When Caudle takes the helm, he will be the first Senate-confirmed CNO since Trump fired Adm. Lisa Franchetti from that post in February without explanation. Adm. James Kilby, the Navy’s vice chief, has been serving as acting CNO since Franchetti was removed.

Caudle told members of the Senate Armed Services Committee during his confirmation hearing last week that he approves of Franchetti’s CNO Navigation Plan, or strategic vision, that was released last year. That plan included Project 33, an effort to accelerate the acquisition and fielding of unmanned systems, AI and “information dominance” capabilities to deter or defeat a Chinese attack on Taiwan or other U.S. interests in the Indo-Pacific.

Caudle told lawmakers that his top priorities for Navy transformation, if confirmed, would be to invest in platforms, sensors and weapons systems that are “modular, scalable and built for rapid upgrade cycles” to stay ahead of emerging threats; boost sailors and warfighters through advanced training, leadership development and talent management; and “accelerate delivery of integrated, networked capabilities across the joint force, including unmanned systems, artificial intelligence, and resilient C3 architectures to enable decision advantage and operational dominance in contested environments.”

Adopting cutting-edge tech such as AI, uncrewed platforms, cyber tools and data-driven decision-making could enable the Navy to “outpace adversaries by leveraging faster learning curves and feedback loops from the assessment of existing combat operations,” he wrote in response to senators’ advance policy questions ahead of this confirmation hearing.

Caudle suggested a more aggressive push to adopt robotic platforms might be needed if Navy shipbuilding programs face further budget constraints or cost growth problems.

“Robotic and Autonomous Systems (RAS), also referred to as Unmanned Systems, are a force multiplier already being employed across a wide range of missions. Prioritizing the integration of RAS at scale, as appropriate, into naval and joint force architecture would be a necessary step [to deal with further fiscal constraints]. Additionally, we could potentially expand and accelerate current RAS systems further across the fleet, in all cases focusing on affordability, training, and interoperability with manned platforms,” he wrote.

The nomination of Caudle — a four-star who has been serving as commander of Fleet Forces Command — for the CNO role wasn’t a controversial pick.

Caudle’s confirmation was approved by voice vote, along with a slew of other military nominations, as the Senate nears its August recess.

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The service issued a request for information Wednesday to help the program executive office for intelligence, electronic warfare and sensors and the program manager for Next Generation Command and Control (NGC2) get feedback from industry and identify potential solutions.

The Army wants to mitigate the cognitive burden for commanders and boost their situational awareness.

“As the Army continues to integrate advanced technologies and expand its use of unmanned aerial systems (UAS), rotary-wing, fixed-wing, and emerging platforms, traditional airspace management methods are being challenged by the growing scale, speed, and complexity of operations,” officials wrote in the RFI.

“Traditional airspace management systems often struggle to process and respond to the vast amounts of data generated during operations, limiting their ability to provide actionable insights in real time,” they added.

The proliferation of drones will make airspace management even more complicated. The Army and the other services are under pressure from Secretary of Defense Pete Hegseth to quickly integrate more small unmanned aerial systems across the force. Hegseth issued a directive earlier this month with the aim of accelerating that process.

Meanwhile, the Pentagon is also pursuing new counter-drone tools, air-and-missile defense systems, and command-and-control tech to address growing threats.

The expanding use of UAS, loitering munitions and autonomous platforms will have to be taken into account by the U.S. military’s airspace management frameworks, which must also be able to deal with the presence of large numbers of friendly, neutral and enemy players — as well as other weapon systems and adversaries’ electronic warfare capabilities, the RFI noted.

“Army airspace management must adapt to rapidly changing mission requirements, including the need for real-time deconfliction, airspace prioritization, and coordination with joint and coalition forces,” officials wrote. “Effective airspace management must account for the coordination of indirect fires, air defense systems, and other effects to ensure mission success while minimizing risk to friendly forces.”

The Army is hoping artificial intelligence tools can lend a helping hand.

“AI-enabled airspace management solutions have the potential to address these challenges by leveraging machine learning, predictive analytics, and automation to enhance situational awareness, optimize airspace allocation, and enable rapid decision-making. Such systems can analyze real-time data from multiple sources, predict airspace usage patterns, and recommend proactive measures to improve safety, efficiency, and mission effectiveness,” per the RFI.

Responses to the RFI are due Aug. 29.

The service is looking to put vendors’ technologies through their paces later this year at a Joint Pacific Multinational Readiness Center event.

