Cisco's AI Strategy and the Future of Enterprise Growth

[00:00:04] - [Speaker 0]
Every year at Cisco Live, there are conversations about products, platforms, and technology announcements. But every now and again, you get a chance to step back and talk about the bigger picture. So at Cisco Live this year, I've sat down with Cisco's chief strategy officer for a conversation about disruption, innovation, and what it takes to stay relevant during periods of extraordinary technological change. I will discuss today why AI should be viewed as a business transformation rather than simply an efficiency tool. And I wanna find out more about how Cisco approaches strategy in a world where breakthroughs seem to arrive almost every week, and why successful innovation requires far more than deciding whether to build or buy technology.

[00:00:55] - [Speaker 0]
So we'll discuss everything from start up trends, venture investing, technology incubation, business model disruption, and what leaders need to understand if they want their organization to thrive in an AI age. Ultimately, today is a conversation about the future, but it's also a conversation about making better decisions today. And with that scene perfectly set, let me introduce you to my guest. So thank you for joining me on the podcast today. Can you tell everyone listening a little about who you are and what you do?

[00:01:32] - [Speaker 1]
Thanks for having me. So I'm Amar Moraka. I am the chief strategy officer at Cisco. What that means is I own a handful of teams. So corporate strategy, our m and a, and in core corporate venture investment teams.

[00:01:46] - [Speaker 1]
I own the teams that run planning and business cadence, and I also own the Outshift team, which is the team at Cisco that does technology incubation. So it's a it's a a collection of of teams really with the the primary mandate is really a, help the company think about disruption and bring that disruption from the outside in. And then we also partner with a lot of our leaders to both drive strategy and help accelerate the the the growth of the company where we can.

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And you've been in the chief strategy officer role for almost a year now. When you look across the tech industry today, where do

[00:02:23] - [Speaker 1]
you believe business leaders are are possibly misunderstand or what are they possibly misunderstanding about the current AI era? Lots of change happening. So my point of view on that is maybe what they're misunderstanding or maybe not keeping or not thinking about in the way I am is that AI really is not an efficiency tool. I think you lot a lot of times you hear about AI in the context of efficiency or productivity that sometimes leads you to believe it's more of a cost, maybe a cost exercise. I really think it's much more of a structural change that every company is gonna go through.

[00:02:59] - [Speaker 1]
It's about doing work very, very differently. It's about amplifying work. It's about making it just getting more done within the same amount of time, same amount of teams that you have. And so I think if you think about it as a as an efficiency play, you may underestimate the type of change you have to make in the company and also probably suboptimize the benefits you can get out of AI.

[00:03:21] - [Speaker 0]
And many companies seem to be constantly adjusting their plans in response to every market shift AI breakthrough or even geopolitical events. At Cisco though, we're talking here about the importance of having one ongoing strategy, so refreshing to hear. How do you balance that long term conviction with that need to remain adaptable? And one of the reasons I say that is Chuck Robbins on stage the other day was saying that three months ago, all we were talking about is rum, and now we're talking

[00:03:49] - [Speaker 1]
About about mythos and about a whole bunch of other thing. Yeah. No. That's that's that's exactly right. So I'll tell you the way I think about it is one of the most important things when you're putting a strategy together is to be very clear about what assumptions you're making that underpin that strategy.

[00:04:03] - [Speaker 1]
The assumptions really are informed by what do you believe is gonna happen in the market, what's happening on the technology side, customer side, partner side. You really try to synthesize all of these inputs to say, what do you believe is gonna happen? What are your assumptions about your own competitive competitive differentiation and where you're good at, where you need to get better at, where the opportunity gonna be? Document those assumptions, And then what you should be doing on a regular basis is testing those assumptions and really being clear eyed about has anything changed that would require me to adjust course. I think changing strategies every, you know, six months really means you probably didn't have a good strategy to begin with, But what you should be absolutely testing all the time is the assumptions that you had as long as you they're well well articulated, you're able to at least double check, test those assumptions, be clear about, be be sort of truthful about whether whether the initial assumption made sense, have have things changed in in in technology, the chances are things have changed.

