As a combined intelligence and combat support agency, NGA is tasked with collecting geospatial intelligence (GEOINT) from satellites and other sources and turning it into actionable data for military operators and decision makers. Although the organization is already well-versed in AI capabilities — as it runs the Pentagon’s high-profile Maven computer vision program — NGA Director Vice Adm. Frank Whitworth is pushing personnel to leverage the technology even more this year.

“As I was looking at the last several years, we use descriptors for the ‘A’ in NGA with a little bit of alliteration, and we would say ‘action’ or ‘acceleration,’” Whitworth told DefenseScoop in an exclusive interview on the sidelines of Space Symposium. “I wanted to put a finer point on it and say, the ‘A’ for this year is going to be AI.”

Research from NGA and industry on multimodal artificial intelligence has been one of the key factors driving his push for acceleration, he noted.

Similar to generative AI, multimodal models can simultaneously process information from multiple source types — including text, images and audio. But while generative AI is geared toward creating new content, multimodal AI expands on those capabilities and allows users to understand different types of data in a single, integrated output. 

For NGA, that could mean creating more holistic intelligence packages from sources beyond just imagery, which will be critical as available data is expected to exponentially increase in the coming years due to new sensors being fielded across domains.

“Distinction is really difficult — to distinguish enemy from non-enemy, combatant from non-combatant,” Whitworth said. “While GEOINT, imagery-derived intelligence typically is one of our primary forms of identifying and driving distinction, we always are looking for other forms of corroboration.”

NGA has already employed three test cases for multimodal AI, although Whitworth said the capabilities are still too early-on in their development to talk about them more specifically. However, he emphasized that the agency continues to explore other ways to collect and verify data beyond computer vision. 

“It’s a big Earth, and so while we have really good indications typically of where to look, there’s no guarantee,” he said. “Our business is to steal secrets, and when people are trying to keep things secret from us that could cause us harm or change the American way of life, we’re going to have to rely on all kinds of sources to ensure we’re looking at the right place.”

NGA also intends to leverage lessons from ongoing AI-focused targeting programs like Maven and apply them to its other roles, such as warning — which Whitworth described as a “behemoth” responsibility.

“Warning involves establishing a baseline of equipment, behaviors, activities around the world and being able to prioritize where you’re looking, and then ensuring you can find anomalies and announce them,” he said. “That’s going to take a lot of work. … Warning requires improvements in workflow, improvements in automation and yes, it will involve AI and ML.”

The warning mission is currently under the purview of the agency’s Analytic Services Production Environment for the National System for GEOINT program, also known as ASPEN, Whitworth said. 

Kickstarted in 2023 to address massive increases in data, ASPEN is a suite of analytic capabilities that leverages automation and AI to help NGA analysts provide more accurate warning indications to customers.

In order to streamline adoption of AI across all of its roles and responsibilities, Whitworth noted that NGA has recently established a new program executive office for advanced analytics helmed by Rachael Martin, who previously served as the program lead for NGA Maven. The PEO intends to bring together the agency’s best practices of artificial intelligence and machine learning.

The new office is NGA’s latest organizational change made to help its AI adoption in 2025. The agency also recently named Mark Munsell as its first director of AI standards, while Trey Treadwell and Joseph O’Callaghan are serving as director of AI programs and director of AI mission, respectively.

“We didn’t actually have people who came to work and said, ‘I am the director of AI.’ And it was time to do that,” Whitworth said. “As the organization begins to mature, you at least have somebody who’s thinking about, what do I need in my organization? Do I need to change names? Do I need to change the organizational structure to ensure AI/ML is treated with the seriousness it deserves?”

At the same time, NGA is keeping an eye out for AI-enabled capabilities being developed by the commercial industry that could be incorporated into its workflows, while leveraging innovative procurement methods geared towards commercial solutions, Whitworth said.

For example, the agency used the Defense Innovation Unit’s commercial solutions opening (CSO) process to award pilot funding for Project Aegir, a program that focuses on commercial techniques to identify, monitor and track illicit maritime vessel activity in the U.S. Indo-Pacific Command area of responsibility. NGA is also exploring using bailment agreements, which allows the Defense Department to temporarily loan government-owned systems to smaller companies in order to test, research and develop new capabilities during a trial period.

“It is really focused on, how do we get industry into the door quickly? That’s why we did things like the CSO, that’s why we’re trying bailment agreements,” Whitworth said. “We’re leaning forward on trying to bring them in, because industry moves at the speed of light.”

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Initiated as a pilot effort in 2023, TacSRT established a marketplace where CoComs can directly purchase commercial imagery and related data analytics. In order to expand the program, the Space Force received an additional $40 million in funding as part of the continuing resolution passed by Congress in March. 