“The Army is seeking interested industry partners to deliver a minimum viable product (MVP) for an AI-enabled airspace management solution that enhances UAS operations during JPMRC Exercise 26-01,” officials wrote. “The MVP must be operationally ready for deployment to the 25th Infantry Division by November 2025 and capable of addressing some of the unique challenges of UAS management in contested and congested environments.”

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Traditionally, that meant collecting and sending data back to command facilities in Hawaii or the continental U.S. for analysis and response. But in fast-changing operational environments, that approach is quickly becoming outmoded and unreliable.

This scenario highlights both the challenge commanders face and the strategic shift underway across the military. The decisive advantage no longer rests solely on the movement of troops and materiel—but on the ability to move and process information faster, more securely, and with greater operational relevance than adversaries.

Achieving that kind of information advantage means being able to deliver real-time insights to warfighters in the field—especially in environments where communications are disconnected, disrupted, intermittent, or limited (DDIL). This isn’t just a technical upgrade; it’s a strategic imperative.

Underlying this shift is the growing expectation that actionable intelligence will reach those on the front lines faster than it reaches our adversaries. That expectation is driven in no small part by the commercial experience most consumers have become accustomed to – e.g., the ability to track deliveries en route and notifications when they arrive.  

Conflict planning and logistics in contested DDIL environments are obviously more complicated, which is all the more reason why the advantage lies with those who have an information advantage. That requires assessing, processing, and disseminating vast amounts of data quickly at the edge.

Gaining the data edge

“In many regards, data is the five-five-six round of the next war,” said John Sahlin, vice president for defense cyber solutions at General Dynamics Information Technology (GDIT), referring to the standardized rifle cartridge used by NATO forces. “It has become the lynchpin to enhance the decision-making process for advantage.”

That advantage depends on more than just collecting data. It requires turning it into usable intelligence faster than adversaries can react.

“The core problem is latency,” explained Matt Ashton, partner customer engineer at Google Public Sector. “Until recently, the immense volume of data from sensors, drones, and logistical trackers required the processing power and AI available primarily in distant cloud computing centers.”

“Our DOD customers struggle with the current status quo at the edge because they can’t run true AI,” said Ashton. “So data has to get sent back to the mother ship to crunch the data and get a resolution. The massive differentiator now is our ability to provide AI at the edge.”

According to both industry experts, the solution lies in a combination of powerful, ruggedized edge computing platforms and AI models specifically engineered for defense use that can operate independently, even when completely disconnected from high-capacity networks.

Google, for example, provides this capability through its Google Distributed Cloud (GDC), a platform designed to bring data center capabilities to the field.

“GDC was built to run so it never has to ‘call home.’ It can sit on the Moon or a ship. It doesn’t have to get updates,” Ashton said. “It’s a family of solutions that includes a global network, but also features an air-gapped GDC box that connects to the Wide Area Network and other on-prem servers not on the internet.”

This allows commanders on submarines, at remote bases, or in forward-deployed positions to run AI and analytics locally and process vast sensor data streams in-theater without waiting on external links.

Why mission-specific AI models matter

However, raw computing power is only part of the equation. Commercial AI models often lack a nuanced understanding of military operations. This is where operationally relevant AI models developed by GDIT that translate raw data into relevant, actionable intelligence are crucial.

Sahlin compared the role of mission-specific AI models to a speedometer in a car. “What it measures is the revolutions per minute of the axle. What it reports is how fast you’re going in miles per hour,” he explained. “That’s the kind of insight that only comes from real-world familiarity with military operations.”

“A clear grasp of operational objectives is key to developing models that are tuned to real-world demands of each mission,” said Sahlin. “So that may mean multiple mini-models to translate data into relevant insights.”

Sahlin also explained why applications built on an open data architecture model are crucial to adaptability at the edge.

“The real value of an open data architecture, particularly in the defense industry, is that it’s a very decentralized platform. Logistics is a classic example of commercial, local, last-mile delivery providers working with many sources. In the military, you won’t have a single source or model. This is where open architecture is critical.”

Security remains foundational to all of this. Sahlin noted that while the military can benefit from commercial innovation, it still needs to ensure higher levels of security than commercial operators. So it’s also essential that the military’s AI development partners have a deep understanding of the Defense Department’s zero trust security practices and requirements, which apply to the broader base of defense suppliers in the DOD’s supply chain.

