Abstract:
Artificial Intelligence (AI) has been responsible for reshaping not only the global security architecture but also the national security architecture of individual actors i.e. states. AI has inevitably become a decisive force multiplier across military, intelligence and all other domains of strategic significance. Global South, situated in a complex geopolitical environment, faces multidimensional security challenges. To mitigate these contemporary challenges, integrating AI into national security framework is not only an opportunity but also a necessity, for actors within the region. This paper presents a critical overview of AI’s inescapable role in the national security of a country and examines its transformative potential, operational applications, institutional readiness, strategic limitations and the emerging nature of security dilemma, significantly posing a major security challenge for developing countries in the Global South, which are at a higher risk of being “passengers in flight” in the emerging Global AI Ecosystem. This paper further provides a comparative analysis of the degree of AI integration in their National Security Strategy, as compared to that of Global North. The paper, here, attempts to comprehend how a new “Algorithmic Empire” is evolving and how AI can be a key determinant in the emerging dynamics between the Global North and the Global South.
Artificial Intelligence (AI) has been responsible for reshaping not only the global security architecture but also the national security architecture of individual actors i.e. states. AI has inevitably become a decisive force multiplier across military, intelligence and all other domains of strategic significance. Global South, situated in a complex geopolitical environment, faces multidimensional security challenges. To mitigate these contemporary challenges, integrating AI into national security framework is not only an opportunity but also a necessity, for actors within the region. This paper presents a critical overview of AI’s inescapable role in the national security of a country and examines its transformative potential, operational applications, institutional readiness, strategic limitations and the emerging nature of security dilemma, significantly posing a major security challenge for developing countries in the Global South, which are at a higher risk of being “passengers in flight” in the emerging Global AI Ecosystem. This paper further provides a comparative analysis of the degree of AI integration in their National Security Strategy, as compared to that of Global North. The paper, here, attempts to comprehend how a new “Algorithmic Empire” is evolving and how AI can be a key determinant in the emerging dynamics between the Global North and the Global South.
Keywords: Artificial Intelligence, National Security, Strategic Force Multiplier, Data Sovereignty, Regulatory Mechanism, Global South
Introduction:
Artificial Intelligence (AI) has emerged as a critical element fundamentally transforming global and national security architectures. Major global powers have already witnessed AI acting as a potent force multiplier across key domains, including defence, intelligence operations, cybersecurity, and border management. They are using AI as a core technological enabler to maintain strategic edge in national security. The global AI in defence market size was valued at USD 12.55 billion last yeari and is expected to be worth around USD 178.14 billion by 2034ii.
The expansion of the global market is driven by several factors such as increased defense spending, technological advancements, demand for autonomous systems, cybersecurityiii needs and enhanced situational awareness as well. Global South, situated in a complex geopolitical environment, faces multidimensional security challenges.
To mitigate the contemporary challenges, integrating AI into national security framework is not only an opportunity but also a necessity, for actors within the region. This paper presents a critical overview of AI’s inescapable role in the national security of a country and examines its transformative potential, operational applications, institutional readiness, strategic limitations and the emerging nature of security dilemma, significantly posing a major security challenge for developing countries in the Global South region, which are at a higher risk of being “passengers in flight” in the emerging Global AI Ecosystem.
This paper critically evaluates the impact of AI on defense modernization, autonomous systems, surveillance, intelligence fusion, cyber defense and border security management of actors within the region. To provide a holistic view, an attempt is made to enlist the doctrinal changes, essential for the Global South countries, to transform their national security architectures. The study further focuses on identifying the capability gaps, data-infrastructure constraints, ethical concerns, data sovereignty concerns and the interaction between Civil-Military Domain of the developing countries, with respect to AI adoption, specifically for accommodating the same alongside existing developmental priorities. In the last section, a few policy recommendations are provided for strengthening national security frameworks of the Global South actors, providing a robust regulatory mechanism and accelerating their indigenous innovation, in the digital age.
How AI Can Act as A Strategic Force Multiplier?
AI serves as a powerful and effective force multiplier, significantly augmenting operational capabilities and efficiency across multiple security sectors. The applications of AI provide substantial benefits that extend far beyond conventional military domains, creating asymmetric advantages and boosting national resilience.
