The Future of the Command Post

As the flow of information into a command post gets more and more complex, they system that processes this information must learn to adapt as well. The introduction of AI into these systems has broadened commanders and their staff’s access to large pieces of data as well as metadata. In this article by Signal, discover how command posts are racing to upgrade their information analysis systems to keep the influx of data running smoothly. 


Artificial intelligence could turn data paralysis into information analysis.

Technologies are spawning a revolutionary improvement in command and control that will have a transformative impact on how it is conducted at the operational level. These advancements, particularly artificial intelligence, are changing command and control functions such as sensing, processing, “sensemaking” and decision-making. Even greater changes lie ahead as innovation serves a larger role in defining both form and function.

Command posts are where commanders and essential staff generally reside and make decisions, so they are designed for information flow. As the speed of communications, richness of data, capability options, diversity of actors, and amount of friendly and adversarial information have increased, so have the requirements for larger staffs and expertise to grow to sort through this complexity. Leveraging technology will be critical to capturing an ever-increasing amount of data while turning it into improved decision-making instead of information paralysis.

The associated downside of a larger staff size is that it becomes unwieldy, causing breakdowns in communications between staff elements and creating a mass of personnel that represents a high-value target for adversaries. As such, protection and ensuring operational availability has and will remain critically important. This task will be increasingly difficult as new weapons and tactics shrink both the battlefield and the time to respond to an adversary’s actions. Hypersonic weapons, weaponized satellites and direct energy weapons will present a severe threat to mission-essential land-based facilities, especially operational command posts.

As a result, future command posts will need to rely on a high-availability network featuring multiple nodes and communications routes to connect personnel or organizations despite their locations or roles. They will need to always be connected, reducing human actions at the tactical level to ensure network or communications availability. In addition, the networks required to manage communications in real time-and respond to degradation, failure, hostile action and more-will require artificial intelligence (AI) to continue to operate effectively.

Designing the specifics of a technologically transformed command post for the year 2035 is challenging but can address these issues. Various levels of automation, up to and including the use of AI, will augment human skills and improve the decision-making process. Sensor availability and usage will increase exponentially, bringing ubiquitous access to data and further blurring the lines between the strategic, operational and tactical levels of war.

These improvements could make the future command post an increasingly tantalizing target. As a result, distributing and dispersing the headquarters and its personnel will be critical for maintaining effective command and control (C2). Exploring technology that makes communication, interfaces and decision-making seamless, resilient and fast will be essential for enabling operational level success on the battlefield.

With future conflicts likely to take place in megacities and highly populated areas, deployed military commanders will need access to local sensors, including not only cameras but also sensors or data feeds related to other essential activities in or around a city. Future commanders will count on a myriad of sensors that will feed a data lake with all types of raw information. Military forces will deploy some sensors, while public or private organizations in the area of operations will own others. These could record economic activities; monitor critical infrastructure or weather; involve social networks; or include structure plans and public records.

Access to nonorganic sensors will require an expansion of the C2 structure. In addition, memoranda of agreement or technical agreements will need to be in place before conflict erupts to enable the cooperation between the military commander and the sensors’ owners such as governments and ministries.

In combination with AI, multisensor platforms will optimize the information delivered to the data cloud. Once the data is in the cloud, AI will facilitate interpretation of the near-raw information differently. It will recognize voices, faces and shapes in videos or pictures. Accordingly, to take full advantage of this capability, sensors would not be switched on only at the moment of gathering the information directly related to the mission’s purpose. Instead, they would collect information continuously.

Keeping an insider threat perspective in mind, placing sensors within a command post with the same level of monitoring also should be considered. Internally recording all conversations, physical movements and communications would have broad implications for process improvement, machine learning and AI refinement; however, the implications for privacy are large.

Collecting this amount of information can pose its own set of problems. “The volume of information, the requirement to integrate numerous information sources and the speed of the reaction can result in information overload and can lead to decision paralysis,” according to a NATO statement. However, the combination of AI, data lake, deep learning and advanced analytics will enable sensemaking and decision-making with a reduced likelihood of paralysis.

But having a populated data lake from which to pull insights to answer requests for information does not ensure the information needed to conduct operations is available or sufficient. The right query must be formulated, likely to be enhanced in the same way AI improves Google search queries.

Advances in other elements in the man-machine command interface also will be needed. For example, the user interface is likely to see significant improvements, alleviating the barriers commanders encounter when searching for relevant data. Virtual and augmented reality also will help a commander establish new C2 relationships with new actors.

These capabilities will benefit commanders in other ways. For example, without the need to travel around the area of operations, the commander will be able to quickly “visit” distant places virtually. This technology will create the opportunity for distributed and dispersed command posts, bolstering increased resilience in this vital C2 supporting construct.

In addition to advances in virtual reality technologies, developments in AI undoubtedly will affect decision-making processes in the future. AI will present objective analyses and recommendations to the commander. At some point, with continual exponential improvement expected, AI will become better at decision-making than commanders in some if not most situations.

Once people begin to trust AI decision-making through experience and positive performance, more responsibilities will be delegated to AI, possibly even replacing positions staff members currently fill.

To address this inevitable situation, planners need to identify thresholds that define when, how many and what type of decisions to transfer to machines. These thresholds primarily will depend on the potential impact of the decision in each situation.

For example, at an operational-level headquarters, the primary driver is the length of the operations planning. Long-term plans are created for activity that will take place in more than 10 days, while medium-term strategies involve actions to be taken in three to 10 days and ongoing operations take place within three days. The overarching process that measures the deviation from the original plan is the operations assessment process, which provides the commander with the recommendations required to get the plan back on track or ensure it remains on track.

AI can assist with this operations assessment process by providing accurate situational awareness. It will help the staff to analyze trends and predict scenario possibilities and developments. AI will recommend operational actions to achieve operational effects, and it is likely to suggest activities the staff would not have identified or correlated.

Technological advancements in communications and networks have shifted. The commercial sector is developing the most advanced capabilities at an increasingly faster rate, and governments and their militaries are struggling to adapt their acquisition policies to take advantage of the technological changes. More aggressive adoption of technologies such as AI will enhance mobility and dispersion of command posts at the operational and tactical level, which is critical for delivering capabilities and achieving operational effects.

Lt. Col. Federico Clemente, ESP A, and Cmdr. Stephen Gray, USN, are staff officers in the Analysis and Concepts branch at the NATO C2 Centre of Excellence, Utrecht City, The Netherlands.


This article was written by Stephen Gray and Federico Clemente from Signal and was legally licensed through the NewsCred publisher network. Please direct all licensing questions to