What Is the U.S. Tech Force? How the Federal Government Is Building an AI Workforce

In this episode of the Macro AI Podcast, Gary and Scott break down the newly announced U.S. Tech Force and explain why it represents a major shift in how the federal government approaches artificial intelligence, technology talent, and workforce strategy. 

Announced in mid-December 2025 by the U.S. Office of Personnel Management with White House backing, the U.S. Tech Force is designed to recruit highly skilled technologists for time-bound service inside federal agencies. The goal isn’t just IT modernization — it’s building real, internal capability to deploy, govern, and scale AI responsibly across government. 

Gary and Scott walk through how the initiative came together, why it’s structured around skills rather than degrees, and why the initial target of roughly 1,000 technologists is intentional. They explore how even small numbers of deeply technical talent can unlock stalled AI projects, modernize legacy systems, and reduce long-term reliance on external vendors. 

The conversation also connects the dots for business leaders. As government modernizes and embeds AI expertise internally, expectations around procurement, compliance, interoperability, and data standards will rise. The episode examines how this initiative could influence the future AI talent pipeline, shape public-sector AI standards, and eventually evolve into a permanent federal technology or AI corps. 

If you’re a business leader, technologist, or policymaker trying to understand what the U.S. Tech Force is, why it matters, and what it signals about the future of AI talent and national competitiveness, this episode provides the context you need. 

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website: 

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:  

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Transcript

00:00
Welcome to the Macro AI Podcast,  where your expert guides Gary Sloper and Scott Bryan navigate the ever-evolving world of artificial intelligence.  Step into the future with us  as we uncover how AI is revolutionizing the global business landscape  from nimble startups to Fortune 500 giants.  Whether you're a seasoned executive,  an ambitious entrepreneur,

00:27
or simply eager to harness AI's potential,  we've got you covered.  Expect actionable insights,  conversations with industry trailblazers  and service providers,  and proven strategies to keep you ahead in a world being shaped rapidly by innovation.  Gary and Scott are here to decode the complexities of AI  and to bring forward ideas that can transform cutting-edge technology  into

01:00
Welcome back to the Macro AI podcast, where break down what's really happening at the intersection of artificial intelligence, technology, and business,  and why it matters for leaders trying to navigate an increasingly complex and fast moving environment. Yeah. And today's episode is  one that sits right at the crossroads of workforce strategy, government modernization, artificial intelligence, and national competitiveness. And we're going to talk about a new government initiative called the US Tech Force.

01:30
it hasn't crossed your radar yet, it probably will in the next few days. Yeah. This isn't just another federal hiring program. It's not a rebranding of IT modernization. It's a signal that the U S government is acknowledging something very directly. Modern AI driven systems require modern technical talent and the old ways of acquiring that talent just will no longer work.

01:56
Yeah. And what makes this especially relevant to our audience is that the same pressures driving this  inside the government, know, AI acceleration, skills gaps,  legacy systems, execution risk.  They're exactly what we're seeing in the private sector right now as well. Yeah. And before we even define what the tech force is, it's worth asking a more fundamental question. Why now? The federal government has known about its technical debt and aging legacy systems for decades.

02:26
Yeah.  And I think everyone can feel it. uh AI has changed the urgency. So before AI, modernization was mostly about  efficiency and costs and might not necessarily be the pressures to  act. But with AI, it's about capability, resilience,  and relevance. Yeah. And I think once AI becomes a foundational layer, not a side experiment, organizations that can't deploy it responsibly fall behind very quickly. So the right talent

02:56
especially in the beginning is very important. Plus it just  helps you propel as an organization, possibly over your competitors. Yeah. And obviously in government supporting the people falling behind doesn't just mean lower productivity. means higher security risk at the federal level,  weaker security, weaker service delivery, slower response  in times that moments that really matter. Yeah. And there's also a workforce reality that's

03:24
possible to ignore. A large portion of the federal IT workforce is nearing retirement. So while younger technologists often don't see government as a place where they can work, especially for their first job, and even more importantly on modern systems or meaningful AI problems. So this does create an opportunity for the feds. Yeah. Yeah. So federal  and private leadership,  they're facing a convergence of pressures all at once. They've got the outdated systems.

