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AWS and Deloitte: Building the Data and Cloud Foundation for National Security

CDO Magazine Podcast Series · 2026-10-30 · 13 min

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Key moments - from our scoring

Substance score

37 / 100

Five dimensions, 20 points each

Insight Density7 / 20
Originality5 / 20
Guest Caliber13 / 20
Specificity & Evidence8 / 20
Conversational Craft4 / 20

This conversation between Aditya Karkera, Chief Data Officer for Deloitte's Government and Public Services, and Samantha Fletcher explores how cloud infrastructure and AI are transforming national security operations. Fletcher brings a unique perspective shaped by direct military experience, including deployments to Iraq and Afghanistan and leadership of billion-dollar defense programs. The discussion centers on three critical challenges facing intelligence and defense agencies: compressing acquisition timelines to match evolving threat speeds, treating data as a strategic asset by breaking down silos across SIGINT, HUMINT, and other intelligence sources, and building AI-ready, cloud-fluent workforces capable of operating at mission speed. AWS's announced $50 billion investment in AI and supercomputing capacity - specifically for AWS Top Secret, AWS Secret, and GovCloud regions - represents a generational commitment enabling agencies to train and fine-tune models on mission-relevant classified data, run real-time analytics at scale, and execute supercomputing workloads elastically in secure environments. The conversation emphasizes that technology alone cannot drive transformation; success requires people, governance, and organizational infrastructure working in concert with cutting-edge capabilities.

Key takeaways

  • →Speed to capability is critical - agencies need access to cutting-edge AI and compute technology within months, not the traditional 18-24 month acquisition timelines.
  • →Data silos across intelligence disciplines (SIGINT, HUMINT, etc.) limit effectiveness; agencies need interoperable, governed, discoverable data foundations to unlock AI value.
  • →Workforce readiness is as important as technology - cloud-fluent, AI-ready teams are essential to operating new capabilities and achieving mission outcomes.
  • →AWS's $50 billion investment in Top Secret, Secret, and GovCloud AI/supercomputing infrastructure enables agencies to train models on classified, mission-relevant data rather than generic commercial datasets.
  • →Success metrics should focus on mission impact - faster intelligence cycles, smarter decisions, increased resilience, and reduced cognitive load for operators - rather than technology adoption for its own sake.

About CDO Magazine Podcast Series

Hosted by CDO Magazine. The show scores 57.7/100 on substance across its analysed episodes. See the full show profile.

Guests

Samantha FletcherAditya Karkera

Topics in this episode

AWS Top Secret RegionAWS Secret RegionAWS GovCloudAI and high-performance computingSIGINT dataHUMINT intelligenceCloud data foundationsMission-relevant machine learningNational security acquisition timelinesCounter-drone systems

Questions this episode answers

How is AWS helping national security agencies compress acquisition timelines?

By deploying cutting-edge AI, analytics, and compute technology through secure cloud environments (Top Secret, Secret, and GovCloud regions) that allow agencies to access capabilities in months rather than the traditional 18-24 month acquisition cycle.

What is the main barrier preventing agencies from using AI at scale today?

Agencies lack sufficient compute capacity and secure environments co-located with their classified data, preventing them from training large-scale models and running real-time analytics across mission-relevant datasets.

Why is data interoperability across intelligence disciplines important for national security?

SIGINT, HUMINT, and other intelligence data remain siloed and underutilized; breaking down those silos and making data discoverable and governed allows AI tools to connect diverse intelligence sources and identify threats more effectively.

What does AWS's $50 billion investment in GovCloud and classified regions enable?

It enables agencies to train and fine-tune their own AI models on classified, mission-relevant data; run real-time analytics at scale; and execute supercomputing workloads that previously required on-premises clusters, compressing intelligence cycles from weeks or days to hours.

Why is workforce development as critical as technology investment for national security agencies?

Technology alone cannot transform organizations - cloud-fluent, AI-ready teams are required to operate new capabilities effectively and deliver mission outcomes at the speed threats evolve.