[00:05:02] - [Speaker 1]
And so instead of changing the strategy, you really should think about the assumptions and then adjust based on where you believe the world is headed now or the assumptions that you made in the in the past. That's the way I sort of think about it.

[00:05:12] - [Speaker 0]
Yeah. 100% with you. And one of the things that stands out about Cisco is that growth isn't viewed simply as a build versus buy decision. So how do you decide when to build an internally acquire, partner, invest, or incubate an idea? And what factors influence those decisions?

[00:05:30] - [Speaker 1]
So you you articulated the the five levers that build, buy, invest, partner, and incubate. And we think of them as a complementary set of levers that you really pull depending on what you're trying to achieve, but they're all levers that we use to accelerate growth. So build versus buy is too narrow. It's very important to always think about build versus buy because most companies build is the primary vector for innovation. It's where you spend a lot of effort, energy.

[00:05:57] - [Speaker 1]
Buy really allows you to use the ecosystem around you as an extension of your own r and d, and so it's really important. And typically, you do that for time to market advantages or capability advantages, and it's a really important muscle to develop. Every time a a GM needs to think about their growth strategy, they really should think about m and a as as a lever of acceleration. But sometimes you a market is too early or you need to learn or you don't really have conviction yet about whether you need to own something or maybe you need to partner and so you end up investing. You you you take an active position in the company.

[00:06:29] - [Speaker 1]
You you know, through an equity investment. But the the most important part there is you're able to learn, you're able to interact with the company. You're able to understand sort of what bets are they making and and help influence or bring that disruption back into the company. And so as long as you do it in a with a clear objective as opposed to just trying to make money or or, you know, following following a trend, as long as you have some rationale for why you're doing it, what what what specific learning you're trying to do, investment actually is a great vehicle to keep optionality open, but also get close to technology, get close to great people building building products. Incubate is really where you're trying to think about net new technologies that's further out.

[00:07:11] - [Speaker 1]
They're not ready to be mainstreamed from a from an r and d perspective or technology perspective, but you're trying to understand, do you have a play? Is there enough technology understanding for us to to make an impact for our customers? Is it too early? What needs to happen for it to be commercialized and and mainstream? Then I think that the the the trick about incubation is you have to give the team some slack to actually think about the future in in a way that isn't quarterly focused.

[00:07:38] - [Speaker 1]
But you also have to have very rigorous graduation milestones so that you constantly know you're making progress. And then think about, hey. I built something interesting. Maybe it's time to open source it. If it's not something that you wanna give to a to a product or or an engineering team.

[00:07:52] - [Speaker 1]
Sometimes it is about about taking that product and and having it drive a particular road map that that an engineering team is driving. And so and sometimes you fail and the technology isn't doesn't isn't ready for commercialization. And so it's a great way to, again, keep optionality open, but also think about net new technologies that may not be ready for the mainstream, but you at least have a team that's thinking about it. And then partnering, you know, I I think that's relatively clear. Cisco's always been very partner oriented as a company.

[00:08:19] - [Speaker 1]
We have 37,000, you know, ecosystem partners, resellers, service service partners, etcetera. But we also have technology partners that are very important to us like NVIDIA or AWS. And and and that's really about developing and delivering solutions to customers because at the end of the day, the world heterogeneous and and and they wanna drive outcomes. Customers wanna drive outcomes. And so we partner when we feel like there's complementarity.

[00:08:43] - [Speaker 1]
And even if there's overlap in the technologies or in the products in a certain part of the business, we we we believe that customer outcome trumps everything, and so we're very open from an ecosystem perspective. It's really important part of the strategy.

[00:08:55] - [Speaker 0]
And you also work closely with Cisco's incubation teams, venture investments, and corporate strategy groups. What have you learned about innovation inside a company with Cisco scale that that might surprise people?

