The Use of Predictive Artificial Intelligence to Support the Strategic States Decisions During a Diplomatic Escalation or Military Conflict: What Lessons for Morocco?
Introduction
The increasing uses of predictive artificial intelligence (AI) have surpassed the known applications in the economic and commercial fields, as this technology has begun to invade the domain of strategic prediction and the organization of critical terrains and spaces. The process of strategic decision-making combined with the potentials of predictive AI to simulate possible scenarios, avoid undesirable situations, and improve strategic decision-making during an escalation or crisis or conflict situation currently constitutes the most frequent uses in the processes of coupling AI potentials in order to serve victory and hegemony. The fact that the potentials of AI are now widely known, and its contribution to the facilitation and normalization of various tasks and processes, especially in the real-time processing of massive data, encourages states to multiply its use and accelerate its integration into other areas that have been dominated by human monopoly for decades. This seems very effective in this disrupted global context full of geopolitical rivalries, diplomatic crises, and military conflicts, where the precision and purification of decision-making have become paramount for decision-makers and states (Machado, 2024). Morocco, as a country with its geographical, geopolitical, and strategic challenges, seems convinced of the use and integration of the potentials of predictive AI in its decision-making processes in order to overcome the influence of ground factors towards the improvement and purification of diplomatic and strategic decision-making in the face of the causes and critical situation surrounding it (Houdaigui, 2019).
Human analytical and predictive capabilities always fall into uncertainty, where the ability to make decisions is far from the influencing factors on the ground, deviating the applicability of the decision and disrupting the course of such planning is an admissible reality. Because the inability of humans—especially in analysing the enormous flows of data in the contemporary world in real-time—risks blurring the imagination of scenarios and the anticipation of critical situations and consequently limiting the predictive potentials of decision-making during a crisis or escalation (Ahajjam et al., 2021). The speed at which information and data flows currently circulate calls into question the capabilities of traditional decision-making methods and processes, maintaining this challenge where time is costly in critical cases and situations, which stipulates speed in decision-making and efficiency in de-escalation (Golfrab & Lindsay, 2022). In this sense, the potentials of predictive AI demonstrate better capabilities to achieve certain improvement objectives and the conciseness of strategic decision-making in critical cases and situations, where the speed of processing and analysing collected data optimizes time and consolidates the old strategy, evaluates alerts, and refines the prediction of critical scenarios (Horowitz & Greenberg, 2022). Indeed, the integration of AI potentials for improving critical decision-making in unpredictable situations appears effective and relevant, thanks to the capabilities that AI offers to decision-makers, providing them with full powers to devise proactive, effective, and timely diplomatic or strategic solutions.
However, the massive integration of AI potentials into these sensitive processes can lead to certain distortions in decision-making instead of perfecting it, such as algorithmic anomalies and issues of usage and ethics, including the challenges of hacking and intrusion into these systems, or the complete exclusion of the balancing role of humans in these processes, which can negatively impact strategic decisions supported by predictive AI and reconfigure the acceptability and behavioral adaptation of humans to/from such decisions (Vold, 2024). To this end, Goldfarb and Lindsay (2022) continue to advocate for the primordial role of humans in these processes and critical situations, emphasizing that the multitude of benefits from using AI should in no way—according to these authors—urge us to ignore the value of human awareness and ethics and their importance in these situations. Mc Chrystal and Roy (2023) went further by urging states to harness the potential of AI to act more swiftly in these situations, avoiding the human longevity that an adversary state could potentially exploit AI for the same predictions, taking the initiative and rendering our vulnerabilities intangible.
According to Bjola and Pokhriyal (2023), we are witnessing a rise in the use of these technologies, with the Ukrainian conflict serving as an example of such situations, demonstrating how the use of AI has facilitated diplomatic decision-making and provided effective alternatives for managing the crisis on the ground and especially for intelligence operations. Barnea (2024) adds that the use of AI’s potential in data analysis helps states manoeuvre positively and in favour of the stability of their regions by strengthening their predictions and forecasts of undesirable scenarios. For this, we attempt in this intervention to analyse the limitations of AI usage in crisis processes or critical situations according to the requirements of the Moroccan context, and how Moroccan decision-makers can harness the potentials and opportunities of these systems without ignoring the usage requirements and exploitation challenges. And finally, through this study, we want to contribute to the creation of a national awareness around the use of AI in the diplomatic and military fields by believing in its predictive capabilities in critical situations and by ultimately providing useful recommendations to Moroccan decision-makers to increase their agility and adaptability in these continuously changing situations.