• Enhanced Intelligence, Surveillance, and Reconnaissance (ISR):
One of the primary ways AI acts as a force multiplier is through the dramatic enhancement of Intelligence, Surveillance, and Reconnaissance (ISR) capabilities. AI systems possess the ability to rapidly process vast quantities of heterogeneous data derived from diverse sources, such as satellites, drones (SIGNIT and GEOINT) and social media feeds, performing this analysis faster, more efficiently and accurately than human analysts. This expedited processing capability delivers real-time battlefield awareness and significantly improves the identification of threats. The tangible impact of this application is demonstrated by specific instances, such as the Indian Army’s “Operation Sindoor,” which successfully leveraged AI-based tools for sophisticated enhanced surveillance and precision targetingiv.
• Asymmetric Warfare and Predictive Capabilities:
The adoption of AI-enabled technologies provides crucial strategic advantages in scenarios of asymmetric warfare. Developing nations and even non-state actors can deploy inexpensive, yet highly effective, AI-enabled tools, such as kamikaze drones, offering a strategic counter against adversaries who may possess conventionally superior military power. Beyond the tactical level, AI contributes substantially to strategic planning through predictive analytics and decision support systems. AI allows for the creation of predictive modelling capabilities designed to anticipate patterns of attacks, forecast the movements of adversaries and optimize the deployment of vital resources. This results in faster, data-driven decisions crucial for effective security responses.
• Cybersecurity and Counterterrorism
In the vital areas of cybersecurity and counterterrorism, AI capabilities are indispensable. AI aids counterterrorism efforts by identifying suspicious financial transactions, detecting irregular communication patterns, and analysing extremist content. Furthermore, AI strengthens cyber defence posture by automating the detection of vulnerabilities and providing real-time threat response systems.
• Logistics:
AI-led predictive maintenance tools such as IBM Maximo Predict, Microsoft Azure Iot Predictive Maintenance or C3 AI Reliability (by US Department of Defense) help forecast equipment failures before they happen and ensure higher level of operational readinessv improves the efficiency of supply chains, particularly in contested or challenging environments. For training purposes, AI facilitates the creation of highly realistic, personalized training simulations utilizing virtual and augmented reality. This technological advancement in training is particularly valuable for nations that operate with limited financial and material resources.
• Civilian Applications and National Resilience
AI applications in the Global South extend beyond direct military and strategic utility, playing a vital role in civilian sectors which ultimately bolster national resilience and stability.
AI is actively being applied to address pressing developmental challenges within critical societal sectors like healthcare, agriculture, and education. For example, the World Food Program’s SKAI model utilizes AI to accurately assess disaster damage, substantially speeding up emergency response operationsvi. These civilian applications reinforce the overall national fabric, contributing indirectly to security outcomes.
Strategic Limitations to Integration of AI as A Strategic Force Multiplier
Despite the overwhelming strategic benefits, the path to successful AI integration for national security in the Global South seems fraught with significant structural and conceptual challenges. The inherent complexity of geopolitical and developmental hurdles mandates AI integration, yet the region faces a major gap as compared to the Global North in technology, research and development (R&D) capacity as well as in strategic framework developmentvii.
A core challenge is the widespread lack of institutional and infrastructural readiness across many developing countries. Many nations lack robust data infrastructure, suffer from a shortage of a skilled workforce capable of developing and managing advanced AI systems and have not yet established coordinated civil-military frameworks necessary for unified strategic development. Furthermore, the absence of robust AI governance models and a heavy reliance on foreign technology providers severely limits indigenous capacity and security autonomy. These deficiencies increase the risk that the Global South actors may become “passengers in flight” in the global AI ecosystem, who are only passively accepting outcomes of AI innovation and regulation rather than shaping them.
The Global South faces a range of multidimensional security threats, including internal conflicts, persistent border tensions, terrorism and increasing cyber vulnerabilities. In this environment, the pressure to adopt AI technologies is intense, leading to a phenomenon that can be described as the “Fear of Missing Out” (FOMO). This inherent urge to rapidly catch up to the AI revolution often bypasses a thorough evaluation of the cost-benefit analysis and the specific suitability of adopted AI policies for their own peculiar national interests. The focus, therefore, must shift from mere emulation of the Global North’s policies to strategic regulation aligned with national priorities.
