Led by the 805th Combat Training Squadron at Nellis Air Force Base, Nevada, the biannual capstone allows the service to test new tech and assess their applicability for battle management and tactical command and control. After a successful iteration at the end of last year, the unit is poised to continue experimentation and rapid development of new capabilities and concepts to support the Defense Department’s Combined Joint All Domain Command and Control (CJADC2) effort throughout the next year.

Although effective execution of CJADC2 involves countless technical and bureaucratic challenges, the 805th — also known as the Shadow Operations Center – Nellis (ShOC-N) — used its most recent capstone event in December 2024 to understand how AI-enabled technologies could assist battle managers in conducting dynamic targeting.

“Modern battlefields are exceedingly complex and require the ability to distill an immense amount of information into a cohesive, actionable amount,” ShOC-N commander Lt. Col. Shawn Finney told DefenseScoop. “The emergence of artificial intelligence in warfighting applications potentially gives battle managers the ability to focus on the most salient aspects of the operational area by reducing the volume of information they must evaluate.”

At the recent Capstone 24B event, the unit experimented with advanced prototypes across three lines of effort: human-machine teaming; international partner and allied integration; and cloud-based C2 decision advantage.

The capstone simulated multiple “combat-representative” scenarios, including offensive counter-air, defense counter-air, electronic warfare and special operations, Finney said.

Notably, officials tested artificial intelligence platforms such as the Maven Smart System and Maverick AI application. The tech allowed battle managers to conduct “tactical control, execution, and assigning” of both friendly and adversarial assets within a common operating picture, according to an Air Force news release. The AI was also able to ingest planning data to give battle managers insights into complex and evolving scenarios.

During the event, the Maven system was for the first time successfully integrated into the Air Force’s new battle management kit, known as the Tactical Operations Centers-Light (TOC-L), at a live exercise.

TOC-L is a mobile, scalable C2 kit embedded with different software and applications that creates a single air picture from hundreds of fused data feeds. The service began prototyping it in 2022 and has since delivered 16 kits to different units around the world — including to ShOC-N — so they could be used in experimentation efforts.

The program is “constructed in a way that we can quickly deliver these prototypes, get them in the hands of our operators, and inform future TOC-L requirements — and really inform, more broadly, the control and reporting center weapons system,” Lt. Col. Carl Rossini III, deputy chief of the deployable systems branch at the Air Force’s Advanced Battle Management System Division, said in an interview.

Battle management teams used the TOC-L system and AI capabilities during Capstone 24B to simulate a dynamic targeting cell, able to rapidly identify and defeat assets that weren’t planned for during operational planning. Rossini said they gleaned insights from the event that ranged from very technical procedures to broader concepts.

“One was how well that [dynamic targeting] cell could operate with some other systems we were evaluating for operational command and control, and [intelligence, surveillance and reconnaissance] for how we manage dynamic targets and authorize those targets for prosecution,” he said. “We also had good learning on the construct of that [dynamic targeting] cell in particular, like the roles on that battle management team.”

The Air Force is developing an integrated “system-of-systems” called the DAF Battle Network to support the Pentagon’s goals for CJADC2. Broadly, the concept looks to connect disparate sensors and weapons operated by both the U.S. military and foreign partners under a single network to enable rapid data transfer across all warfighting systems and domains.

Steve Ciulla, TOC-L program manager, told DefenseScoop the Air Force is investing in the AI-enabled tools featured at ShOC-N’s recent capstone as a way to accelerate decision-making.

“Those are the specific things they were looking at, in terms of testing some of those cutting-edge software capabilities and speeding up the process of identifying striking targets — the dynamic targeting — and looking at how AI could help do some of those things, [and] also some human-machine learning as well,” Ciulla said.

While both Maven and Maverick AI successfully demonstrated automated capabilities during the capstones, Finney noted that the 805th will continue to experiment with them to mature the technology further.

“The human-machine team concept continues to evolve as we uncover new and better ways to unlock the potential of both the hardware and software while also understanding where software still has gaps that humans must perform,” he said.

Moving forward, the 805th plans to execute an experimentation campaign series throughout 2025 comprising four experiments — three of which will contribute to the Air Force’s Bamboo Eagle exercise and the Army’s Project Convergence — culminating in a final capstone event. Finney described the series as taking a “building block approach” in how the team uses lessons from previous events as baselines for subsequent experiments.

“This approach exposes large training audiences of warfighters to experiment results in a rapid and iterative fashion. We firmly believe in the experimentation-to-exercise process,” he said. “Through this, potentially immature capabilities can gain significant reps and sets within a single calendar year.”