[00:09:08] - [Speaker 1]
I I think what surprises people, at least what surprised me, when you have a lot of scale, you actually have a lot of market sensing that happens across the company. Think about where we have customer we have over a million customers in a 150 countries. Just think about the breadth and the scope of the type of customers from small business to enterprise to large government organizations. If you're if you have the structure to listen to feedback, you actually have a great amount of information that's coming into the company. A lot of partners that also give you a lot of feedback all the time.

[00:09:40] - [Speaker 1]
We have the scale to invest in companies. We are interacting with venture capitalists, with entrepreneurs all the time. If you find a way to synthesize all that information, again, it drives the assumption set that I talked about at the beginning when you're setting strategy, but it also gives you a lot of information about what's happening, and it really helps drive innovation if you're able to harness it. And so even though scale sometimes can slow you down, it can also if if if harness properly can can be a great opportunity to just listen to so much more than if you just are selling to one particular customer segment or maybe in in one geography. You really have the breadth to be able to synthesize and correlate across lots and lots of data points.

[00:10:16] - [Speaker 1]
So maybe that's something that people don't think about naturally for when companies have a lot of scale.

[00:10:21] - [Speaker 0]
And I think many organizations struggle with the tension between protecting an existing business and creating the next one. How do you

[00:10:28] - [Speaker 1]
at Cisco avoid becoming maybe constrained by your own success? So I actually think innovating when you have a very successful business, innovating something that maybe is not germane or core to that business or even disrupts that core business, I think that's the hardest problem in business because you're you're a victim of your own success. And so our lessons learned around that, we we you know, nobody's done it perfectly, but the way we've tried to to to tackle it is a, create a separate team that thinks about these further further along incubated type of technologies. Don't let them be governed by what you need to deliver quarter to quarter because there's enough pressure there that's very hard then to think about things that are way further out or have a lot more risk. So that so that's number one.

[00:11:10] - [Speaker 1]
Number two, you have to basically be very clear about what is the risk that you're trying to mitigate when you incubate. And and for us at Cisco, the Outshift team that does incubation really thinks about two different types of risks. There's technology risk. So it's an interesting technology, but we don't know yet whether it's real, whether it can be commercialized. You know, quantum networking is a good example of that where we're doing a lot of research there, but but we're trying to derisk the the technology risk.

[00:11:35] - [Speaker 1]
The other type of risk is market risk. So maybe the technology is there, but we don't know whether it can be commercialized properly, whether there's enough of a market for it. The kinds of activities and metrics you do there are different, but you you go through a a phase gate process where you're trying to understand it more and more and then make a decision about is it ready to graduate, whether it's, like I mentioned, to an open source, whether it's to in a product road map, whether it's, you know, ready to be commercialized, you you make that decision, but you're doing it based on the metrics that you've set out to at the beginning as opposed to needing to adjust based on quarterly pressure that that you may be under. So at least that's the way we've tried to do it. It's a very difficult problem, but I think giving the team the room to think about these things in a in a longer time horizon, I think, is very, very important.

[00:12:23] - [Speaker 0]
And because you oversee investments and acquisitions, I think you have a unique view into emerging startups and technology trends. So what themes are you consistently seeing appearing in conversations with founders, innovators that that maybe enterprise leaders listening should be paying closer attention to. Any big trends? One of the biggest trends I see is there is a lot of innovation happening in silicon and core infrastructure. And if

[00:12:50] - [Speaker 1]
you think two, three, four years back, I don't think there were a lot of innovation or venture capital money going into silicon. But fast forward to today, you know, it's an incredible ecosystem now with lots and lots of innovation. So that's one thing for technology and business leaders to be thinking about. There's gonna be a lot of innovation going after some of the bottlenecks that we're feeling today as we scale this this new AI infrastructure, whether it's in silicon, in power, in memory, all of these interconnects, you know, speed, all of these. There's a ton of really interesting startups and and entrepreneurs in that space.