“GDIT’s value lies in its longstanding experience supporting defense missions,” Sahlin said. “We work with clients to gather the right data, build tailored models, and deliver intelligence to the edge, even in DDIL conditions where units may be disconnected or intentionally silent.”

Looking ahead

By combining a platform like GDC with mission-specific AI models from GDIT, military logistics teams can move from reactive support to proactive planning, anticipating needs, reallocating resources, and outmaneuvering adversaries.

As operational demands grow more complex and communications become more contested, defense leaders say gaining an information advantage at the edge isn’t just important, it’s essential for mission success.

Learn more about how GDIT and Google Distributed Cloud can help your organization deliver at the edge more proactively.

This article was sponsored by GDIT and Google Cloud.

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The move comes amid a broader modernization push by special ops forces and the Defense Department to add new digital tools and robotic platforms to their arsenal.

In a new subsection for “Advanced Autonomy and Artificial Intelligence,” the amended BAA for technology development noted that SOF is keen on “modular, open integration” of cutting‐edge solutions incorporating AI and machine learning to enable enhanced autonomy in unmanned systems.

“Specific areas of interest include but are not limited to agentic AI and vision language action (VLA) models to achieve more sophisticated autonomous behaviors like adaptive learning; neural radiance fields (NeRFs) for 3D scene representation and navigation; generative AI for simulation and data augmentation; advanced automatic target recognition (ATR) algorithms with edge node refinement and autonomous model retraining; advanced machine learning operations (MLOPs) to support data management, model training, validation, and monitoring,” officials wrote.

They noted that proposed solutions need to be designed with well‐defined interfaces and adherence to open standards to promote interoperability and integration into existing architectures.

Earlier this year, the command re-released its “SOF Renaissance” strategic vision, which observed that innovations in AI, autonomous systems and cyber tools are reshaping warfare and enhancing targeting and strike capabilities.

The document calls for commando forces to be early adopters of these types of technologies. SOCOM has been on the cutting-edge before as an early DOD user of the Maven Smart System, for example.

“The distinction between optimizing and generative AI is crucial and will be a game changer. Swarms of low-cost drones and remote explosive devices, using AI and autonomy, blur traditional human-machine boundaries on the battlefield. SOF must also use these systems to improve decisionmaking and situational awareness,” officials wrote in the strategy.

Vice Adm. Frank Bradley, the current commander of Joint Special Operations Command who’s been nominated by President Donald Trump to be head of SOCOM, said the use of innovative drone capabilities and tactics in places like Ukraine and the Middle East have ushered in a “revolution in military affairs.”

“The changing, accelerating pace of technology, the ubiquitous information environment, and the advent of man-machine teamed autonomy on the battlefields of the world today are absolutely changing the character of warfare … in our very eyes,” Bradley said last week during his confirmation hearing with the Senate Armed Services Committee.

He added that legislative proposals such as the FORGED Act and SPEED Act, and other initiatives to reform DOD acquisitions and speed up the fielding of new tech, are “critical to allowing us to use the innovative spirit of our operators to be able to capture those problems and opportunities we see on the battlefield and turn them into new man-machine teamed approaches.”

The amendment to the BAA comes just two weeks after the Pentagon’s Chief Digital and Artificial Intelligence Office announced the award of $200 million contracts to multiple vendors for “frontier AI” projects.

“The adoption of AI is transforming the Department’s ability to support our warfighters and maintain strategic advantage over our adversaries,” CDAO Doug Matty said in a statement accompanying that announcement. “Leveraging commercially available solutions into an integrated capabilities approach will accelerate the use of advanced AI as part of our Joint mission essential tasks in our warfighting domain as well as intelligence, business, and enterprise information systems.”

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The Thinking Agent for Logical Operations and Strategy (TALOS) tool is an AI-powered agent able to study and clone various spacecraft operations into a simulated environment of the space domain, according to a Slingshot news release. Members of the Space Force have already tested and used TALOS during training exercises, and the company is now looking at how the technology can assist the service even more.

“TALOS builds upon years of collaboration with the U.S. Space Force’s Operational Test and Training Infrastructure (OTTI) and Slingshot’s proven virtual environments,” Slingshot Aerospace CEO Tim Solms said in a statement. “It embeds AI agents that simulate realistic threats, optimize real-world operations, and support mission command decision-making with unprecedented speed and precision.”

