Perspective_

A commander facing an emerging threat today has access to unmanned systems (UxS) feeds, intelligence updates, operational tracks, subordinate reporting, sustainment data, and other sensor inputs, all containing pieces of the picture needed to act. The critical information is there, but finding it, validating it, and separating it from everything else competing for attention takes time. As modern command and control (C2) succeeds at connecting more systems and making more data available, the challenge shifts from accessing information to turning decision advantage into authorized, executable action across a distributed force—often when connectivity is intermittent or degraded. The problem is has expanded beyond how quickly a headquarters can understand the fight to how reliably that understanding becomes coherent action across a force that is increasingly distributed, software-enabled, and autonomous.

The next C2 challenge

For years, C2 modernization has focused on overcoming information scarcity by connecting systems, integrating data, breaking down stovepipes, and accelerating decision advantage. Efforts such as CJADC2 and NGC2 demonstrate meaningful progress in the foundational work to make data discoverable, interoperable, trusted, and usable. But that progress creates a second-order challenge: as the force collects and integrates more data, increasing information availability can create information saturation. At the same time, increasingly distributed forces and increasingly autonomous systems mean that decisions must travel farther, reach more elements, and remain valid even as conditions and connectivity change.

That is only the first part of the challenge. Once the commander understands the situation and decides how to respond, that decision must become executable action across a distributed force. Commanders must communicate the right information, the intent behind the plan, and the authority delegated so that subordinate leaders can exercise disciplined initiative and unmanned systems can execute within defined bounds. When communications are disrupted, that intent helps people and machines remain aligned; when connectivity returns, the force must be able to reconcile what changed, preserve the history of what was authorized and executed, update the plan, and redistribute revised intent. The C2 problem extends beyond decision speed to the durability and coherence of the decision after it leaves headquarters.

The C2 lifecycle

C2 is not complete when a commander makes a decision. In a distributed human-machine force, the decision must be translated into intent, bounded by authority and constraints, executed at the edge, adapted as conditions change, and reconciled when the force reconnects. That creates a continuous lifecycle: sense, decide, express intent, delegate authority, execute, adapt, reconcile, and redistribute revised intent. The design question therefore extends beyond how quickly a headquarters can make a decision to how reliably that decision can remain coherent as it moves through the force.

Decision advantage is the foundation

Decision advantage produces a mission outcome only when the force can act on it. The enterprise may need to integrate enormous volumes of operational data because it cannot always know in advance which combinations will become important. But broad data integration and broad data exposure are not the same requirement, and human decision-makers should not have to consume that same volume directly. The answer is not to integrate less. Future C2 should integrate broadly, then inform selectively.

The information surfaced to a company commander should reflect the decisions the commander is responsible for making. Division staffs need a different view. A logistics node, fires cell, individual operator, or unmanned system each need another. The relevant information changes with mission, echelon, authority, time, and operational context.

AI, analytics, and software should protect the commander’s capacity to command by helping answer three questions quickly:

• What changed?
• What matters?
• What requires my decision?

From decisions to distributed intent

The force must translate these decisions into objectives, priorities, authorities, constraints, acceptable risk, and sufficient operational context for subordinate elements to act. Mission-planning software, shared semantic models, and machine-readable tasking must then embed those elements in a versioned plan that tells people and machines what they are expected and authorized to do, as well as when those authorities change or expire.

We call that distributed intent.

This is not a replacement for mission command or commander’s intent. Mission command is the operating philosophy; distributed intent is the systems construct for carrying that philosophy through a force in which actions are increasingly executed by distributed humans, software, and autonomous systems. The distinction is that intent is an explicit, versioned, machine-readable object that carries objectives, priorities, authorities, constraints, and context, meaning intent can be reconciled when conditions and connectivity change. Distributed intent is therefore a mechanism for carrying established command relationships into an increasingly distributed operating environment.

Distributing intent does not eliminate hierarchy or replace centralized command with unrestricted autonomy. It gives subordinate leaders enough understanding and delegated authority to exercise disciplined initiative when detailed direction is unavailable, or conditions are changing faster than headquarters can respond. For machines, the same construct establishes the goals, permissions, constraints, and conditions under which execution is authorized.

Subordinate elements closest to an emerging threat may see opportunities or risks that were impossible to anticipate when the original plan was issued. Preserving their adaptability becomes a strength when they can remain aligned with the broader operation.

Future C2 should help subordinate leaders understand not only their tasking, but why it matters, which priorities take precedence, which authorities are delegated, what they are authorized to change, and which boundaries they must respect.

Aligning people and machines

The rapid growth of unmanned and autonomous systems makes this problem more urgent.

UxS increasingly operate on both sides of the C2 equation. As sensors, they generate imagery, tracks, detections, telemetry, and other data—sending more information toward commanders. As effectors, they support missions from reconnaissance and protection to electronic warfare, logistics, deception, and kinetic action—requiring commanders to push objectives, priorities, and tasking back toward ever more platforms at the edge.

