?

Tim: (16:01)

Well, of course I'll be a little biased. I think they should call Cisco and Insight. I think that would be a wonderful first call. I think what they should do is talk to their, their business owners. Um, folks that are in information technology or in, in the, the, the corporate functions of, of our, of our customers should be talking to their businesses, understanding what their roadmap looks like, what do they want to be, how do they changing again, their customer interactions. I think understanding their business in a way that goes beyond routers and switches and access points, I think is really important at this point in time.

Hilary Kerner: (16:32)

So this is gonna sound like a very self-serving question, but I don't mean it though this way, but why is it so hard to do it alone?

Tim: (16:38)

Oh, I don't think it's hard to do it alone. I think it's impossible to do it alone. Um, I'm incredibly proud of what Cisco's brought to the table. We've, we've built and partnered and organically and inorganically built this incredible portfolio, but we can't do it ourselves. We need partners to help us even run our own business. Uh, so I think it's, it's hard because the output and the outcome is so incredible. If all I wanted to do was send email from one place on a college campus to another, which is a little bit of the history of Cisco, that was easier to do on your own. But what I wanna change the way I go to market and the way I interact with my internal and external, you know, users that requires partnerships.

Hilary Kerner: (17:16)

Well, thank you so much to my appreciate the conversation. I think, uh, thinking about the infrastructure demands that AI is gonna place, um, is something that we don't talk about enough, so I appreciate

Tim: (17:26)

It. No, it's been my pleasure. It's very exciting. I think what's ahead of us is an incredibly exciting time.

Hilary Kerner: (17:30)

Awesome.

Speaker 4: (17:32)

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