The tool was built leveraging Slingshot’s behavior cloning pipeline, which allows AI agents to learn how to perform a task by directly imitating an example from the real world. According to the company, TALOS is geared towards replicating and simulating satellite tactics, including “representative behaviors, space warfare maneuvers and dogfighting strategies.”

“Once assigned a mission, TALOS evaluates its surroundings, reasons through potential strategies and tactics, and executes its objective within a simulated, physics-accurate orbital environment,” a company news release stated.

Although TALOS is relatively new, the Space Force’s 57th Space Aggressor Squadron — the service’s unit that provides simulations of adversary space systems that can be used during training — recently tested the tool during exercises. Guardians used TALOS to create realistic and adaptive simulations of enemy satellites and their behaviors, as well as during the planning phase of the service’s first Space Flag exercise.

As the Space Force undertakes a large effort to build out its training infrastructure under the Operational Test and Training Infrastructure (OTTI) program, service officials have highlighted capabilities like TALOS as important tools for modernization. OTTI is envisioned as a high-fidelity virtual environment that will rely heavily on AI-enabled capabilities that can automatically simulate threats to critical space systems.

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As vice president of AI-first transformation, Plumb will spearhead IBM’s Next-Generation Transformation Strategy and work across the company’s core business lines to foster adoption of AI, automation and hybrid cloud computing throughout the global organization and with its clients and partners.

Plumb started in the role July 14.

A key part of her job, Plumb told DefenseScoop, will be serving as IBM’s “Client Zero,” meaning she will internally operationalize AI technologies and concepts to test them before deploying to clients.

“The approach is really taking AI solutions and embedding them in the company’s own processes and then using that to prove out how AI solves problems, drives agility, creates efficiencies, which IBM then can use to help demonstrate that value for its customers, right? So, this is an internal transformation role, but with an eye towards building out concrete examples of execution for external consumption,” Plumb told DefenseScoop.

That’s not so dissimilar from her role leading the CDAO, which serves as a central hub for accelerating and spreading the adoption of AI, data and analytics capabilities across the U.S. military. She likened it to the work of CDAO’s Rapid Capabilities Cell, which has been responsible for ushering in major contracts with frontier AI models.

Likewise, IBM is very focused on “scaled adoption at the enterprise level,” Plumb said.

“So how can you get AI tools into the hands of your workforce, and do it in a way that, rather than AI as a substitute for all the humans, you team AI with the humans to drive efficiency and productivity?” she said.

Plumb explained: “IBM’s big bet is … how can we do this as an enterprise transformation and really kind of drive the AI transformation vision in concrete ways through businesses.”

In particular, she sees an opportunity for IBM in working with her former employer, the Pentagon, and the federal government at large on the business side with applications, for example, managing supply chains, logistics, contracting and more.

“That’s where I think there’s a lot of potential for rapid movement of things we find that work in IBM and applications to the federal sector,” Plumb said.

Since Plumb’s departure from the CDAO in January, the office was led by Margie Palmieri, the deputy CDAO, until DOD leadership named Douglas Matty as the new leader in April. Matty previously founded the Army AI Integration Center under Army Futures Command, which he led between 2020 and 2022. Last week, DefenseScoop reported that Palmieri, one of the CDAO’s longest-tenured leaders, is the latest to depart the organization amid a raft of others who’ve left.

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“This draft solicitation has been canceled as the Advancing Artificial Intelligence Multiple Award Contract (AAMAC) program is currently on hold,” officials wrote in the contracting document published Wednesday.

Advana is a mash-up of two words: advancing analytics. It refers to a complex data warehouse and platform that supplies the military, defense officials and their approved partners with decision-support analytics, visualizations and data-driven tools. 

Advana’s origin traces back to DOD’s chief financial officer’s unit, when staff needed to pull data from thousands of disparate business systems that were not interoperable at the time. 

In 2021, Booz Allen Hamilton won a five-year, $647 million contract to expand the program. Shortly after that, Advana’s management and oversight was one of the main Pentagon elements transitioned to underpin the CDAO when that office launched and became operational in 2022, during the Biden administration.

In the fall of 2024, senior Defense Department officials unveiled aims to potentially award follow-on contracts — and ultimately fund up to $15 billion to a diverse range of companies over the next 10 years. The draft request for proposals to inform the DOD’s potential development of an AAMAC solicitation was released in November.

