In fact, some senior military leaders think that AI will be more important to great power competition than military power itself. The military needs a strong plan now if it does not want to find itself shooting useless algorithms at its most challenging problems tomorrow.
AI is not magic; adopting AI tools is no guarantee of success. But given the role AI is likely to play in future conflict, not adopting AI will likely guarantee failure. Therefore, learning how to effectively use AI today—with all of its strengths and weaknesses—will be critical to success on future battlefields.
Readiness—a keystone challenge for AI
Assessing readiness informs or draws upon nearly every aspect of military decision-making, from tactical operations to force structure to budgeting. To make readiness assessments and decisions effectively also requires huge volumes of diverse data from many different sources. Large data volumes, diverse sources of information, complex interactions, and the need for speed and accuracy make readiness a problem tailor made for AI to tackle. And if AI can help tackle readiness, it can help the military tackle just about anything.
We have described how redefining readiness can help bring new tools and technologies to bear and provide greater insight than ever before. At its core, this redefining breaks readiness assessments into three smaller tasks: You have to understand what capabilities are required, to know the current status of those capabilities, and to act to improve those capabilities where needed. Each of these readiness tasks involve sifting through mountains of information, teasing apart complex interactions, and then trying to understand the effects of any decision. That makes them incredibly difficult for human planners to tackle, but perfect for AI.
AI tools can tackle many different aspects of readiness, everything from understanding force requirements to increasing aircraft up-time with predictive maintenance. However, the real power of AI in readiness does not come from discrete point solutions, but from linking many different AI-powered tools together. Then, the smart output of one tool can become the smart input to another.
Putting the AI pieces in play
The term AI may be misleading in one respect. It may lead us to believe that there is just one type of “intelligence” that all AI tools aspire toward. Nothing could be further from the truth. Different AI tools have different purposes, different strengths, and different weaknesses.
The important insight here is that AI is not a magic bullet to all problems. Until future research breakthroughs create a general purpose and context-aware AI, users must make informed choices about the trade-offs inherent in different AI tools. Perhaps the most basic trade-off is between depth of insight and model complexity, which is at the heart of any discussion of assessing military readiness. Some of the information requirements inherent in assessing readiness are simpler and can be aided by simpler AI tools.
For example, today the requirement to understand the assets required of an assigned mission is often done in the context of static planning documents. These are assembled at a strategic or operational level and infrequently change. However, even relatively simple AI can yield more dynamic and potentially more accurate predictions by making use of historical mission data. Historical mission examples and existing plans, such as operation plans OPLANS and concept plans CONPLANS, provide much information on which assets—people, equipment, and infrastructure—have been deployed around the world. Each historical mission also has unique factors, from terrain to adversary capabilities to timeline. Pairing these two types of data in an AI tool such as a neural network can allow users to make predictions about which assets are vital for success of their particular mission set.
However, other aspects of readiness require deeper insights that can only be provided by more complex models. The resources and time required to build and run these complex models mean that they are not well-suited to every situation. As a result, defense leaders seeking to know current force capabilities or how to act to best improve those capabilities face a choice.
They can either have faster, lighter, but less reliable answers to those questions or more reliable answers but at the cost of time and resources. It’s important to understand that these are the general trade-offs military leaders face in their adoption of AI.
How would you define AI?
The term “artificial intelligence” can mean a huge variety of things depending on the context. To help leaders understand such a wide landscape, it is helpful to distinguish between the types of model classes of AI, and the applications of AI such as classifications based on how AI works; and also based on what tasks AI is set to do.
Most debate about military artificial intelligence centers on robots, but professionals usually talk logistics. Without fuel, ammunition, spare parts, and maintenance, no weapon, manned or unmanned, is going anywhere.
What’s more, while AI has made great progress in recognising objects/targets and navigating the physical world, autonomous combat robots are far in the future.
New contract to apply artificial intelligence to Marine Corps maintenance could streamline logistics and help lessen dependence of fighting forces from long supply lines. Ultimately, AI could enable the far-ranging manoeuvres envisioned by the multi-domain operations
Marines will apply AI-driven “predictive maintenance” to part of its aging fleet troop carriers equipped with diesel engines, heavy-duty transmissions, and other features with hundreds million hours of metrics on diesel engines alone, and in the world of AI machine learning, the more metrics you have, the more accurate your predictions get.
The goal is to track the performance of each major component in real time — oil pressure, turbocharger speed, battery life, etc. etc. — and predict when it’s likely to fail.
Predictive maintenance has two benefits. First, most obviously, it lets you replace or repair a part before it breaks on you. Second, it lets you skip a lot of so-called preventive maintenance, when you pull your vehicle into the shop after so many hours of operation because that’s when, on average, such-and-such a component will need an overhaul.
There’s been a small blitz of media coverage of the contract, but it’s focused on how predictive maintenance can improve efficiency and cut costs, but there are uniquely military benefits.
Logistics has been a double-edged sword for Marines for generations. On the upside, plentiful supplies of fuel, ammunition, and spare parts in good times have kept huge armoured forces on the march. On the downside, the long supply lines, iron mountains of Marines will apply AI-driven “predictive maintenance” to part of its aging fleet troop once it’s arrived.
Marines could cope with these logistical limits when it has months to build up before the shooting started, with nearby as bases, and a relatively short distance to drive.
But logistical demands can be much greater when distances are longer with large combat formations moving along a single axis of advance, let alone supply convoys and depots.