[00:13:22] - [Speaker 1]
I think the other two themes I see, one is there are a lot of there's a lot of energy now in what I call sort of enabling technologies for this AI adoption in the enterprise. So think about security or orchestration of agents or how do you bring your data together so that agents can have a context layer for the enterprise. Lots of interesting ideas around how do you secure agents and drive observability and some of the things that we announced today. At Cisco, we actually acquired companies that that had capabilities in that space, but there's a lot of innovation going on in that in that area. And from an enterprise perspective, it should be thought of as they're trying to solve real problems around AI adoption at the end of the day within a context of an actual enterprise.

[00:14:02] - [Speaker 1]
And then the third the third maybe theme is a lot of interesting companies trying to use AI for specific vertical productivity use cases. And and that one is, you know, the jury's still out on how many of those are gonna be independent companies serving those use cases versus just the foundational model players just going after those use cases. I think I think the the the jury has been has has is out on some of the use cases outside of, say, software development, which we know now OpenAI and Anthropic and a lot of these companies have already claimed, and maybe software and maybe customer service. But there are a whole bunch of other use cases and other functions where there's gonna be some interesting innovation coming out. And there I think the the theme is is let's see what kind of traction these companies get and can they how sustainably can they drive value from the foundational models.

[00:14:51] - [Speaker 1]
And it's just gonna be interesting to see.

[00:14:52] - [Speaker 0]
Yeah. Exciting times ahead. And if we look at the AI market today, where do you see the greatest disconnect between the hype that we often see on our news feeds and the reality of what your customers are actually demanding and and the

[00:15:05] - [Speaker 1]
many conversations you've probably had this week as well. I think the there's a there's a term that was coined around this whole AI disruption called the capability overhang, which is really just the power of the models are increasing so much faster than the enterprise's ability to to actually adopt this technology. I fundamentally believe in that overhang, and it's only gonna get bigger and bigger. And so so to me, it's it's really thinking through what is it gonna take in real life deploying these things and getting real value out of them. And I think a lot of it comes down to what I call, you know, boring things like you gotta invest in the underlying infrastructure.

[00:15:45] - [Speaker 1]
You gotta have the right data. You gotta have the right access controls, the right security. All of these things that, you know, you can't just just wish away and and won't be solved if you if you don't actually do the hard work of creating that infrastructure and modernizing and getting ready for that. And then the other one is much more of a of a people human problem, which is you need to redesign workflows and you need to have people adopt technology and you have to have drive the change management required. And if you don't do those two things, one is infrastructure, but the other one is very people.

[00:16:15] - [Speaker 1]
My sense is we won't really solve that capability overhang. And and I think that that last mile deployment is gonna be very important because you can't you can't just throw an AI tool and expect productivity. You really need to do the hard work both setting up the right infrastructure, but also going through the the change management required to actually adopt it. And I I I think we're at the early stages of both of those.

[00:16:35] - [Speaker 0]
And if you were advising your CEO outside the tech industry industry, who who could could be be listening listening today, today, what would you tell them is the single most important strategic decision that they need to make about AI over the next twelve to twenty four months? I know it's a it's a big question to ask, almost an episode on its own, but what would you advise her? The the one thing

[00:16:57] - [Speaker 1]
I I think if I'm the CEO, I think I would advise them to, you know, prioritize one or two use cases in the company, something that's really critical to their differentiation and go very hard on leveraging AI to redesign that entire workflow. Pick one or two, drive it from the top, make sure that you are keeping track of what it would take foundationally to make that happen, and go drive it. Put your real real emphasis behind it. I feel like being able to do that gives you the the blueprint to say, how do I then go after other AI use cases in my in my environment? But it also gives you a sense of what some foundational technologies you need to develop or to deploy in order to make those successful.