As for the TOC-L team, Ciulla said they are focused on exercising the systems in the Indo-Pacific region over the next year. The goal is to conduct as much joint and international integration as they can across multiple exercises — including Project Convergence 25, Bamboo Eagle, Return of Forces to the Pacific (REFORPAC) and others.

The exercises will help inform the Air Force’s next iteration for TOC-L acquisition, expected to kick off by summer. The service intends to improve on current kits and scale the number of systems globally, Ciulla said. 

“It’s not going to just end with this phase one experimentation effort,” he added. “We’re still going to be getting this feedback loop [and] user data coming in to support our development, design for the next iteration of the system to tell us what the biggest risks are, what’s working [and] what’s not working.”

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The Golden Dome for America initiative — previously referred to by Trump as the Iron Dome for America — calls for a multi-layered shield for the U.S. homeland. The Space Force is expected to play a central role in setting up the architecture — which emphasizes the need for space-based sensors and interceptors — and the service has already established a cross-functional “technical integrated planning team” and is reaching out to industry.

However, while Golden Dome is expected to include next-generation technologies, there could also be a role for some of the Air Force’s “traditional” capabilities such as fighter jets, suggested Maj. Gen. Joseph Kunkel, the service’s director for force design, integration and wargaming.

Homeland defense is already a key element of the service’s force design vision, he noted during a Hudson Institute event Wednesday.

“This thought of a Golden Dome that protects the homeland, that is completely in line with the force design, and how we do that is completely in line. But I would suggest that the threat and the number of threats and how the threats are being presented, presents new challenges, but it also offers opportunities for … some of the capabilities, the traditional capabilities that we would call mission area three,” Kunkel said.

“When you think about how the Air Force and … the nation has defended itself, we defend ourselves as far away from our borders as possible. And when we build this Golden Dome, we can’t think of this Golden Dome as this thing that stops at the borders. And where we’ll use this air layer is in the countering of, you know, adversary bombers that are approaching our borders and shooting missiles from those borders. So you know that combined arms approach that we took in our force design, it’s equally applicable to this Golden Dome concept where there’s going to be a combined arms requirement for that to counter the different threats that we’re going to see,” he added.

Trump’s executive order directing Defense Secretary Pete Hegseth to develop a plan to field additional missile defense tools noted that it must address the development and deployment of capabilities to defeat missile attacks before launch.

While sensors and weapons will play important roles in the multilayered missile defense architecture, battle management will also be key, Kunkel noted.

“The sense is a big part of it. The effectors are … a big part of it. But this battle management of the whole thing is also a big part of it. I know that Air Force is right in the middle of that with DAF Battle Network,” he said.

The DAF Battle Network fits in with the Pentagon’s next-generation warfighting concept dubbed Combined Joint All-Domain Command and Control, or CJADC2, which aims to better integrate the sensors, shooters and data streams of the U.S. military services and key allies and partners into a more unified network.

Kunkel sees AI as an enabler of these types of concepts.

“One of the major areas where I think artificial intelligence will help us is in decision-making, you know, that’s in battle management and those types of things, and understanding risk calculus and that. I think it’ll help us in autonomy,” he said. “There are opportunities there where AI can be introduced in some capabilities to achieve even longer endurance, you know, flights or longer-range weapons. And those are some of the areas we’re looking at. But I do think the area that is like ripe for exploitation for artificial intelligence is decision-making and how we do battle management.”

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The amendment to the BAA, published Feb. 29, revises a key technical area and adds three subsections to the document that was originally issued in August 2023 regarding “artificial intelligence and next generation distributed command and control.”

The changes provide more information about the operational context for the Air Force’s pursuit of new techniques to tailor and replace faulty algorithms on deployed systems, as well as its plans for addressing related challenges. They also come as the service is working to develop and field new AI and machine learning tools for a variety of tasks, including target identification and operating autonomous drones known as collaborative combat aircraft.

Officials recognize that some artificial intelligence capabilities developed in a lab might not be up to snuff when they’re sent into a warzone.

“Because models are trained a priori on data (and simulations) in an anticipatory fashion, AI-based systems encounter situations in the real world that are incompatible with training feature distributions and parameterization of employed algorithms. The result is degradation to model performance that can negatively impact mission effectiveness and safety. Therefore, the Air Force requires new battle management processes to monitor the performance of AI-based systems and update incumbent models in response to changing battlespace conditions,” the amended BAA states in the section for Technical Area 1, which deals with command and control of artificial intelligence systems to achieve mission-tailored AI.