“The addition of this money represents a congressional vote of confidence in our efforts to tap into the commercial space market for the collective good,” Chief of Space Operations Gen. Chance Saltzman said Wednesday during his keynote address at the annual Space Symposium.

Saltzman and other service leaders have touted the success of TacSRT in recent months, especially the initiative’s ability to rapidly deliver critical information to warfighters. Through the program’s Global Data Marketplace, combatant commands can put in requests for “operational planning products” that include unclassified data from imagery and sensors collected by commercial space vendors. 

Col. Rob Davis, program executive officer for space sensing at Space Systems Command, told reporters Wednesday that TacSRT data is primarily being used to support humanitarian operations and monitoring of illegal fishing around the world. 

And while the pilot version of TacSRT initially supported U.S. Africa Command, leaders at other combatant commands are leveraging the program’s marketplace as well. For example, U.S. Central Command also purchased commercial data analytics during construction of the Joint-Logistics-Over-the-Shore pier in Gaza, and TacSRT provided U.S. Southern Command with real-time tracking of wildfires in South America, according to the Space Force.

As it looks to scale TacSRT, the service is still figuring out the best ways to operationalize the program, Davis said.

In the TacSRT Tools Applications and Processing Lab, “we are doing the development of additional techniques, partnering with industry, partnering with [Space Force] component field commands … to develop new tools that we can then operationalize, as well,” Davis said during a media roundtable. “We continue, in that more developmental space, to do ad hoc support through that experimental space to answer questions that combatant commands have.”

With plans to expand TacSRT, the Space Force is also working with the intelligence community — including the National Geospatial-Intelligence Agency and the National Reconnaissance Office — to delineate roles and responsibilities for purchasing commercial imagery. 

Under current Pentagon-IC policies, NGA is responsible for buying analytical models and ISR products from commercial providers, as well as determining who across the government receives the packaged data. At the same time, the NRO is tasked with acquiring imagery from commercial remote sensing satellites and disseminating it across the Pentagon and intelligence community. 

However, the Space Force’s TacSRT pilot caused some tension between the service and intelligence agencies — with some concerned that the Space Force’s acquisition and distribution of space-based commercial imagery is a duplication of NGA’s and NRO’s work. 

But after years of back and forth, NGA Director Vice Adm. Frank Whitworth told DefenseScoop in an interview that the agency and the Space Force have drafted a “memorandum of agreement” over the relationship between NGA and TacSRT. The service is also finalizing a similar agreement with the NRO, according to a report from Breaking Defense.

Whitworth explained that in his role as functional manager for geospatial intelligence, he is charged with oversight of both the Defense Department’s and intelligence community’s acquisition of space-based ISR from commercial satellites. To that end, his responsibility moving forward will be reporting on the use of commercial imagery in warfighting — including via TacSRT — to lawmakers while also involving the Space Force, he said.

“This fits beautifully into being that integrator, and Congress feels the same way from a stewardship perspective,” Whitworth said. “So getting to that issue [of] we’re not paying twice, keeping that denominator involving TacSRT officially in our world and vice-versa is healthy.”

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In an interview with DefenseScoop this week, the National Geospatial-Intelligence Agency’s new and first-ever Chief AI Officer Mark Munsell shared initial details about one ongoing pursuit to train a cutting-edge model and shed light on his approach to steering NGA’s early adoption of the still-uncertain technology.

“We could not have predicted some of these inventions with transformers, like [generative pre-trained transformer or GPT] and stuff, and because of that and the trajectory of those, I think certainly we’re going to be living in a better world. But for the first time, we’ll have to really guard against misuse,” Munsell said.

As the CAIO suggested, genAI, geoAI and associated frontier models are part of a rapidly evolving field of technologies that are not fully understood, but are pushing the boundaries of what existing AI and machine learning can accomplish. Typically, such tech can process massive volumes of data and perform increasingly “intelligent” tasks like recognizing speech or generating human-like media and code when prompted.

These capabilities hold a lot of promise to dramatically enhance how the agency’s analysts detect and make sense of objects and activities they are tracking across sprawling data sources, inside NGA’s world that revolves around capturing and deciphering geospatial intelligence about movements and happenings all around the globe.

Munsell is expressly determined in his early months as the new AI chief to set the agency on a clear path for responsibly exploring and adopting powerful frontier models in their day-to-day operations.

However, one immediate challenge he said his team is confronting has to do with the fact that the major companies developing these next-generation models to date have not prioritized geographic use cases that would impact NGA’s work.

“So, we have a big role to play, I think, there on behalf of the country — and really, potentially on behalf of the world — which is to ask these companies to focus on certain capabilities that don’t exist yet, or that the models do not do well yet,” Munsell explained. 