[00:17:43] - [Speaker 1]
Those types of foundational investments are probably gonna be beneficial regardless. And so you as a CEO champion or two of those use cases, drive it from the top, worry about the change management required, and and and celebrate the ROI that's that's invariably gonna come from that. And don't think of it as a as an efficiency play. Think of it as a as a way for you to just accelerate and do a lot more with the resources that you have.

[00:18:06] - [Speaker 0]
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[00:18:43] - [Speaker 0]
And at Cisco, you've been on multiple technology transitions from networking and cloud to security, now AI. What allow what do you think it is that allows some companies to successfully reinvent themselves over decades while others still struggle to adapt? Again, massive question, but where do you stand on this?

[00:19:02] - [Speaker 1]
I think companies that reinvent themselves, first and foremost, have the ability to be honest about what's happening in their environment and the impact on the competitive advantage or the differentiation that trade they drive in the market. And what I mean by that is if you're if you're sort of drinking the Kool Aid, if you will, if you're not honest that there's a disruption happening in your market, By the time you realize that across the entire company, it's probably too late because things are happening so fast. So how do you set up mechanisms to always be sort of truthful in synthesizing the market feedback that you're getting, whether it's from customers, from technology, from market share, win loss, you know, all of these things to basically have an honest assessment of where are we, what is our position, are some of the things that used to give us advantage in the past, are they eroding or not. I think if you have the ability to synthesize that information and be truthful about have a forum that allows you to to be truthful about whether or not it's impacting your business, I think that to me feels like step number one.

[00:20:09] - [Speaker 1]
And then saying, what do we do about it? And if you catch it early enough or if you have the ability to reallocate resources, you can reinvent yourself. If you feel like you don't if if you act as an incumbent and you don't take advantage of the fact that you need to be aware of what's happening around you and really be honest whether on on whether or not you're being disrupted. I think it's very hard to catch up. And so maybe that's that's the thing, which is create first of all, make sure you have these inputs coming into the company.

[00:20:37] - [Speaker 1]
Make sure that they don't get diluted as they, you know, travel up the management chain. And then just be honest about having these conversations about your differentiation, your advantage, and whether these things are still holding true or not. I think you're able to reinvent yourself if you're able to recognize that your position is either getting weaker or stronger. If you can't, then it's gonna be very hard for you to change.

[00:20:58] - [Speaker 0]
And one of the things I try and do on this podcast every day is bust a few myths and misconceptions or lay to rest a few things that might frustrate you when you're scrolling down your LinkedIn feed. So are are there any widely accepted assumptions about the future of where enterprise tech's going that you might personally believe is wrong?

[00:21:16] - [Speaker 1]
Well, I I think it's it's hazardous to forecast enterprise technology these days, I would say. But and and I I like to say the one thing you know for sure about a forecast is that it's wrong because it's a forecast. I think one of the things that maybe is is something I believe and maybe is underappreciated is I think the disruption that's happening in the monetization models of SaaS companies feels very real and very genuine. So this sort of per seat model that has served a lot of enterprise companies, enterprise software companies so well, I think it's fundamentally going to become under a ton of pressure. And these companies adopting AI or or embedding AIs that in their workflows, think is great, but I don't think it's gonna fundamentally address this monetization challenge that I feel is is gonna be coming their way.

[00:22:09] - [Speaker 1]
I think that's one thing that I've learned over time is actually business model disruption is much harder to defend against than technology disruption because because it's so when you're a successful company, you've built your entire set of processes really to drive a particular business model, and you're very you become very good at it, especially at scale. Trying to adjust to a business model disruption is so much so much harder. We saw that when when actually people went from on prem to cloud from a monetization perspective or when when the models went from traditional consumption to traditional pricing to consumption based pricing, those tend to be very hard to implement. And I feel like we're at the cusp of something from a monetization perspective. It's gonna be pretty profound for software companies if their model is monetizing a seat based license.

[00:22:57] - [Speaker 1]
So maybe that's the thing that that that would be interesting to watch.

