The digital transformation of armed forces’ resources and platforms is generating massive volumes of data, from both human and automated technical sources. However, to confer an operational or even a strategic advantage, this data must be prepared, sorted and processed, to avoid creating an information and cognitive overload, whether at the level of the individual combatant or headquarters. The use of algorithms at the right levels can improve decision-making by filtering the growing mass of data collected, and building a better situational picture. The use of these new technologies increases combatants’ ability to act in a collaborative and coordinated manner, thanks to the sharing of information in real time, the networking of all levels and the use of the Internet of Things and the cloud. Combining a military Internet of Things (IoMT) with an AI-enhanced C2 structure will accelerate real-time data collection, information exchange between units and coordination of operation
Combined with human decision-making capabilities, “artificial intelligence” algorithms become “machine-augmented (human) intelligence” and can provide a decisive advantage at the strategic, operational and tactical levels. Augmented Intelligence (AI) can boost the capacity of command posts (CPs) to process masses of data and extract trends not detectable to the human eye or precise information buried in this mass. Ultimately, AI should make it possible to reduce the number and size of CPs, increasing their stealth, agility, mobility and responsiveness. Based on a connectivity architecture dedicated to massive data processing, AI should also make it possible to offer commanders options based on the analysis of available data in record time, enabling them to move faster from knowledge to anticipation.
While AI will never be able to demonstrate an initial intention, the prerogative of a sentient being, it will certainly transform the way in which command is exercised. Its ability to process information in near-real time, and to apply self-enhancing models, will enable it to be increasingly integrated into the decision-making process. However, this integration can pose major problems, starting with commanders’ dependence on this type of solution and the relative loss of the ability to make decisions in uncertain conditions, in the event of malfunction or destruction. It is also important to bear in mind the inability of AI to innovate or propose breakthrough solutions, based, by design, on past data and the application of statistical models, albeit highly advanced ones (machine learning). A C2 system ‘boosted by AI’ can nevertheless become a decisive operational advantage, once a balance has been struck between maintaining a human capacity for analysis and decision-making – and therefore the inherent risk-taking – and accelerating the OODA (Observe, Orient, Decide, Act) loop. Similarly, on a more technical level and to be truly effective, the AI employed by all levels of command (strategic, operational, tactical) will need to incorporate an explanatory component, so that the solutions or recommendations issued by the systems can be questioned and analysed by humans to refine the analyses and options proposed. Acculturation of command levels to the understanding and proper use of AI as a decision-making tool will be an essential challenge if we are to take full advantage of it.
Initial feedback from Ukraine also shows the importance of developing a multi-domain C2 doctrine (MDC2) that takes account of civilian contributions, particularly in the network area, as in the case of the Starlink satellite network in the resilience of Ukrainian communications. But this civil/military interweaving also goes further in terms of relations with civilian populations, for example the contribution of the software ecosystem to the development of intelligence applications – which raises the problem of the distinction between civilians and combatants – but also the development of ‘civil protection’ and warning applications. For the Atlantic Alliance, the challenge will also be to harmonise the various national MDC2s to develop an effective decision-making process, enabling information to be shared rapidly. Generative AI, capable of synthesising masses of heterogeneous data to propose options to commanders, could be one way of overcoming the growing complexity of these interconnected MDC2s, which the exponential growth in the mass of data and the acceleration of the OODA loop risk paralysing.
As a result of the massive digitisation of platforms and equipment at the tactical level, the problem of the bandwidth required for data transfer is already arising, and beyond that, the problem of the computing capacity needed to use it. To reduce the amount of data transferred, armed forces and manufacturers will have to install more computing power in vehicles and tactical systems, so that some of the processing can be carried out locally. As the tempo of operations accelerates, AI will give the tactical echelons a decisive advantage by making it possible to deport analysis capacity as close as possible and thus speed up the targeting cycle (Find, Fix, Track, Target, Engage, Assess) by automating certain functions. However, these AI systems will need to be designed in a ‘distributed’ way to ensure their ability to operate autonomously, otherwise the theoretical advantages will be disconnected from the realities on the ground.
In the event of a major engagement, the acceleration of the OODA loop and MDOs have implications for the chain of command that the post-Cold War period had led us to forget. For the enemy, destroying or neutralising CPs is a priority objective and, as seen in Ukraine, an achievable one – whether through tactical or strategic action. Another reminder of the current conflict is the importance of electronic warfare (EW), localisation, jamming and – in defence – reducing electromagnetic signatures. The physical (mobility) and technical (electromagnetic stealth) agility of CPs must therefore be taken into account to ensure that the digitisation of these PCs does not become a vulnerability factor on the battlefield. In order to speed up the installation of CIS resources while maintaining electromagnetic silence for as long as possible, certain technologies can be used, such as Li-Fi (Light Fidelity), which was tested during phase 4 of the Orion exercise.
The war in Ukraine also highlights the important role of cyber defence in a major operations, whether for purely military aspects, critical infrastructures or even private individuals. To maintain essential command functions and support the civilian infrastructure still in place, modern cyber defence must be more agile, in order to switch CIS architectures from peacetime to wartime mode faster.