“In the trivial case, operators will simply repurpose a pretrained model that fortuitously fulfills unanticipated mission requirements. In the extreme case, operators will coordinate a distributed workflow, known as an AI COA, to retrain, test, and deploy new models in line with mission execution, so that dependent systems can continue to function as intended with minimal loss of service,” it added.

As an example of a use case where this type of “battle management” of AI could be applied, the document described a hypothetical intelligence, surveillance and reconnaissance mission being carried out by an unmanned aerial vehicle operating in bad weather.

“A new kind of battle manager within the forward tent, deemed the AI Interface Officer, monitors the performance of computer vision models hosted on UAVs and looks for cases of ‘AI drift’ — unexpected behavior caused when the domain of the learned function is no longer compatible with input data. In this case, an object detection model is no longer performant with live sensor data due to significant changes from a weather event. The AI Safety officer must evaluate the risk to mission success posed by continued employment of the model. If the risk is deemed too high, the AI Safety Officer will coordinate with remote operators via cloud-based services to determine the root cause of the drift and propose new AI adaptation strategies (e.g., replace model, fine tune, transfer learn, etc.) and deployment options (e.g., ‘use uplink to replace model on UAV at 1500 hours’) that accommodate the environment while also adhering to imposed mission timelines,” the BAA explains.

In another use case, the software on combat drones could be tweaked if too many of the platforms are getting shot down, not attacking enemy targets effectively, or coming up short in other ways.

“For example, operators could update control policies onboard autonomous collaborative platforms … with improved skills to evade adversary forces or provide cover fire. Some alert mechanism, perhaps triggered by unacceptable platform attrition rates or poor mission performance, should help operators decide when and how to update the autonomy,” the document states.

To get after the challenges related to implementing its vision, the Air Force added three technical subareas to the BAA related to decision-making aids, manufacturing and deployment processes, and situational awareness.

For the first subarea, the Air Force wants capabilities that can use a government-provided inventory of available datasets, algorithms, models and host platforms to perform tradeoff analyses, rank different adaptation and deployment options according to various factors, and provide an interface for battle managers to review options and make their selections.

“When an automatic target capability … exhibits aberrant behavior, an operator must choose the best adaptation and deployment options to resolve the drift. Because each step has a local cost, the technology should help operators understand the overall compounded cost as it pertains to fulfillment of mission requirements and resource availability … For example, the system could communicate tradeoffs in terms of model accuracy versus deployment readiness, assuming better models take longer to train and evaluate,” the BAA states.

The Air Force is looking for “novel presentation approaches” to facilitate this type of selection process.

For the second subarea, which is related to the manufacturing, test and deployment of AI models, the service notes that it needs operators to be able to coordinate workflow execution at next-gen battle management stations.

“Once a newly manufactured AI model is approved and ready for deployment, the system should post model updates onto the host platforms, perhaps while in motion assuming sufficient comms. Platforms should expose software interfaces that enable operators to dynamically read, update, and delete models,” per the BAA, which notes that offerors will be expected to develop adaptors and processes around open platform interfaces furnished by the Defense Department.

For the third subarea, focused on situational awareness, the Air Force wants capability trackers that provide location data and other critical information about the status of mobile weapons platforms and the AI models they’re loaded with.

It also needs monitoring tools that enable “plug-and-play integration of drift detection algorithms and live performance feedback” from operators, so that battle managers can be alerted to underperforming AI and consider courses of action to address the problem.

“Because drift detection research is still in its infancy, [this announcement] solicits frameworks to integrate existing (possibly rudimentary) drift detection methods as opposed to development of new state-of-the-art algorithms,” the BAA states.

It notes that the Air Force isn’t soliciting proposals for new platforms, communications hardware, communications networks, or AI development frameworks. Rather, it seeks “innovation for how to connect existing AI development frameworks within battle management control stations and workflows to configure the behavior of AI” as outlined in the document.

The Defense Department plans to conduct live experiments of companies’ solutions at various military exercise to assess completion of technical milestones.

The BAA — which includes five other technical areas — runs through fiscal 2028. However, the Air Force is encouraging contractors to submit white papers by March 15 if they want to align with projected funding opportunities for fiscal 2025.

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In the past, a service member specializing in air battle management had expertise that was tied to specific airframes — such as the aging E-3 Sentry airborne early warning and control aircraft and the E-8 Joint Surveillance Target Attack Radar System (J-STARS). Some of these platforms will be phased out of the fleet in favor of more modern systems that will enable Joint All-Domain Command and Control (JADC2), a Pentagon-wide effort to better connect all the services’ sensors and shooters under a more unified network.