[00:23:00] - [Speaker 0]
And finally, you've had a packed week this week talking with media analysts, customers, your own team. When you finally get home and you find yourself just decompressing, trying to digest all the information, all the conversations, what are gonna be taking back and reflecting on? You know,

[00:23:18] - [Speaker 1]
I think from an industry perspective, I think the pace of change is something that that is really astounding. If you think about if we were having this conference two months ago, we would not have been talking about Methos. We would glass wing. So many new things have happened just in the last sixty or ninety days that I think I think customers and partners and even vendors need a lot of help. There's a lot of we need to step back and think about things, but we don't have a lot of time to figure out what we need to adjust.

[00:23:47] - [Speaker 1]
So it's it's that has been a theme probably throughout all of my conversations, just the amount of change that's happening that that people need to absorb. That that's one theme. I think from a Cisco perspective, it's been great to see the reaction to both the fact that we have had consistent strategy and message for the last couple of years, which I think has been a welcome development for a lot of our partners and our customers. And then the other one is we've started now to to actually to actually drop the product and the the technology proof points of the strategy that we talked about, whether it's around platformization with cloud control or whether it's about trying to develop a broader set of services to help our customers or it's, you know, converging the platforms. All of these things that we've been talking about, we've now refreshed the entire product portfolio.

[00:24:38] - [Speaker 1]
So these things now are real. They're in customers' hands. And so being able to go away from just trust us, this is coming to actually having people give us real feedback on this technology. I think that's another thing that I will look back and and say that's a really great moment for us right now because almost every piece of product I think we've had at Cisco has been refreshed over the last sort of couple of years. And so we were in a really interesting time, and and we've done it in a really good from a timing perspective, it's been really interesting because we really do believe that modernization is about to take on a whole another sense of urgency, whether it's because of the the security issues or because of, you know, agentic and all these new workloads.

[00:25:17] - [Speaker 1]
And so that modernization has happened at a really good time for us because we feel really good about the portfolio that we that we now have, and we can help our customers throw it through that journey.

[00:25:26] - [Speaker 0]
And I think that's a thought provoking moment to end on. I will include links to everything at Cisco Live, including your LinkedIn and the work that you're doing. I urge everyone listening to check that out. But more than anything, thank you for sharing your vision today and strategy. Really appreciate your time.

[00:25:40] - [Speaker 1]
Thank you for having me. Appreciate it.

[00:25:41] - [Speaker 0]
One of the things I loved about this conversation today was how my guest consistently brought the discussion back to fundamentals. Because very often, conversations around AI focus on models, tools, and headlines, And he emphasized something much more practical, and that is that strategy is ultimately about understanding what is changing or challenging your assumptions and being honest about where your organization stands. And I was also fascinated by his perspective that AI is being misunderstood when it's viewed purely as an an efficiency play. Because the bigger opportunity lies in redesigning workflows, changing how work gets done, and creating entirely new ways of operating. And that requires technology, but it also requires leadership, culture, and a willingness to rethink some of those long established processes.

[00:26:37] - [Speaker 0]
And another theme that stood out was the pace of change. Throughout our conversation, he repeatedly highlight highlighted just how quickly the tech industry is evolving and how important it is for organizations to maintain that clear strategy while continuously testing the assumptions behind it. And perhaps my favorite takeaway was his observation that a business model disruption is often harder to respond to than technology disruption. And that's the kind of insights that stays with you long after the conference lights have dimmed. But as always, wanna hear your thoughts on this one.

[00:27:12] - [Speaker 0]
What's the biggest strategic assumption that your organization is making about AI today? And how often do you challenge it? Well, techtalksnetwork.com. Send me a message. Send me a voice message DM.

[00:27:27] - [Speaker 0]
We have 4,000 views across nine podcasts there. But thanks for listening today. I'll be back again tomorrow with another guest. And, hopefully, I'll get to speak with you again then. Bye for now.