He provided several examples to demonstrate this issue, particularly when it comes to existing computer vision technologies.

“How well the models can identify things on a photo —  that is super important, and we want companies to do that better,” he noted.

Beyond that realm, Munsell said, modern large language models are learning to generate GEOINT assets, like graphs and graphics. But, in his view, these systems are not yet highly skilled at understanding geography and critical features, like longitude and latitude coordinates. 

“Simple things, like depiction of boundaries or understanding certain geographic locations. Today, it’s all based on maybe words in a gazetteer, or words in an encyclopedia, or words in an atlas. A lot of the training has been like that. So there’s a lot to do to turn these large models into things that are geographically aware. NGA will have a big part to play in that,” Munsell said. 

During the interview, the CAIO also offered DefenseScoop the first preview of an initial generative AI experiment that agency insiders are pursuing. 

“One of the examples we’ll have soon, early next year, is we’re doing a retrieval augmented generation — so people just use the term the RAG — implementation of a large language model that’s being trained … on every NGA report ever written,” he said.

Each day, agency officials compile detailed documents on intelligence activities around the world, such as adversary undertakings at specific locations.

“Essentially, [we’ll] be able to ask it any question on any report that’s ever been written, and it [could] have the depth of knowledge and understanding of analysts that worked on accounts for 30 years,” Munsell explained. 

The longtime technologist joined the Defense Mapping Agency (which evolved into NGA) for the first time roughly 30 years ago, as a software engineer in 1995.

Notably, he’s part of a very small percentage of senior executives in the government who have around a million lines of software code under their belts.

“For example, I wrote the system that NGA used up until last year to produce all its aeronautical information that goes into all of the DOD aircraft. That was my first assignment here at NGA,” he noted. 

After that, Munsell spent some time in the private sector. He returned to NGA in the early 2000s and has been rising through the tech ranks there ever since. In recent years, he helped launch the Data and Digital Innovation Directorate — a hub he’s continuing to lead in his now dual-hatted role as CAIO.

“It made logical sense for the agency and for the director to appoint the director of that component as the chief AI officer,” he said.

Munsell has been taking it all in as AI and machine learning have intensely evolved over the course of his career. 

Looking back on his first stint at NGA, he said he didn’t totally anticipate the emergence of generative AI. And while he believes it will improve the human experience, he also repeatedly pointed to the need to adopt these yet-to-be-fully-understood technologies responsibly.

“It’s really kind of a one-two punch. On one hand, you’re going to promote these great inventions that will do wonderful things for for the world. And on the other hand, you do really have to watch and protect people from misusing these. So, that’s … how I look at my responsibilities. It’s two gloves,” Munsell said. 

“On one hand, I’m promoting the use — the proper use — because we know it’s good and better. And on the other hand, we’re checking and we’re ensuring that people are doing right by this technology,” the CAIO told DefenseScoop. 

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During an interview with DefenseScoop on Tuesday, Munsell reflected on his motivation for taking on this nascent role, and discussed those and other key priorities on his near-term agenda as NGA’s newly named CAIO.

“I think you’ll see a lot more energy around implementing generative AI in the analytic workflow,” he said.

Historically considered America’s super-secret mapping agency, NGA is the Defense Department’s functional manager for geospatial intelligence, or GEOINT. That discipline involves the capture of imagery and data from satellites, radar, drones and other means — paired with expert analyses to visually display and monitor physical objects and geographically referenced activities on Earth.

As Munsell suggested, the maturing realm of generative AI (which broadly incorporates disruptive models that can pull patterns within existing data to generate original content across many forms) presents heaps of opportunities and risks for NGA analysts.

The emerging technology and associated, advanced frontier models were already top of mind for Munsell as NGA’s director of data and digital innovation. In addition to serving as CAIO, he’ll continue to lead that directorate — and in doing so, he’s set on “putting AI into the hands” of the agency’s users.

“And what I mean by that is a lot of these … big models being developed by the big companies like Anthropic and Google and OpenAI are still not accessible by the folks at NGA. They are still not usable by the folks in NGA. So I would consider myself successful when our analysts and the officers at NGA have access to those — the world’s best models — on a top secret network,” Munsell told DefenseScoop. 

One primary task that’s already in-play for his team related to this intent, involves revamping NGA’s guidance for how its personnel adopt artificial intelligence to include additions that better confront generative capabilities.

“A new AI strategy will be published by NGA probably after the [2024] calendar year” ends, Munsell said.

Among other responsibilities as CAIO, he’s also working closely with the agency’s first-ever Responsible AI Officer Anna Rubinstein on pursuits to establish more technology governance assets and facilitate initiatives geared at strengthening the trustworthiness and reliability of GEOINT models.