Context of the Research
Karthikeyan (2024) and Aliyev (2024), articulate their results on the adoption of predictive AI potentials to strengthen and refine strategic decision-making by demonstrating the algorithmic capabilities of these systems through real-time analysis of collected data, including their potential to identify influencing factors that deviate processes or affect human capacities and behaviours during decision-making in critical situations. Aliyev (2024) adds that the potentials of predictive AI are indeed real in the economic field and the global market sector by analysing individual behaviours and predicting market directions and trends, as well as the flow of trade, helping economic and commercial decision-makers anticipate market needs, transaction directions, and business environment behaviours, and to develop adaptive strategies. Predictive AI, therefore, in the economic field according to Asiabar et al, (2024), has indeed helped economic decision-makers to refine their decisions and achieve their market interests thanks to its analytical, processing, and predictive capabilities.
The contribution of predictive AI to the accuracy and conciseness of economic decisions in critical cases and uncertain situations will prove to be very effective, as its use has strengthened communication processes, competitiveness resilience, crisis prediction, and risk prevention (Stranjik et al., 2024). The analytical and predictive potentials of AI have also helped economists avoid potential crises by making their decisions agile and their adaptation strategies concise during situations of uncertainty (Asiabar et al., 2024).
Aljohani, (2023), also resulted in these research findings related to the use of predictive AI in decision-making processes, indicating that AI has enhanced decision-making capabilities and facilitated the anticipation of challenges and issues surrounding the application of such human decisions. Asiabar and Aliyev (2024) confirm this idea by advocating for the existence of a strong relationship between attempts to integrate the predictive potentials of AI and the improvement of human decisions, as well as the enhancement of their strategic directives, including the good governance of their resources in various fields, especially in strategic areas and critical cases. Yesufu and Alajlani (2025) confirm these ideas by presenting in their studies related to this research theme that large firms, especially Google and Walmart, have a good grasp of using AI predictive technologies and systems to improve their activities and ensure the agility and strategic effectiveness of their decisions in their fields of activity.
We observe that all these researchers emphasise the importance of integrating predictive AI into strategic decision-making processes and stress the role of these technologies and systems in improving decisions. However, we must not ignore the recommendations of other researchers such as Galaitsiet (2022), Leyer and Schneider (2021), on the importance of the human element in these processes to balance these uses and avoid undesirable deviations. It is in this process of argumentation that Goldfarb and Lindsey (2022) insist on the idea that predictive AI will only serve as a complementary element and support for human decisions and should never, according to them, take the place of humans or replace their presence in cases and situations of uncertainty. However, they all almost agree on the exceptional potential of predictive AI in helping states and decision-makers overcome the impacts of crises, manage their resources, and multiply their advantages in critical situations.
Theoretical framework & Methodology of the study
According to Rajagopalan (1997), the implementation of a strategy requires conciseness and rigor, with the decision-making process, as an essential element of the overall strategic vision, aligning and adapting to the principles of this strategy, reflecting its coherence and rigor, and its ability to guide in situations of uncertainty. In addition to these criteria related to the decision-making process and its source strategy, Ahmed (2014) adds that management sciences have also highlighted the “conditions” that the decision and the decision-making process should adopt to be rational and abstract, capable of encompassing the situation it addresses. In this regard, this author emphasizes the necessity of coherence and alignment between decisions and strategic visions, which would be the factors of influence and appeasement. However, according to Galavotti (2019), the criteria and conditions for the decision to be at the level of the targeted ambitions and objectives and always coherent and rational in such a critical situation risk being weak in the face of the enormous flows of information and data that weigh against human capacities aimed at the soundness and affinity of decisions.
For this reason, Karthikeayn (2024) believes that the integration of AI and the use of its data analysis and processing potentials to strengthen decision-making processes (in the market domain) in a world of constant transformations and in the face of traditional qualified processing frameworks that can no longer keep up with continuous changes, is a necessity, even an obligation. Yesufu and Alajlani (2025) still defend this idea, stating that the potentials of AI used in the field of markets have helped decision-makers optimize their time and resources. Moreover, according to these authors, they have led to organizational and operational efficiency, and to concise data analysis, thus helping to ensure very high rates in the rigor and conciseness of strategic decision-making. The fact that these authors still defend this vision is that they are influenced by the models adopted by Google and Walmart, which use these strategic management modalities to promote the conciseness and precision of their decisions. These methods of using AI in the field of strategic decision-making mark the beginning of a new era where AI adjusts human imprecision in the realm of strategic decisions and illuminates the paths for decision-makers to apply good governance and ensure the rationality of decision-makers in uncertain times (Murugesan and Kadalmani, 2023).