03:53
insufficient internal expertise, uh ever-growing dependence on contractors,  and now AI demanding a deeper understanding inside the organization itself, know, workflows, everything.  And now obviously with extreme urgency to beat the competition. So either in the enterprise space or at the federal level with the increasing global pressures. Yeah. And at this point, it's worth grounding this in time because the U.S. tech force isn't some

04:22
long running pilot that's been quietly underway for years. Right. Yeah. think the U S tech force was formally announced just the other day in December, 2025, both publicly. And it was also announced pretty deliberately. It came from the, uh, U S office of personnel management with clear backing from the white house. So that's significant because the OPM controls how the federal workforce actually works, you know, job classifications.

04:52
hiring authorities and pay structures. Yeah. So this wasn't symbolic. It wasn't  a single agency trying something experimental. was really a planned structural move. Yeah, exactly. Yeah. And I think the timing matters by  December of this year, AI had moved from  experimentation to really an expectation and agencies  were under pressure, uh waiting another budget cycle.

05:22
uh, was no longer an option. So I think that's a big part of why we, why this came out right now. Yeah. Yeah. Good point. Um, let's talk about how this actually came together because I think the origin story explains why it's structured the way it is. Yeah. For years, there've been internal conversations around, uh, well across all agencies about the mismatch between how government hires and how modern technology works.

05:52
actually gets done.  Yeah.  I mean, I think everyone is aware of that traditional federal hiring is slow, rigid, uh, and credential heavy. And that might work for some roles. I'm not discounting that, but it's completely breaks down for AI, uh, and even data science and cloud engineering and cybersecurity. Um,  and this is a profession where top talent wants to move fast, make changes and

06:20
build a portfolio that demonstrates innovation and success,  which kind of conflicts with  the historical nature of traditional federal hiring. Yeah, 100%.  And at the same time, uh agencies became increasingly dependent on  outside vendors to build and operate mission critical systems. And  you've heard many stories about them becoming very costly. And  the problem with that model is, you

06:48
Institutional knowledge never compounds. And of course,  you know, on top of that are all the layers of costs. And when AI entered the picture, you know, if you recall that that became an existential problem. AI systems don't just need to be built, need to be understood, need to be governed, monitored and adapted over time. And the realization led to a key insight, meaningful public service doesn't require lifetime employment. You can build capability.

07:17
through time-bound service. Right, agreed with that. And structurally, uh OPM oversees the hiring framework, like we noted, but individual agencies define the missions  and participants are then  embedded inside of agencies. They're not just  floating consultants,  they're embedded inside each agency.  And hiring focuses on demonstrable skills rather than degrees or titles uh for the purview.

07:46
So if you can build systems,  work with data, deploy models or secure infrastructure,  that's what really matters, which is  kind of like what we've been hearing from  Alex Karp, the CEO of Palantir,  just come work. Yeah. And to that point, mean, compensation is competitive enough to attract real talent. ah And the roles  in the US tech force are explicitly time bound. Typically, I think it's like one to two years. So it's not that lifetime role that

08:16
we were just talking about. Yeah.  I think that time bound nature is  critical. It creates urgency, accountability, and then knowledge transfer, which is exactly what modern AI systems require. Yeah. And I think if you're listening right now, a lot of you are probably asking the same question.  How big is this thing really? Yeah. Yeah. I think that's an important one because when people hear tech force, sometimes think  or imagine a massive new

08:46
Exactly.  I think the reality  here is the initial design target is about 1000 technologists.  And that number is intentional. This isn't about  scale for optics. It's about leverage. uh Think about this, a thousand deeply technical practitioners  embedded across agencies is really a huge injection of capability, especially when internal AI and data.

09:15
data benches are thin. Yeah, it certainly is.  And in many agencies, even uh five  or 10 strong technologists can unlock projects that have been stalled for years just because  they know how to act and move quickly and solve problems. Yeah, and this mirrors what we see in enterprises. AI progress is rarely bottlenecked by budget. uh It's bottlenecked by talent.

09:41
uh density and focus.  And that's what we see at the enterprise level. Yeah. Yeah. And the plan for U.S. tech forces is cohort based. So people roll in, they serve their term, they roll out. And that means the pipeline becomes the real asset and the learned skills can then,  you know, disseminate out into the public sector. Right. And everything about the structure suggests that 1000 is  phase one modular number. It's not a ceiling.