Without a different approach, commanders risk being overwhelmed twice: as consumers of machine-generated information and as managers of individual machines. Future C2 should abstract that complexity so commanders can operate at the level of mission intent rather than platform-level control: observe this area, protect this formation, prioritize these threats, preserve this capability, remain within these constraints. Planning and autonomy software, policy engines, and human-machine interfaces must express that intent in forms suited to humans and machines: people need purpose, priorities, and latitude; machines need explicit and authenticated goals, boundaries, permissions, prohibitions, and abort conditions.

Human leaders retain responsibility for judgment, risk, accountability, and purpose, while autonomous systems provide speed, persistence, scale, sensing, and execution within defined bounds. Future C2 systems must use distributed intent to align people and machines without allowing cognitive burden to scale alongside the number of sensors and autonomous assets.

AI as a force multiplier

AI can help commanders manage complexity across future C2 systems by surfacing second- and third-order effects, identifying how a change in one part of the battlespace may affect others. This includes identifying emerging conflicts and generating courses of action that account for commander-defined priorities, authorities, and constraints. In LMI’s SHEPRD™ platform, for example, AI tools take real-time threat tracks and provide decision-makers with courses of action shaped by these priorities and constraints. The same principle of supporting decision-makers holds when a resupply route becomes unsafe or a supported unit changes mission: C2 should identify likely downstream effects, recommend route adjustments, and help propagate approved changes across the force.

Used this way, AI becomes a force multiplier, reducing the human effort required to monitor complexity, identify consequential changes, and coordinate responses across an increasingly complex battlespace. Over time, that may reduce the staffing burden associated with some C2 functions, with corresponding reductions in the personnel, protection, and sustainment required to support them. The more immediate benefit, however, may be a different allocation of human attention: less time spent monitoring and reconciling routine changes, and more time spent exercising judgment where consequences are highest.

Disconnection is not the end of the C2 cycle

In addition to aligning a larger human-machine force and helping commanders manage its increasing complexity, C2 must preserve that alignment when communications fail. Imagine a subordinate formation intermittently loses connectivity during a rapidly developing engagement. It moves to, expends resources, identifies a previously unknown threat, and adapts its approach. At the same time, higher headquarters receives new intelligence and changes a broader operational priority.

Each time connectivity returns, both echelons may have changed the operational state and may hold actions or authorities that were valid when connectivity was lost but now conflict with higher-level changes. The harder problem is not simply merging two sets of data; it is determining which actions, authorities, and elements of intent remain valid considering what changed while disconnected.

Future C2 should make resynchronization after communications are restored a core function rather than an administrative task. Versioned plans, event histories, provenance, and distributed synchronization must reconcile data and state, authority, and intent. AI-assisted comparison can surface consequential conflicts and ambiguities for human adjudication before revised intent is redistributed.

When a subordinate action remains valid under the authority available at the time it was taken, but conflicts with a newly issued higher-level intent, the system must preserve that history rather than simply overwrite it. Doing so allows commanders to distinguish what happened, what was authorized, what changed, and what requires a new decision.

Reconnection closes the loop. Once conflicts are surfaced and adjudicated, revised intent must be re-expressed and redistributed, beginning the cycle again. In this model, synchronization is not a back-office function; it is part of command.

Enabling the future C2 model

Taken together, these requirements define the emerging C2 gap: turning information and decisions into durable, bounded intent that can be executed, adapted, and reconciled across a distributed human-machine force. The opportunity is to connect the functions across a single lifecycle rather than treating decision support, planning, execution, and synchronization as separate problems.

Implementing this model requires C2 services that treat intent, authority, and operational state as core objects; preserve provenance and version history; present role- and context-appropriate information; support execution at the edge; and surface consequential conflicts for human adjudication. These capabilities provide the digital mechanisms needed to carry, apply, and reconcile command relationships across the force.

The underlying data architecture will integrate broadly while interfaces inform selectively, surfacing what matters without forcing commanders to search the expanding data environment. Planning, orchestration, and decision-support tools will help commanders turn decision advantage into mission-appropriate objectives, priorities, authorities, constraints, and context for humans and machines. When the network degrades, edge services and local mission data keep the force operating through disruption. When connectivity returns, versioning, provenance, and synchronization reconstruct changes while AI surfaces important conflicts so commanders can update plans and redistribute revised intent.

Distributed intent: decision advantage to coherent action

The future C2 model can be framed simply: Integrate broadly. Inform selectively. Distribute intent. Resynchronize rapidly.

Decision advantage remains essential. But the goal cannot be to simply make more information available faster. The goal must be to ensure commanders in the increasingly complex human-machine force can focus attention, communicate intent and delegated authority, and keep the force acting coherently, all without overwhelming them and without assuming continuous connectivity.

LMI’s view is that the emerging C2 opportunity is to connect these functions across one continuous lifecycle—from sensing and decision support through intent, delegated authority, edge execution, adaptation, and reconciliation—so that decision advantage survives the rest of the operation. The differentiator preserves coherent command as decisions move through the force, change at the edge, and are reconciled when the force reconnects.