“We know that the work that we do with AI is serious work — positively identifying targets, accurately geo-locating them — it’s serious work that could be used in warfare. And we knew how important it was for us to establish that program of responsible AI implementation and to have a senior officer in charge of it,” Munsell said. 

As CAIO, he now oversees “a couple-hundred-person organization” with offices, divisions and branches. Some of that staff will also be supporting Munsell in an ongoing but complex effort to produce a full inventory of all NGA initiatives and programs on artificial intelligence. 

“We’ve been doing the inventory for a couple of years now, but it’s one of the harder things to do,” he said. 

“There are designated programs that are building and making and implementing AI, but there are hundreds of programs that could sort of suddenly be using AI. And so at some point you do want to know every program and every initiative that’s using AI, so you can have some level of audit on it, some level of security on it, and some level of safety evaluation on it. But sometimes the AI is embedded in software that you’re buying commercially off-the-shelf, and then you’re bringing [it] into the agency and you might not even know it,” Munsell explained.

For that and other reasons, NGA’s inventory will be, as he put it, “less literal,” as well as “a little more logical” and “a little bit more about investments in programs that are deliberately either building or buying or implementing AI.”

In response to questions from DefenseScoop regarding why NGA tapped him as its first CAIO at this particular point in time, Munsell noted that the move is now obligatory for federal organizations under multiple recent directions from the White House and Congress. 

But in his view, the spy agency has also been ahead of the game, especially over the last four years. He called out defense “visionaries” who impacted NGA’s path to realizing AI and enabling the Pentagon’s high-stakes Maven computer vision effort — including former and current NGA and DOD officials such as Phillip Chudoba, Sandra Auchter and Drew Cukor.

“For me, it’s an honor to be the first [CAIO]. But in a way, I’m standing on the shoulders of giants — and I think you should say that, because it’s so true,” Munsell told DefenseScoop.

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The NGA director unveiled this initiative — called the Accreditation of GEOINT AI Models, or AGAIM — during a roundtable in Washington hosted by the Defense Writers Group.

“The accreditation pilot will expand the responsible use of GEOINT AI models — and posture NGA and the GEOINT enterprise to better support the warfighter and create new intelligence insights. Accreditation will provide a standardized evaluation framework. It implements risk management, promotes a responsible AI culture, enhances AI trustworthiness, accelerates AI adoption and interoperability, and recognizes high-quality AI while identifying areas for improvement,” Whitworth said.

Historically considered the United States’ secretive mapping agency, NGA is the Defense Department’s functional manager for geospatial intelligence, or GEOINT. Broadly, that discipline involves the capture of imagery and data from satellites, radar, drones and other means — as well as expert analysis to visually depict and monitor physical features and geographically referenced activities on Earth.

One of NGA’s primary contemporary missions encompasses managing the entire AI development pipeline for the U.S. military’s prolific, evolving computer vision program Maven.

With increasingly “intelligent” capabilities, the agency’s capacity to detect threats globally is getting sharper. 

“[We’re] distinguishing objects, let’s say, for our aviators who fly our planes in and out of airfields. [We’re] distinguishing objects that could actually bring them harm, that are new, that encroach upon the airspace as they come into an airfield — or that might be new as it relates to a newly discovered seamount on the seabed, or that might be new relative to bathymetrics and hydrography for people who are in ships,” Whitworth explained. 

“These are things that keep people alive,” he said.

And as the technology rapidly matures, officials at the agency are using machine learning techniques to train models to detect anomalies for humans, as the director put it, “while we might be asleep or while we’re not looking at a particular image.”

New and more sophisticated models are also starting to emerge at an unprecedented pace. 

“In GEOINT — getting back to that issue of distinction — it is so important that we make sure these are good models, because the issue of positive identification underlies, effectively, whether you’re going to be correct and whether we might have some sort of an apology on behalf of our nation or an alliance” if the U.S. government gets something wrong, Whitworth said.

The agency envisions this pilot to eventually become a pathfinder within DOD that ultimately ensures that all players have the same standards to guide their GEOINT model development.

“You’ve got to start somewhere,” the director said.

Traditional computer vision and generative AI capabilities will be addressed in the new pilot.

“There are a whole lot of different types of models, and everyone likes to talk about [large language models, or LLMs]. This is more of the LVMs — I’m going to make that term up a bit for a large visual model, or a visual transformer — I think is actually a better way of talking about this,” Whitworth told DefenseScoop.

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“I think the blessing and curse of AI is that it’s going to think differently than us. It could make us better — but it can also confuse us, and it can also mislead us. So we really need to have ways of translating between the two, or having a lot of understanding about where it’s going to succeed and where it’s going to fail so we know where to look for problems to emerge,” NGA’s first-ever Chief of Responsible Artificial Intelligence Anna Rubinstein recently told DefenseScoop.