Asiabar (2024), and Horchuk (2024), agree that AI has the potential to make decisions better and make strategies more flexible, coherent, and useful. However, they also say that AI has some problems and raises a lot of questions about ethics, security, transparency, and other issues. Spangler (1991), and Galavotti (2019), also argue that the human element is important in strategic decision-making, saying that relying only on AI can cause inconsistencies, deviations, or even unwanted excesses. The authors keep saying that trying to figure out the possibilities of AI should never be seen as an attempt to replace human initiative. Instead, machines should always be present with human vision, vigilance, and agility, especially when things are uncertain. Right now, the possibilities of predictive AI look good because it can help make decisions better and faster during important times.
To achieve our research goal, we adopted a methodology that includes a systematic review, a case study, and the construction of a simulation scenario to profile unexpected interactions with the aim of improving the future integration process of predictive AI into decision-making processes in cases of uncertainty. That is why the literature review we conducted helped us understand the state of the art in the field of AI usage in the strategic decision-making sector. The research approach, especially the case study, helped us model hypothetical parallel scenarios and use the results of these analyses to predict the desired ideal situation, which can assist Moroccan decision-makers in similar situations.
To have a concise analysis of the data, the sources of this data must also be concise and rigorous. In this regard, we base our collection on reliable and academic sources that analyze and discuss the general idea of our research. Afterwards, we test in our study the effectiveness of predictive AI algorithms used in the market domain, in the strategic domain, and how these systems can either improve or, conversely, limit the decision-making effectiveness of Moroccan decision-makers in a crisis situation, referred to as “uncertainty in the market domain.”
During the simulation, we will use an analytical process based on the presentation of previous results and the demonstration of the advantages and disadvantages when applying predictive AI in similar processes, if they exist, or in the field of markets as a similar and relevant domain. This will help us develop solid and concise results around the use of predictive AI in strategic decisions according to the requirements of the Moroccan context. This analysis technique will help us achieve our research objective and provide a theoretical and epistemological basis for future researchers, including offering a planning and management guide for Moroccan decision-makers in such cases.
The research results
After the systematic consultations we conducted based on the selected literature, we found that predictive AI has indeed contributed to the improvement of strategic decision-making, especially in areas related to the economy, and those that have initiated these processes using predictive AI to ensure agility, efficiency, and precision in their decisions in times of slowdown and uncertainty. The systems and computing machines used during these processes, according to Karthikeyan (2024) and Valle-Cruz (2024), have demonstrated great capacity, enabling companies to anticipate factors and obstacles undermining their potential to navigate confidently through uncertainty and economic upheavals in global markets. The research results of Yesufu and Alajlani (2024) not only support the argumentative process defending the effectiveness of using predictive AI. However, they assert that the use of these predictive systems not only helps to avoid obstacles and unpredictable scenarios but also to seek opportunities and interests, especially by investing in and exploiting the situation, which may be out of sight for decision-makers in such circumstances.
We also conclude, alongside the defense of the interests that predictive AI offers to strategic decision-makers, that its use without standards organizing its massive integration into these processes invokes unnecessary implications that can ethically be unjust and affect the use of predictive AI in a transparent manner to improve a strategic decision at a given moment. So, we can say that our research findings align with previous writings discussing the use of predictive AI to improve strategic decisions, especially those of Youwangka, Gupta, and Kumar (2024), and also advocate for argumentation processes aimed at integrating predictive AI systems into sensitive strategic processes in case of security crises to increase the rationality, efficiency, and quality of decisions in such situations, aligning with the results of Csaszar (2024).
However, although we support the use of predictive AI to refine strategic decisions in cases of security uncertainty. We urge vigilance and caution regarding the implications of usage that do not generally respect the ethics of AI use and do not respect the rights and obligations related to its use. We also highlight the complementarity between AI and human tasks in these processes, emphasizing that human dependence on these emerging technologies can in no way replace human presence due to the specificities of human vision and consciousness in these cases and situations.
The discussion of our results
In terms of results, we believe that we have ensured the alignment of our results with our research objectives. In this regard, we conclude that the integration of the potentials of predictive AI systems into strategic decision-making processes during periods of uncertainty and security crises is certainly a very relevant and adequate approach for improving decision-making and ensuring the effectiveness of operational processes for Moroccan decision-makers in situations of insecurity and instability. This vision is based on several factors, including the optimization of human and financial resources, as well as the reduction of time during the analysis of collected data thanks to the potential of computation and prediction and the realization of scenarios. For this reason, the objective of the research aligns with the results we gathered during the collection and analysis of data regarding the argumentation on the positive contribution of predictive AI in improving strategic decision-making. Because according to our results, the predictive AI systems we evaluated will help political and strategic decision-makers just as they have helped economic decision-makers in uncertain market situations. Agility, stealth, and efficiency in strategic decision-making will be ensured through the integration of the predictive potentials of these systems into the strategic decision-making domain, helping Moroccan decision-makers improve their perceptions and forecasts of events or situations of uncertainty or instability.