What our scoring noted

Our reviewer’s read on each dimension, with quotes from the episode.

Insight Density

7 / 20

The episode spends roughly half its runtime on biographical storytelling and inspirational narrative, leaving limited space for operational insights. The substance that does appear - acquisition timeline compression, siloed intelligence data, workforce readiness - is real but stated at a surface level with no depth or mechanism explained.

our national security customers, they're operating in environments um, where our threats are evolving much faster than the traditional acquisition timelines really allow us to move at
a lot of it still remains really siloed and therefore it's underutilized

Originality

5 / 20

The episode recycles standard enterprise digital transformation talking points - data as strategic asset, workforce readiness, technology alone doesn't transform organizations - applied to a government context. There is no contrarian argument, no first-principles reasoning, and no framework a senior B2B operator wouldn't have already encountered.

technology alone can't transform national security and it can't transform organizations. The people do that
leadership isn't about authority, it's about service

Guest Caliber

13 / 20

Samantha Fletcher holds a genuinely senior role at AWS in a highly specialized domain, and her background - combat deployments, counter-drone systems, billion-dollar defense programs - is authentic practitioner experience at scale. The score is limited because the conversation extracts almost none of that depth.

working across the Middle east and Africa building counter drone systems, you know, leading large business units
I was responsible for intelligence work, um, where the stakes were truly life or death

Specificity & Evidence

8 / 20

A handful of concrete figures appear - the $50 billion investment, 1.3 gigawatts of capacity, 18-to-24-month acquisition timelines - but there are no named agency case studies, no before/after metrics on mission outcomes, and no specific program or contract details. Vague outcome language dominates the back half.

AWS announced plans to invest almost 50 billion to add nearly 1.3 gigawatts of AI and supercomputing capacity
it can't wait 18 to 24 months on that acquisition timeline

Conversational Craft

4 / 20

The host asks broad, pre-scripted questions ('what does success look like,' 'what does it mean in practice'), agrees with every answer, and never follows up or challenges a claim. The episode functions as a PR segment rather than an interview, closing with effusive compliments rather than any substantive probe.

Well, Sam, this has been such a great conversation. Thank you so much for your time and for your candor today. I know the audience is going to be super excited
Yeah, Sam, I couldn't agree more

Conversation analysis

Computed from the transcript - who did the talking, and the words that came up most.

Share of words spoken

  • Speaker A71%
  • Speaker B29%

Most-used words

data14today11mission9agencies8technology8moments7success7national6thank6environments6focused6career5security5defense4programs4super4

Episode notes

How can national security agencies accelerate AI adoption while working with classified data and evolving mission requirements? Samantha Fletcher, Head of National Security Programs at AWS, discusses secure cloud infrastructure, interoperable intelligence data, and workforce readiness with Dr. Adita Karkera, Chief Data Officer for Government and Public Services at Deloitte.

Full transcript

13 min

Transcribed and scored by The B2B Podcast Index.

Speaker A: Foreign. Hello and

Speaker B: welcome to the CDO Magazine interview series. I'm, um, Aditya Karkera, Chief Data Officer for Deloitte's Government and Public Services. And today I have the privilege of sitting down with someone whose career spans the front lines of national defense and the forefront of cloud innovation. Samantha Fletcher, Head of National Security Programs at Amazon Web Services. Sam, welcome.

Speaker A: Thank you for having me.

Speaker B: Sam, where are you joining us from today?

Speaker A: I am joining you from Herndon, uh, Virginia today, so in the U.S. uh,

Speaker B: on the east coast. Yay. So, um, thank you again for making time. Sam, I'm super excited for our conversation today. I want to start off with a little bit about your career. When you and I were having our prep call, uh, I was genuinely impressed by your career trajectory. And I mean, you were enlisted in the army at what, like 17, 18, something like that. You were deployed into combat environments, you run billion dollar defense programs, and now you lead national security cloud adoption at aws. I mean, gosh, where do we even begin? I guess. I'd love to

Speaker A: hear,

Speaker B: yeah, I'd love to hear from you. What were some of those, um, career defining moments for you in that journey and how that shaped you to who you are today?