Since the beginning of the second Trump administration, the near-term vision for the CDAO’s path ahead — as well as Advana’s — has not been revealed. There’s also been an exodus of senior staff from the office, including some who will not be replaced as newly installed defense leaders prioritize President Donald Trump’s demands for cuts and efficiency. 

In response to questions about the reason for the solicitation cancellation, the AAMAC hold, and the plan for the platform moving forward, a defense official told DefenseScoop: “Advana continues to mature technically and programatically. It serves as a foundational enterprise capability. The department will initiate activities in the coming months to leverage best of industry support to meet department requirements.”

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“The United States must aggressively adopt AI within its Armed Forces if it is to maintain its global military preeminence while also ensuring, as outlined throughout this Action Plan, that its use of AI is secure and reliable,” the 28-page AI Action Plan document states.

Released on Wednesday — ahead of several corresponding executive orders in the publication pipeline — America’s AI Action Plan broadly promotes more widespread use of AI and machine learning, and seeks to reduce administrative and other hindrances limiting government deployments. 

“The Action Plan’s objective is to articulate policy recommendations that this administration can deliver for the American people to achieve the president’s vision of global AI dominance,” officials wrote.

The strategy prioritizes three pillars: driving innovation, building out infrastructure, and leading in international AI diplomacy and security.

It builds on the American AI Initiative launched under the first Trump administration, and was prompted after the president rescinded a Biden administration AI mandate in January at the start of his second term.

Because of DOD’s “unique operational needs,” the new action plan carves out policy recommendations custom for the department — such as the new AI and autonomy proving ground. The process for that new test range will begin “with scoping the technical, geographic, security, and resourcing requirements necessary for such a facility,” officials wrote.

The plan also directs the Pentagon to develop a streamlined process for classifying, evaluating, and optimizing workflows involved in its major functions and, eventually, a list of its priority workflows for automation with AI.

Personnel are additionally told to “prioritize DOD-led agreements with cloud service providers, operators of computing infrastructure, and other relevant private sector entities to codify priority access to computing resources in the event of a national emergency so that DOD is prepared to fully leverage these technologies during a significant conflict.”

Further, Trump’s framework calls for new talent development programs to meet the Pentagon’s AI-related workforce requirements — and to grow its Senior Military Colleges “into hubs of AI research, development, and talent building, teaching core AI skills and literacy to future generations.”

On a call with reporters Wednesday morning, a senior White House official said that more than 10,000 responses were submitted to the administration’s request for information to inform the action plan’s development.

“It was probably one of the most diverse sets of individuals from across the country and across different sectors — from civil society, to Hollywood, to academia, to the private sector. It really represented and showed the intense interest that the American people had in this and the responses from that RFI ultimately were reflected in the report,” the senior official said.

The guidance does not explicitly name the Pentagon’s Chief Digital and AI Office in regards to carrying out any of these new responsibilities.

Editor’s note: FedScoop’s Madison Alder contributed reporting.

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The effort is part of the service’s sprawling Next Generation Command and Control (NGC2) initiative, one of its top modernization priorities to provide commanders and units a new approach to manage information, data, and command and control with agile and software-based architectures.

Army officials have said NGC2 is composed of a horizontal operational design that involves a technology stack that goes from a transport layer to an integration layer to a data layer to an application layer, which is where soldiers interact with it. That application layer is also where the Army has broken down the silos of individual warfighting functions — such as intelligence or fires — into applications that ride on the same integrated backbone.

A team of vendors led by Anduril was awarded a nearly $100 million contract last week to continue prototyping for NGC2 and scale it to a full division with 4^th Infantry Division.

Despite the award, the Army is pressing on to continue offering industry opportunities to support the program. The Army is planning to continue releasing periodic so-called characteristics of need statements, which initially served as an acknowledgement of a complex problem space, officials said.

In doing so, the service doesn’t seek to prescribe requirements for industry, but rather provide them with a broad set of challenges they could then seek to develop creative solutions against.

The most recent update, which was just recently signed out, targets decision dominance.

“To me, decision dominance is reflective of a concept,” Joseph Welch, deputy to the commanding general at Army Futures Command, told reporters on the sidelines of a daylong conference hosted by AUSA on Tuesday. “The concept of an OODA loop or a killchain has been one that’s been well established for some time and obviously very consequential to the outcome of a military engagement.”

Officials have stated that one of the most important aspects for NGC2 is the data layer. To realize the stated vision for NGC2 — the ability for commanders to do “more, better, faster” — commanders need to make sense of their data quicker than the adversary.