Although the advantages of using predictive AI are numerous, the disadvantages are also many. This constitutes limitations in the research aimed at achieving its goal of reconfiguring decision-making parameters and improving them by utilizing the potential of collecting and analyzing real-time data streams. Several factors contribute to limiting the advantages of using predictive AI, including the lack of human resources in less technologically advanced countries, which can hinder the establishment and sober use of AI systems. There are also specificities related to law, ethics, trust, and transparency, all of which constitute barriers for organizations aiming to integrate the potentials of predictive AI into their decision-making processes (Samarah et al., 2024; Ekellem, 2024). Abuzaid and Harmash (2024) add other technical factors, such as the limitations in the infrastructure’s capacity to assimilate the technological potentials of AI systems, or the challenge of accurate or falsified data that circulates massively during a significant event, which can also limit the systems’ work and their ability to refine human decisions. Finally, the sociocultural context will also weigh on this process of adoption and integration, which will either facilitate integration or, conversely, accelerate adoption.
We ultimately recommend that, in order for decisions to be refined, the processes of integrating predictive AI should be adopted with the theoretical requirements related to ethics and law. Moreover, the frameworks related to algorithmic calculations and programming should also be refined to ensure precise and nuanced predictive outputs, far from algorithmic hallucinations. The presence of the human element is thus important to ensure that these systems are aligned with the requirements of human morality. Filling the gap regarding human resources is an obligation, and expanding the contribution of social science fields in this area aims to broaden the understanding of predictive AI in the context elements.
It is also imperative to provide a framework for the use and application for politicians and decision-makers who wish to integrate the potentials of predictive AI into their tasks and activities to refine their decisions in situations of uncertainty or crisis, where the respect for legal, moral, and ethical standards should be emphasized in these frameworks of use and application. This allows for reducing the transgressions that can be made against the principles of law in situations of uncertainty or crisis, and makes the activities of predictive AI and the related usage processes by decision-makers responsible, equitable, and institutionalized. Finally, it is also crucial to remove the issue of the purity of the data used in order to perfect the analytical process and avoid deviations caused by uncontrollable data flows.
Conclusion
To conclude, in our study we dedicated effort to examining the integration of predictive AI to improve decision-making processes and how, by hypothesis, it will contribute through its potentials for collecting, analysing, and evaluating risks, optimizing resources and time; and help in producing agile and effective decisions during periods of insecurity. The predictive potentials of AI also allow Moroccan decision-makers to clarify their visions of the risks surrounding and creating situations of uncertainty or crisis, and to chart their paths towards strategic clarity and the precision of their objectives. These potentials also enable the implementation of concrete and concise strategies and allow for predictive preparation against emerging threats and risks that undermine social security and stability.
On the other hand, our study highlights the presence of some drawbacks limiting the responsible use of predictive AI potentials to refine human decisions. The absence of human morality during the algorithmic learning of machines and in the calculation process risks exposing decision-making processes to issues of credibility and transparency, where AI recommendations in these cases can be considered as violations of fundamental rights if the models of the systems used are not evaluated and compared with systems used in similar fields. This can only be achievable through the continuous monitoring of the systems in question or by comparing their activities with similar systems to analyse the compliance of the responses and recommendations of these systems with moral standards. However, we insist on the complete presence of the human being in these processes to validate decisions, as human wisdom cannot currently be completely replaced by machine decisions.
We found during our analyses that the integration of AI potentials to refine human decisions requires, in addition to what has been mentioned, a complementarity and alignment with the principles and values of ethics and morality in order to ensure credibility, transparency, and accountability before the law. We insist on these recommendations because we believe that only these processes can ensure the perfect use of AI’s predictive potentials to improve human decisions and guarantee the strategic agility of decisions made in times of security uncertainty.
Indeed, this no longer marks the end for the improvement and reform of the processes for integrating predictive AI. However, strengthening the revival in the field of AI generally in Morocco is also linked to the enhancement of scientific and academic research to develop AI programs and systems capable of providing decision-makers and strategists with the best decisions during moments of security uncertainty. This also requires the development of technical methods and organizational and institutional means to evaluate these decision-making systems within a broader social and human context.
In this global geopolitical context and the emergence of conflict and political and security crises, the need for predictive AI to improve and refine human decisions in these unstable contexts will become essential and paramount for decision-makers manoeuvring in these spaces of instability and distrust. In this regard, the development of robust frameworks organizing the use and integration of AI in these processes will facilitate the task for our decision-makers and ensure the proper conduct of events and the stabilization of society during periods of security uncertainty or social upheaval.
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