Speaker A: Yeah, it's a great question. Uh, it's been quite a journey. Ah, looking back, I think there's a lot of defining moments, like there is for all of us. I think there's some that were the big monumental moments that really shaped me are kind of my trajectory within my career. Um, the first, like a lot of people from my generation, um, was probably 9, 11. I was just a teenager in Southern California at the time of the attacks. Um, and I remember a lot about that day, as most people do, but I remember calling my mom at her hospital, um, which was on lockdown, and hearing the fear in her voice. Um, and as a young American, even as disconnected as I was in Southern California, I was really trying to wrap my head around what had happened and why. And that day really kind of rearranged my vision for the future and the traditional path, you know, that I was expected to take for, for college, get a job, start a family, have stability. Um, and instead it all went up in smoke. Um, and I joined the army, um, really driven by probably a somewhat naive, um, but also really fierce belief that, that I could make a difference in the world. Um, so that was definitely one of those, those big moments. Um, another was probably my first deployment. Um, I got to my first duty station, which was in Wiesband, Germany, just after completing basic Training and ait and we almost immediately deployed to Iraq. Um, I was very young. I was very far from home, um, and all of a sudden I was responsible for intelligence work, um, where the stakes were truly life or death. And, um, I learned so much, um, in that time. But, you know, in combat, rank and titles, they tend to really dis. Solve, um, and what endures is that competence and that trust. And that was a foundational lesson for me. I learned that success was never individual, um, it was a collective, it was a team. Um, and it's really done by teams that are bonded together by the mission, by shared sacrifice, accountability, and shared success. And I learned that the stronger the team, the greater the impact and the outcome could be. Um, and it was also in this time frame where I found my own talent and passion, um, for hunting bad guys, um, and that really would shape, um, and consume the better part of the next decade of my life. Um, other big moments. Life happens to everybody. I definitely had some moments where life happened to me. So I think another big moment or lesson or pivot point, um, was really probably a combination of severe injury during my time in the army, um, and also a breast cancer diagnosis a couple years ago. And both these moments really kind of changed my perspective or recalibrated my perspective on fragility and gratitude. And I learned in a really hard way, um, and then subsequently reminded, um, of my own great strengths and specifically resilience. So I think, like most people, every chapter, um, you know, makes. It makes its impact. And I think for me, you know, deployment certainly in Iraq and Afghanistan, um, working across the Middle east and Africa building counter drone systems, you know, leading large business units. All the things that you mentioned, they all really reinforce the same core lessons for me, um, especially about leadership. Right. And leadership isn't about authority, it's about service. It's about listening and empowering others, uh, leading by example and standing firm when everything is uncertain. And I think those, those principles, you know, were gained in those hard times, but those principles still carry me every day. Um, whether I'm in a boardroom or in a meeting with mission partners, they're still kind of my guiding light.

Speaker B: Wow. Um, Sam, thank you for sharing that with the audience. I mean, what really strikes me with your background is, you know, whether it was your journey when you were at 19 or whether you kind of standing up these, uh, defense programs at multiple agencies. I mean, the common thread definitely is that all of this is focused on mission for you. And, uh, your story of resilience is really inspiring. Um, semis as we move on. Um, today as head of national security programs for uh, AWS today you are working across agencies, uh, at almost every classification level. Uh, what problems are you most focused on solving right now? Um, I guess, you know, what does success look like today in your current role?