In her inaugural year in that nascent position, Rubinstein led the making of a new strategy and instructive platform to help guide and govern employees’ existing and future AI pursuits. That latter educational tool is called GEOINT Responsible AI Training, or GREAT.

“So you can be a ‘GREAT’ developer or a ‘GREAT’ user,” Rubinstein said.

During a joint interview, she and the NGA’s director of data and digital innovation, Mark Munsell, briefed DefenseScoop on their team’s vision and evolving approach to ensuring that the agency deploys AI in a safe, ethical and trustworthy manner.

Irresponsible AI

Geospatial intelligence, or GEOINT, encompasses the discipline via which imagery and data is captured from satellites, radar, drones and other assets — and then analyzed by experts to visually depict and assess physical features and specific geographically referenced activities on Earth.

Historically, NGA has a reputation as the United States’ secretive mapping agency.

One of its main missions now (which is closely guarded and not widely publicized) involves managing the entire AI development pipeline for Maven, the military’s prolific computer vision program.

“Prior to this role, I was the director of test and evaluation for Maven. So I got to have a lot of really cool experiences working with different types of AI technologies and applications, and figuring out how to test it at the level of the data models, systems and the human-machine teams. It was just really fun and exciting to take it to the warfighter and see how they are going to use this. We can’t just drop technology in somebody’s lap — you have to make sure the training and the tradecraft is there to support it,” Rubinstein noted.

While she was a contractor in that role, that Maven expertise is now deeply informing her approach to the new, permanent position within the federal agency that she was tapped for.

“I’m trying to leverage all that great experience that I had on Maven to figure out how we can build enterprise capabilities and processes to support NGA — in terms of training people to make sure they understand how to develop and use AI responsibly — to make sure at the program level we can identify best practices and start to distill those into guidelines that programs can use to make sure they can be interoperable and visible to each other, to make sure that we’re informing policy around how to use AI especially in high-risk use cases, and to make sure we’re bringing NGA’s expert judgment on the GEOINT front into that conversation,” Rubinstein explained. 

Inside the agency, she currently reports to Mark Munsell, an award-winning software engineer and longtime leader at NGA. 

“It’s always been NGA’s responsibility to teach, train and qualify people to do precise geo-coordinate mensuration. So this is a GEOINT tradecraft to derive a precision coordinate with imagery. That has to be practiced in a certain way so that if you do employ a precision-guided munition, you’re doing it correctly,” he told DefenseScoop.

According to Munsell, a variety of timely factors motivated the agency to hire Rubinstein and set up a new team within his directorate that focuses solely on AI assurance and workforce development.

“The White House said we should do it. The Department of Defense said we should do it. So all of the country’s leadership thinks that we should do it. I will say, too, that the recognition of both the power of what we’re seeing in tools today and trying to project the power of those tools in five or 10 years from now, says that we need to be paying attention to this now,” Munsell told DefenseScoop. 

Notably, the establishment of NGA’s AI assurance team also comes as the burgeoning field of geoAI — which encompasses methods combining AI and geospatial data and analysis technologies to advance understanding and solutions for complex, spatial problems — rapidly evolves and holds potential for drastic disruption.

“We have really good coders in the United States. They’re developing really great, powerful tools. And at any given time, those tools can be turned against us,” Munsell said. 

DefenseScoop asked both him and Rubinstein to help the audience fully visualize what “irresponsible” AI would look like from NGA’s purview. 

Munsell pointed to the techno-thriller film from 1983, WarGames.

In the movie, a young hacker accesses a U.S. military supercomputer named WOPR — or War Operation Plan Response — and inadvertently triggers a false alarm that threatens to ignite a nuclear war.

“It’s sort of the earliest mention of artificial intelligence in popular culture, even before Terminator and all that kind of stuff. And of course, WOPR decides it’s time to destroy the world and to launch all the missiles from the United States to Russia. And so it starts this countdown, and they’re trying to stop the computer, and the four-star NORAD general walks out and says, ‘Can’t you just unplug the damn thing?’ And the guy like holds a wire and says, ‘Don’t you think we’ve tried that!’” Munsell said. 

In response, Rubinstein also noted that people will often ask her who is serving as NGA’s chief of irresponsible AI, which she called “a snarky way of asking a fair question” about how to achieve and measure responsible AI adoption.

“You’re never going to know everything [with AI], but it’s about making sure you have processes in place to deal with [risk] when it happens, that you have processes for documenting issues, communicating about them and learning from them. And so, I feel like irresponsibility would be not having any of that and just chucking AI over the fence and then when something bad happens, being like ‘Oops, guess we should have [been ready for] that,’” she said.