“The biggest thing for us is the data layer and that’s where artificial intelligence and future capabilities like artificial intelligence come in. We have to understand the data and how we integrate data across a different platform. All of our forces need access to that same level of data. For artificial intelligence, for C2, decision dominance is the answer,” Col. (P) Mike Kaloostian, the incoming director of the C2 cross-functional team for Army Futures Command, told the conference. “Whoever is able to sift through the amount of data that’s going to be available on the battlefield of tomorrow, to sort through that and use that information effectively to make decisions that force is going to win war. There’s no doubt about it … AI-enabled decision dominance is where we need to come and what the future is.”

The updated characteristics of need with the new decision dominance focus provides industry with a baseline to work off of.

Officials noted that data has to be in the right place and AI is ineffective if the location of data is unknown or isn’t in a place where it can be analyzed.

As the Army continues to work with industry partners — either working on the prototype or others still vying for future NGC2 efforts — to establish a data integration layer and scale it, there must be a destination for all the data to go.

Industry can help the Army figure out what that data plane looks like and how the service is bringing in data, ingesting it and sorting through it to make it relevant to commanders in real time. Areas the Army is interested in include using capabilities such as edge computing to process data and decisions faster than the adversary in the dirt.

Continuing characteristics of need for industry

When the initial characteristics of need concept was first announced, the plan was to update it every 90 days or so as the Army conducted exercises and experiments to keep industry abreast of the latest observations.

The plan, even after the prototyping contract, is to continue updating it; however, the cadence might shift.

Welch described periodic updates that will be based on lessons learned, which will likely come from home station events with 4^th Infantry Division at Fort Carson.

“We’re focused now on our work with our awarded team. We’re focused on the work that we’ll have upcoming through the” commercial solutions offering, he said, describing an ongoing effort with the program office to evaluate additional vendor teams and capabilities with the vision of adding them on in the future. “We’re focused on 4ID in our first prototyping initiative right now and I think there’s a lot that’ll be coming from that.”

He said the Army needs to continue to convey where opportunities exist for industry, and the characteristics of need aims to lay things out broadly, including for the Army, to understand the scope of what it is looking for.

“We’re going to continue to describe what we know about the capability as we work into prototyping, what we think we have solved and where we still think there are challenges,” Welch said.

The prototyping effort will help the Army discover what the NGC2 architecture looks like.

“We were very resistant to providing an architecture up front for companies to bid on, not because we don’t understand the importance of it, but because we feel it’ll likely be emergent as we work through, continue on with the prototype, with whatever commercial software or sets of commercial software may underpin it. That’s something that will emerge as we continue to work the prototyping effort,” he added. “That may be a level of detail that may not be in the characteristic of need, but will certainly be, I think, very useful to industry in terms of understanding where the opportunities, the base of which to innovate upon, is going to get established.”

Welch noted that within the technology stack, he’s always envisioned sub-problem statements that components of teams can try to help solve.

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“After more than three years as the inaugural Principal Deputy of the Chief Digital and Artificial Intelligence Office, Ms. Margaret Palmieri will be departing the organization in August. We are immensely grateful for the incredible groundwork she laid while standing up the CDAO,” a defense official told DefenseScoop on Monday.

Four predecessor organizations — the Joint Artificial Intelligence Center, Defense Digital Service, Office of the Chief Data Officer, and the Advana program — were fused together to form the CDAO, which was announced in late 2021 and reached full operating capability in 2022.

One of the earliest CDAO employees, Palmieri was tapped to serve as its first-ever deputy chief in early 2022, soon after the office was announced. Before that, she spent more than a decade in the Office of Naval Operations where she led a number of technology-driving initiatives, including setting up and leading the Navy Digital Warfare Office.

At the CDAO, she helped steer the Pentagon’s AI and machine learning strategy, development and policy formulation and create the foundation for departmentwide digital infrastructure and services to support military and civilian components’ algorithmic-enabled asset deployments. Palmieri also led the CDAO in an acting capacity multiple times during her tenure, including most recently during the transition into the second Trump administration.

Her planned departure marks the latest in an exodus of senior leaders and other technical employees from the CDAO in recent months, and comes as the office’s new leadership has yet to publicly reveal its vision for the future. 

DefenseScoop has contacted Pentagon spokespersons regarding whether a new deputy has been selected to replace the deputy CDAO in a permanent or acting capacity.

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