So emerging concepts called multi-domain operations or distributed operations envisions Marines spreading out to make themselves harder targets. Relatively small units would operate “semi-independently,” moving frequently from one position to another, without resupply for days at a time.
The problem is Marines are not set up to do this today. Heavy armoured vehicles just require too much fuel and maintenance to operate this way. The long-term solution is to develop lighter and less logistically demanding vehicles, but recent efforts have been less than successful.
In the meantime, Marines need to figure out how to support the forces it has more efficiently so they can manoeuvre more freely, with less frequent pit stops for maintenance or supply runs for repair parts.
That’s where the new contract comes in. A lot of maintenance that’s done is based on what the owner’s manual says. You should go and get your oil changed and your engine checked every so many miles which can function as a baseline but it doesn’t take into account how the machine is being used and the wear and tear and stresses.
So we track not only the individual performance of specific components on specific vehicles, but also external variables like weather. Heat, cold, and humidity can all impose stress on machinery.
Where is this information coming from? It turns out the ability to put digital sensors on its products got ahead of its ability to do anything with it. A lot of machines have the sensors already on them that are producing metrics, it’s just that nobody’s listening.
Another problem is when vehicle is in a location with poor bandwidth, or if there’s a military reason to turn off all transmissions, the system can stop sending updates for a time. It can also do some of the assessments onboard the vehicle and may not have to send the results back to the central station minimising bandwidth use and transmission length.
But the big benefit is the ability to pool all available information in one place and then let machine learning figure out patterns, which can then be used to forecast future performance.
We can track general trends across a fleet of vehicles, but the real value is with prediction. Imagine if, instead of having to go to the shop for your scheduled work, you could have your status 24/7.
On the individual machine/equipment level, will the fighter unit make it through the day and do what it needs to do?
Our goal is for tactical commanders to know -- we have this many vehicles this is what the overall status is for each one so better strategic decisions can be made.
Logistics is the ‘bridge’ taking resources and applying them on the battlefield. At first, many activities which occur within this ‘bridge’, are properly controlled and coordinated, ultimately contribute to the overall ‘readiness’ of the logistics system to act when it is required.
But many issues result from how the logistics process are not suited to the demands of the real operation when it happens. Some logistics deficiencies could have been directly addressed through improvements in resourcing. But there are many other influential factors essential for logistics readiness, and the early performance of the logistics process at during an operation.
When readiness comes up in meeting, many leaders confuse it with preparedness terms such as a ‘notice to move’. But it is common to find that despite a unit being well within its designated ‘notice’ when time comes for action, the unit is constrained because of the availability of kit, a lack of enabling elements available in supporting formations, or slow activation of resources by strategic organizations and also other logistics factors.
In some cases, strategic-level decisions result simply because available capabilities cannot be appropriately sustained and are unable to be deployed. No operation is free of friction caused by logistics, but in many times readiness of logistics systems inadequate, under-resourced and inefficient.
Fundamentally, logistics readiness is the ability to undertake, to build up and then to sustain, combat operations at the full combat potential of forces. Readiness can comprise of actions undertaken during operations, but is predominantly a consequence of routines and practices set in organisation behaviour long before deployment.
It is not a simple matter of issuing logistics units their own ‘notice to move’ or applying some other metric that will inevitably be ‘crashed’ through in a time of crisis.. Logistics readiness is a function of total organisational performance and efficiency factors that are applicable at all levels – from the strategic to the tactical:
1. Must be a high state of materiel readiness across the force. In addition to appropriately funding the sustainment of equipment, and the establishment of appropriate stockholdings in appropriate areas to enable operational contingencies, the means of sustaining equipment must be as appropriate for support operations as they are for efficiency in garrison.
2. Failures in materiel readiness in garrison are often replicated in major sustainability issues on operations, and necessitate consequential actions such as cannibalisation to achieve desired operational readiness outcomes.
3. The logistics process, capabilities and organisations must be systematically assessed for its readiness. Every military activity or exercise is an opportunity for assessing logistics performance, but most military exercises don’t comprehensively test and assess operational sustainability and logistics readiness.. Fewer still are those exercises that test logistics readiness through a major deployment performed at short-notice; a phase of an operation that demands all supporting agencies are ready.
4. Must be timely exchanges of information; one of perennial challenges in supporting operations is knowing how far to compartment operational information, especially with commercial partners.
5. Must be an appropriate balance of logistics resources to the combat elements. This is captured in the idea of the ‘tooth-to-tail’ ratio.
6. Logistics resources can be appropriated by a variety of means, but the important factor is the total amount of firepower which can brought to bear. Determine the amount of effective power can be delivered and make smart choices about personnel type ratio.
7. Logistics plans and policies, from stockholding policies at the unit and formation level right up to national mobilisation plans at the grand strategic / economic level must be available. Format and bulk of plans are less important than those that are developed through interagency effort, and reflecting the nature of an efficient and effective logistics process.
8. Logistics organisations must be structured to support operational requirements rather than bureaucratic needs. Although organisations may not need to be resourced to their full wartime capability during most periods
9. Organisational architecture must be established to enable the transition to an operational footing and policies in place to enable such a transition to occur rapidly.
10. Must be a mutual understanding between commanders and the logistics units, agencies and organisations that support them founded on clear execution of commander’s intent, but also the culture of cooperation set within the military or formation.