Munsell added that in his view, “responsible AI is good AI, and it’s war-winning AI.”  

“The more that we provide quality feedback to these models, the better they’re going to be. And therefore, they will perform as designed instead of sloppy, or instead of with a bunch of mistakes and with a bunch of wrong information. And all of those things are irresponsible,” he said.

‘Just the beginning’

Almost immediately after Rubinstein joined NGA as responsible AI chief last summer, senior leadership asked her to oversee the production of a plan and training tool to direct the agency’s relevant technology pursuits.

“When one model can be used for 100 different use cases, and one use case could have 100 different models feeding into it, it’s very complicated. So, we laid out a strategy of what are all the different touchpoints to ensure that we’re building AI governance and assurance into every layer,” she said.

The strategy she and her team created is designed around four pillars. Three of those cover AI assurance at scale, program support, and policies around high-risk use cases.

“And the first is people — so that’s GREAT training,” Rubinstein told DefenseScoop.

The ultimate motivation behind the new training “is to really bring it home to AI practitioners about what AI ethics means and looks like in practice,” she added.

And the new resources her team is refining aim to help distill high-level principles down into actionable frameworks for approaching real-world problems across the AI lifecycle. 

“It’s easy to say you want AI to be transparent and unbiased, and governable and equitable. But what does that mean? And how do you do that? How do you know when you’ve actually gotten there?” Rubinstein said.

In order to adequately address different needs across the two groups, there’s two versions of the GREAT training: one for AI developers and another for AI users.

“The lessons take you somewhat linearly through the development process — like how you set requirements, how you think about data, models, systems and deployment. But then the scenario has a capstone that happens at the end, drops you into the middle of a scenario. There’s a problem, you’re on an AI red team, people have come to you to solve this issue. These are the concerns about this model. And they’re three rounds, and each round has a plot twist,” Rubinstein explained. 

“So it’s, we’re giving students a way to start to think about what that’s going to look like within their organizations and broadly, NGA — and even broader in the geospatial community,” she said. 

Multiple partners, including Penn State Applied Research Lab and In-Q-Tel Labs, have supported the making of the training so far.​​

“We got the GREAT developer course up and running in April, we got the GREAT user course up and running in May. And then beyond that, we will be thinking about how we scale this to everyone else and make sure that we can offer this beyond [our directorate] and beyond NGA,” Rubenstein said.

Her team is also beginning to discuss “what requirements need to look like around who should take it.”

Currently, everyone in NGA’s data and digital innovation directorate is required to complete GREAT. For all other staff, it’s optional.

“The closer they are to being hands-on-keyboard with the AI — either as a producer or consumer — the more we’ll prioritize getting them into classes faster,” Rubenstein noted.

Munsell chimed in: “But the training is just the beginning.”

Moving forward, he and other senior officials intend to see this fresh process formalized into an official certification.

“We want it to mean something when you say you’re a GREAT developer or a GREAT user. And then we want to be able to accredit organizations to maintain their own GEOINT AI training so that we can all be aligned on the standards of our approach to responsible GEOINT AI, but have that more distributed approach to how we offer this,” Rubinstein told DefenseScoop. “Then, beyond that, we want to look at how we can do verification and validation of tools that also support the GEOINT AI analysis mission.”

Updated on June 18, 2024, at 8:05 PM: This story has been updated to reflect a clarification from NGA about how it spells the acronym it uses for its GEOINT Responsible AI Training tool.

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Geospatial intelligence, or GEOINT, broadly refers to imagery and data that’s gleaned from satellites, radar, drones and other means — and then analyzed by experts to visually depict and evaluate physical features and specific geographically referenced activities on Earth. 

“To preserve and further advance our technological edge is one of the key pillars of the NATO 2030 agenda. And in this effort, geospatial artificial intelligence — or GeoAI — is a key area which will revolutionize the way that we look at GEOINT in the future,” NATO’s Assistant Secretary General for Intelligence and Security Scott Bray said during his keynote at the annual GEOINT Symposium on Tuesday.

GeoAI methods combine artificial intelligence with geospatial data and analysis technology to boost understanding and solve complex, spatial problems.

“Spatial machine learning algorithms and deep learning techniques have become extremely powerful, fueled by unprecedented computing power. Leveraging these technologies on large collections of imagery, or geospatial data, will allow us to greatly improve the intelligence production cycle through applications like automatic change detection, and in areas of interest or socio-economic analysis, maritime safety, analysis of space and cyber events, and many others,” Bray said. 

He pointed to NATO’s Defense Innovation Accelerator for the North Atlantic (DIANA) initiative as a key mechanism via which the allies involved can directly connect with commercial and academic partners around innovative capabilities and activities like GeoAI. 