Brown, who has been tapped by President Biden to be the next chairman of the Joint Chiefs of Staff, emphasized that even with changes in platforms and concepts, the Air Force will still need experienced battle managers to work through missions.

“The thing we got to think through is how we restructure our organizational construct of putting that expertise in the right place,” he said Wednesday during a webinar hosted by the Mitchell Institute. “And whether it’s in the air control squadrons that do more of this versus them being tied to an airborne platform — those are the things we’re looking at to be able to make sure we’re putting that experience in the right place.”

In particular, Brown noted that the Air Force will have access to more space-based intelligence, surveillance and reconnaissance data in the future as a portion of the E-8 J-STARS fleet is set to be replaced with a space-based Ground Moving Target Indicator (GMTI).

In the Space Force’s budget request for fiscal 2024, it is requesting $242.6 million to kick off the brand new program, known as Long Range Kill Chains. The initiative is intended to expand the GMTI capability to track surface targets in contested environments where current J-STARS platforms are unable to fly.

“Space-based GMTI system will provide actionable information on adversary surface targets to the warfighter through the Advanced Battle Management System (ABMS) as an integral part of Joint All-Domain Command and Control (JADC2) concept. The [Space Force] is working with the Air Force and the Intelligence Community (IC) in a complementary way to design, develop, and deploy space-based GMTI systems,” budget documents stated.

Adding more space-based surveillance tools will also likely create more observational data for officials to work with than previous platforms did, creating new aspects for the air battle management mission, Brown said.

“We’ve got to look at not only how we do the battle management asset, but also how we do the processing, exploitation and dissemination [of data] that’s associated with it as well. And that’s a paradigm shift. This is an area that we’ve got to be willing to change,” he said.

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The SDA, which is now part of the Space Force, recently released a draft solicitation for the Battle Management Command, Control, and Communications (BMC3) Application Factory.

“The acquisition establishes software development capabilities to securely and rapidly field mission applications developed by BMC3 ecosystem participants in support of Joint All Domain Command and Control (JADC2) objectives,” the draft solicitation states. It is expected to yield a “DevSecOps continuous integration/continuous development pipeline that provides governance and infrastructure to enable BMC3 software applications to develop, integrate, test, and deploy into the” national defense space architecture.

“Basically, it’s the software that will be used by performers on the ground to build the apps and test out the apps in a secure environment to … basically do uploads onto the satellites so that we can upgrade the BMC3 processors on orbit,” SDA Director Derek Tournear explained during a recent virtual event hosted by the National Security Space Association.

The technology is intended to enable edge processing for SDA’s new layers of data transport satellites.

The agency wants industry’s help with development and implementation of the BMC3 app factory; development and sustainment of the Secure Interoperable-middleware layer (SIL); integration, testing, and operational support for BMC3 applications; and leading the BMC3 “ecosystem.”

The SIL is intended to enable the apps to integrate and run on BMC3 hardware.

Responses to the draft solicitation are due by Dec. 9. A final solicitation for the application factory is expected to go out in February after the SDA incorporates industry’s feedback, and an award is expected “shortly thereafter,” according to Tournear. The agency plans to use an Other Transaction Authority agreement for the acquisition.

Solicitations for the initial apps that will be put through their paces in the new factory are expected to be released in summer 2023.

“We’re going to kind of have an annual process where we select those and move forward. But that’s more of a rolling process because … it’s not that we pick one, we pick one vendor and go with them [and exclude other vendors]. We’ll pick vendors based on whatever apps they have and have this kind of rolling process. So that’s a little different,” Tournear said.

As the SDA builds out the new national defense space architecture with additional tranches of satellites, network data routing is expected to become much more automated.

“We’ll have that network operations essentially with a man-on-the-loop versus a man-in-the loop doing that … pushing more and more of that automation from the ops center floor up into the spacecraft itself,” Tournear said. “That’s when the app factory and the apps come into play.”

The apps will help fuse data from a variety of satellites made by different vendors.

“They’ll also do fusion of any other [intelligence, surveillance and reconnaissance] data into tracks to be able to send those down to targeting centers to be able to do weapons-data pairing so we can send those to weapons. So apps will do that, then the apps will also do all of this network data management,” he said. “That will be automated and eventually that will be done on board the transport satellites themselves. So all of that network management that changes the network routing tables will be done autonomously onboard those satellites via an app.”

The SDA wants the app factory in place “next year” so people can start developing the apps, he noted.

The draft solicitation calls for a minimum viable product for the application factory and the SIL in fiscal 2024.

“The apps need to be really developed and running in the ‘25, late ‘25 timeframe, so we can start to upload those and actually do operations on board” the spacecraft, Tournear said.

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