Speaker A: Yeah, there's a lot of things that we're focused on right now. Um, it is interesting times, it is trying times. Um, sometimes of the things we're most focused on right now is speed to capability. Um, our national security customers, they're operating in environments um, where our threats are evolving much faster than the traditional acquisition timelines really allow us to move at. And so the need for cutting edge technology, AI analytics, compute, um, it can't wait 18 to 24 months on that acquisition timeline. And so it's my job and it's my team's job to help compress that timeline and enable um, tech to reach the mission end users much, much faster. Uh, we're spending a lot of time focused on data as a strategic asset. Um, right. The agencies have enormous volumes of data. We've got SIGINT data, Emmett humint, all kinds of data. Uh, but a lot of it still remains really siloed and therefore it's underutilized. And so we spent a lot of time focused on helping them build the data foundations, um, that make AI and other tooling um, actually work, um, but also make all of that data so much more powerful and useful, make it discoverable, have it governed, um, and most importantly having interoperable data that can be used across all the domains is huge um, for us right now. And um, I think especially with government, we spend a lot of time right now talking about focusing energy on the workforce readiness. Um, technology alone can't transform national security and it can't transform organizations. The people do that. So we're investing really heavily in helping our customers build cloud fluent AI ready teams, um, who can operate the capabilities that we're bringing to bear but also do it at mission speed, um, to success. I um, know that looks different in every era. Uh, but um, I think success for me is kind of simple right now. Um, did we make mission faster? Did we make it smarter? Did we make it more resilient? And did we help drive impact and mission outcomes? Did we lighten the load, you know, for, for an operator? Did we lighten a cognitive load? Did we help an analyst, um, connect diverse intelligence sources to identify a threat? Um, those to me are real measures and they're tangible success outcomes. Um, and they all lead to the end goal, right? Not just doing technology for technology's sake, but technology that delivers impact and outcomes.

Speaker B: Yeah, Sam, I couldn't agree more. I mean, technology is moving at such a fast pace, but it all comes down to the foundation. So I really appreciate your comments on the foundations around data as well as kind of bringing your workforce along because, uh, it's almost always seems, at least in my 26 years serving the public sector directly and indirectly, like, you know, technology is not the problem. It just seems that most of the bottlenecks are around the organizational and the governance infrastructure. And of course the workforce piece is super important because I feel like you can throw in all the technology, all the processes, and if you're not bringing your people along to your point, that's what we've already call it, a success. Uh, Sam, Late last year, AWS announced plans to invest almost 50 billion to add nearly 1.3 gigawatts of AI and supercomputing capacity. And I believe it was specifically around AWS top secret, AWS secret and govcloud regions. You know, that's quite an incredible commitment, you know. What does it mean in practice for the agencies and missions you support?

Speaker A: Yeah, uh, I mean it's not a small investment, it's huge. Um, it's the largest investment to date. But we've been making massive investments in this space for well over a decade. And this is truly, I mean this is a generational investment. Right. Um, and I think we should be really clear about what it unlocks, um, because the scale really can't be overstated. Um, it's going to, for the first time, allow agencies, um, you know, intelligence and defense agencies to have access not just to AI and high performance computing, but to purpose built AI, um, and high performance computing infrastructure. It's designed specifically for their environments. Right. And for their mission needs. Um, so a lot of our agencies today, they're constrained, um, they can't run large scale models or AI workloads. Um, they need the compute that just isn't there to do the larger training. Um, and of course for them their data is in specific environments. So we have to bring those environments to where the data lives. And that means at every classification level. So this investment, um, as well as the investments we've been making for over a decade, they really change that equation. So it means that the agencies can train and fine tune their own models on their data. Not generic commercial data, but mission relevant data. So it means you can run real time analytics at scale across multiple domains. Um, it means super computing workloads that previously required dedicated on prem clusters can now be run elastically in secure environments. So practically, it really translates to faster intelligence cycles, more sophisticated AI enabled decision support, and, um, the ability to do in hours what used to take days or weeks.

Speaker B: Well, Sam, this has been such a great conversation. Thank you so much for your time and for your candor today. I know the audience is going to be super excited to listen to all of the great insights you share today.

Speaker A: Yeah. Thank you so much for having me.

Speaker B: Absolutely. And for our audiences, please continue to watch out for more interviews coming out from our government leaders in this series. Thank you.

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