Launched in 2022, DIANA is designed to expand multinational cooperation and foster an innovation network to more strategically deploy emerging and dual-use technologies. 

Building on momentum — and the expansion of NATO to include Sweden and Finland — since then, the alliance recently confirmed plans to host tech accelerator sites at DIANA locations in 28 nations.

Outside of that well-backed innovation initiative though, Bray said NATO members still have a lot to do to improve their ability to share data and work interoperably at speed and scale.

“With 32 allies, with lots of intelligence that comes in — ultimately, in a world in which we are faced with not just the Russia and Ukraine challenge, but with so many other issues — then ultimately, what we need is more capacity for rapid exploitation and sense-making of that intelligence,” he explained. “That is a place where, certainly, private industry is leading,” which means it’s a ripe area for NATO to pursue new and deepen existing partnerships, he added.

Bray — who has extensive intelligence community experience and previously served as the U.S. acting director of naval intelligence — emphasized that today’s security environment is different.

“We’re not [just] talking about great power competition right now in Europe — we’re talking about the fact that there is open conflict in Europe. And the degree of integration that it is going to take between all the allies, to include the United States, and with our private industry partners to ensure that our defense industrial capacity and our intelligence industrial capacity is well-integrated, is absolutely essential for peace and stability in our era,” Bray said.

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The search comes as the service is preparing to refresh technology for the Distributed Common Ground/Surface System-Marine Corps Geospatial Intelligence program.

The DCGS-MC GEOINT platform is a secure, multi-level, integrated, tactical data system that provides Marine analysts with the capability to task, collect, process, analyze, exploit, produce, store, disseminate and expose geospatial intelligence data and products, according to a request for information released Aug. 8 on Sam.gov.

The tech “provides georeferenced data and products that establish the GEOINT foundation for battlespace visualization and a common frame of reference to support the commander’s decision-making process. It enables the ability to rapidly respond to, or predict, threats around the world by providing near real time geospatially referenced data and products supporting the full spectrum of Marine Air-Ground Task Force (MAGTF), joint, and multinational partners operations,” per the RFI.

As it looks to upgrade the system’s capabilities, the Corps is pinging vendors to find out what solutions are available for “an artificial intelligence chatbot capability to receive, parse, and output information pertaining to Marine Corps geospatial processes, requirements, and workflows through natural language processing.”

The chatbots must be operable on all the service’s network domains, the RFI noted.

The due date for industry to submit white papers is Aug. 29. Vendor demonstrations are expected to be held in late fiscal 2023 or the first quarter of fiscal 2024, which begins Oct. 1.

After the demos, promising tech may undergo further evaluation “in a controlled lab environment and then put into the hands of Marines for testing in field conditions by establishing Bailment Agreement(s). Lab and field evaluation results will inform requirements development, integration/system development, and may ultimately lead to the fielding of systems in support of a more combat-effective fighting force,” per the RFI.

The Marine Corps isn’t the only Department of Defense component interested in generative artificial intelligence, which can create content such as text, audio, code, images, videos and other types of media, based on prompts and data inputs.

The Pentagon launched Task Force Lima on Thursday focused on understanding how the DOD can effectively and responsibly leverage generative AI tools such as large language models. The new organization will be led by the Chief Digital and AI Office’s (CDAO) Algorithmic Warfare Directorate.

The task force will identify ongoing efforts related to generative AI at the department; analyze potential mission areas, workflows and use cases for the technology; support the development of and oversee the integration of capabilities throughout the DOD; and perform other tasks.

Intelligence agencies such as the CIA are also looking into how these types of technologies could help them with their missions.

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A list of the entities that landed spots on the GEOINT Enterprise Operations Service and Solutions Program with Industry, Core Mission Operations (GEO-SPI B) contract was included in a federal contracting award notice posted online on Monday afternoon.

“The companies selected for the IDIQ will compete for individual task orders across the seven-year ordering period, collectively worth up to $900 million,” an NGA spokesperson told DefenseScoop in an email on Tuesday.

The spy agency has been pretty tight-lipped about the work GEO-SPI B will fundamentally enable. Contracting materials that would shed light on that are accessible only to individuals and businesses approved by the U.S. government to use the Intelligence Community Acquisition Research Center. 

“This suite of IDIQ contracts provide NGA’s core contracted intelligence and foundational analysis encompassing the tasking, collection, processing, exploitation, and dissemination (TCPED) functions that underpin GEOINT work,” according to the agency’s spokesperson.