10:11
Yeah. So if I think if early cohorts or see some success, it's pretty realistic to see, you know, expansion through additional cohorts, specialized tracks or annualized intake, you know, particularly an AI cyber security, cybersecurity cloud, and then the data governance piece. Right. And long-term size matters less than continuity. Even a rotating population of 1500 to 3000 technologists over time.

10:39
would fundamentally change the government's internal capability. Yeah. No, I completely agree with that. ah So let's uh pivot a little bit and talk about what these teams will actually be doing day to day. Right. So a lot of foundational work. So think of cleaning and organizing data, modernizing legacy systems,  automating manual workflows, and  building secure cloud environments. Yeah.

11:08
Yeah, because in most organizations, both on the public side and the private side, the biggest AI blocker really isn't the model, it's readiness. And you and I see that every day with the clients that we work with. Yeah, it's everywhere and all sizes of organizations. And that's why AI is really the through line here and the catalyst  for success. Yeah, I think an important insight  is that

11:37
With the U S tech force announcement, the government is recognizing that you can't governor deploy or even use AI responsibly. If no one inside the organization understands how it works and you have a roadmap from that point forward. That's actually a really good point because the understanding goes beyond coding. It includes data lineage,  bias, model drift, explainability, uh security and  life cycle management.

12:07
The tech force embeds that understanding  really internally rather than outsourcing it. Yeah. And I think that's critical because,  you know, as we know, AI systems aren't static. They just continuously evolve from the day that they're turned up.  And in government, those systems  affect, you know, real people at scale, which raises the bar for responsibility. Yeah. Good point.

12:34
Yeah. Good point. So let's bring this back to business because that's where a lot of the listeners are probably asking, why should I even care? Yeah. Good question. think, you know, when, government modernizes  businesses  feel it and in procurement compliance, interoperability data exchange, you know, it's, it's something that just that, you know, businesses will interface with. Yes.  As public systems become more AI enabled expectations on vendors.

13:04
and partners rise  across the ecosystem. Yeah, definitely. And then for businesses, there's also the, you know, the talent ripple effect. Like we talked about, you know, people who come out of the tech force will have rare experience. They'll have, you know, advanced technical skills, exposure to, you know, massive regulated environments,  and they'll learn how to be nimble to be effective and get projects done. That's a good point, because that combination will be incredibly valuable.

13:33
consulting firms,  enterprises,  startups, and even possibly back into other government  organizations. Yeah. Yeah. It'll be interesting to see what happens here. I think over the next 12 to 24 months,  execution by the U.S. tech force  will be the story. And so we'll keep this topic on the watch list for our podcast, see if we can find some insights and some stories. Yeah, it will definitely be interesting to watch. There will be friction.

14:04
Guaranteed there'll be onboarding challenges, some legacy complexity and certainly security constraints. Yep. Yeah. I'm sure they'll find, you know, as they start getting going, some incremental wins, you know, a single automated process, you know, cleaner data sets in every agency, pilot AI systems that can actually scale. It'll be good to see the results that are measurable and even ones that are, you know, obvious, you know, rolling out to the taxpayers.

14:32
Yeah. mean, looking out five to 10 years, this could evolve into something much bigger. Yeah. Yeah. I think it'll probably be roll into a permanent federal AI or technology core, you know, something closer to a, you know, a digital foreign service with rotating assignments to get exposure, uh deep expertise, institutional memory. It could even be a place that's a goal for top young talent to earn a, you know, earn a badge per se for their credentials.

15:02
And I'm sure that some of those talent will have input uh into the landscape of AI standards, which is really  still pretty nascent at the moment. Yeah, that's a point.  From a business perspective, US tech force will definitely drive clear standards along with better designed public sector AI systems and  more predictable regulatory environments.  totally agree. uh

15:31
I think that's probably a good place to wrap it up. think  my final comments would be,  when you hear a US tech force, think less about the head count and more about the intent and we'll see where it evolves over time. Yeah, it's about building internal AI capability really deliberately and also responsibly over time. And for business leaders, it's a reminder that the AI talent conversation isn't slowing down. It's accelerating everywhere.

16:01
Thank you again for listening to the Macquarie Podcast. We'll see you soon. Please share and like and subscribe our uh friendly little show and uh have a good  set of holidays. Have a good one.