The 13 approved contractors include:

• 3GIMBALS
• BAE Systems
• Booz Allen Hamilton
• Castalia Systems
• Continental Mapping Consultants
• Geo Owl
• Leidos
• ManTech
• Novetta 
• ProCleared
• Royce Geospatial Consultants
• Solis Applied Science
• Thomas & Herbert Consulting 

Once selections are made under this IDIQ, associated work will be performed at NGA sites and in partner facilities.

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These moves are necessary to fulfill new responsibilities recently delegated to NGA to scale maturing AI efforts, according to Director of its Research Directorate Cindy Daniell, who spotlighted ongoing initiatives and fresh opportunities at Capital Factory’s Fed Supernova conference in Austin, Texas. In her view, they’ll likely also prove essential to ensuring the U.S. maintains a technological advantage as technology and global competition evolve in the near term.  

“The future is unknowable — but our resources, our strengths, opportunities, weaknesses, as well as the trends that lie before us, are not. From these, we can make educated guesses on how to enable the future, and where possible, accelerate it,” Daniell said. 

Speaking to an audience of government officials, technologists, investors and entrepreneurs in Texas’ capital region, she also repeatedly emphasized “our national security challenges are too difficult for the government to solve alone.”

NGA provides geospatial intelligence (GEOINT) that is fundamental to the nation’s security. And that GEOINT “tells you what is happening, where, and what might happen when,” Daniell said. The term refers to the exploitation and analysis of imagery and geospatial information to describe, assess and visually depict physical features and geographically referenced activities on the Earth.

While GEOINT capabilities have been “a critical source of information for all eternity,” she said, that has especially been the case for the modern national security apparatus. 

“When we layer this with multiple types of imagery and combine it with other intelligence sources, it literally reveals the ground truth — informing critical national security decisions surrounding the Cuban Missile Crisis, the raid on Osama bin Laden’s compound, and support for humanitarian assistance and disaster relief,” Daniell explained. “Needless to say, it has also played a crucial role in the war in Ukraine.”

Given the shifting conflict and political landscapes of this era, the NGA leader and former electrical engineer said she could “not emphasize enough” how important it is for the public, private and academic sectors to work together to drive “novel practical solutions” at this moment.

From a research perspective, Daniell said NGA capability development is informed by three lines of effort. 

“The first is validation” or accurate, high-resolution and continually updated representations of Earth’s elements, through physical or activity models, and positioning navigation and timing (PNT), she noted. The second, “collection technologies,” encompasses efficient strategies and methods to deliver spatial-temporal data from an ever-increasing number of sources. The third area, analytic technologies, is all about “accurate, timely, reliable, and scalable methods for data exploitation and analysis,” which are constantly evolving, she noted. 

GEOINT elements of the Pentagon’s trailblazing early AI effort — Project Maven — are presently being transitioned to NGA’s purview, and the project is now a major priority for the agency.

“Maven will enable us to integrate and institutionalize automated, geospatial AI capabilities with NGA’s strategic priorities. This will ultimately enable NGA to provide our military service customers with the critical and timely insights they require,” Daniell said. “To this end, we’re looking for the full spectrum of capabilities — everything from discrete, bespoke software products to complete end-to-end solutions.” 

The agency is developing software and requirements for future systems that are specifically designed to ensure the information is accessible, and it has legacy and new datasets that must be fused. New sensors and information sources are being built and refined “at a rate we’ve never seen before,” Daniell also said, noting that NGA needs to incorporate more automation, advanced modeling and machine learning to push the envelope. 

“We need your help — every single one of you — to accelerate this development, integration, sustainment and refresh of automation and computer vision,” she told the audience in Texas. “And we are expanding our partnerships with all sorts of innovation in the commercial space. This means we’re providing new engagement venues and mechanisms to enable government teaming with smaller non-traditional companies who are no less innovative than their larger counterparts.”

Last year, NGA launched a broad agency announcement to speed up how it buys specific priority technologies to perform its required functions. 

“We will be releasing more topics, both broad and specific, with the BAA in the future. So, stay tuned,” Daniell said.

Beyond expanding collaboration with government research labs and military branches and other pursuits, the agency also recently launched a new Data, Digital and Innovation initiative (DDI) to help to lead the GEOINT community “through the agency’s adoption of AI,” the director also noted.

To build advanced models, NGA needs accurate test data that closely represents the format and structure of operational data. 

“So over the next year, we are working to create an open-data repository with a variety of sample datasets made just for you, for use by academia and industry requirements,” Daniell noted. Further, her team is looking at producing “a truly representative development sandbox architecture” to run, test and demonstrate models in an operationally relevant architecture.

That work will be tested and accelerated as a permanent feature at NGA’s brand new “moonshot laboratory facility” in St. Louis.

“Our goal is to enable you to quickly iterate on solutions while maintaining operational security and control,” Daniell said.

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