The global asymmetry in AI development means that the Global South frequently bears significant risks associated with the un-audited or potentially biased deployment of AI systems. When core technologies like Machine Learning, Deep Learning, Natural Language Processing, Computer Vision and Generative AI Models especially LLMsviii are developed externally, without conducting a proper need-gap analysis, the resultant systems can introduce biases that undermine fairness, efficiency, and security operations within the adopting nation, posing a further dissipation of resources when the Global South already opt for parsimonious developmental initiatives.
Recommendations For Enhancing Digital Sovereignty and Resilience
To navigate the complex challenges and mitigate the risks associated with the Algorithmic Empireix, the Global South requires a balanced, strategic and cooperative approach, prioritizing sovereignty and internal development. One of the key challenges to national sovereignty comes from the non-state actors. with the emergence of Cryptocurrency, a new mode of terror funding has emerged where a covert means to move funds across the borders from solicited donations is used posing a challenge to the use of conventional monitoring and tracking mechanisms used by a country’s security forces. AI-powered Blockchain Intelligence Toolsx can facilitate the authorities to map suspicious crypto transactions and directly linked crypto wallets used for carrying out illicit transborder activities.
• Fostering Indigenous Capacity and Infrastructure
A crucial step is fostering indigenous capacity through Government Funded Multimodal Large Language Model (LLM) Initiatives, for example, India’s BharatGen . Developing localized models tailored to regional languages and contexts is essential for reducing reliance on foreign foundational models.
Equally important is developing Digital Public Infrastructure (DPI) to serve as a global template suitable to the needs of the developing economies and their limited capacity for developing state-of-the-art AI-driven infrastructure and investment in R&D of defence technologies, from scratch. This investment ensures that essential data and digital services are built on sovereign, accessible foundations.
Additionally, embedding Techno-legal compliance directly into the AI development lifecycle (MLOpsxii) is necessary. An act similar to that of adopted within EU’s AI Actxiii where Policy-as-a-Code (PaC) directly supports EU regulations, a multilateral cooperative mechanism In the form of a risk management system, that fits the conditions within the Global South AI Adoption framework, can be developed for identifying high-risk AI systems.
This ensures that ethical considerations, governance standards and legal requirements are addressed proactively during development, rather than retrospectively. Automated tools and processes should be implemented for labour-intensive tasks within the security apparatus to maximize efficiency and resource allocation.
• Governance, Cooperation and Regulation
The Global South must move promptly to address the regulatory vacuum that currently exists. Instead of traditional, centralized models, establishing a polycentric Governance Commons in the digital domain will not only ensure decentralisation of AI capabilities but also build a more democratic international order in this domain. This decentralized, networked model is designed to facilitate global cooperation on AI standards and practices without compromising individual national sovereignty for any country, developed or underdeveloped.
The Global South must move promptly to address the regulatory vacuum that currently exists. Instead of traditional, centralized models, establishing a polycentric Governance Commons in the digital domain will not only ensure decentralisation of AI capabilities but also build a more democratic international order in this domain. This decentralized, networked model is designed to facilitate global cooperation on AI standards and practices without compromising individual national sovereignty for any country, developed or underdeveloped.
1. Establishing robust standards for data sovereignty.
2. Securing critical AI supply chains.
3. Developing cutting-edge cyber security and defence collaborations.
4. Creating regulatory frameworks specifically addressing dual-use AI technologies.
Way Ahead:
The Global South stands at a critical juncture where bilateral and multilateral engagement, characterized by high-stakes and nuanced relationship building, is the need of the hour. There is a dire need for a balanced and well-curated approach to AI adoption within the region, moving away from uncritical emulation of existing frameworks and towards focused regulation.
A robust AI policy framework must be implemented, consciously combining four core pillars viz., Innovation, Regulation, Sovereignty, and Cooperation. By focusing on filling the regulatory vacuum and strategically investing in sovereign technological foundations like national LLMs and DPI, the Global South can leverage AI’s force multiplying effects while mitigating the profound risks posed by the rising Algorithmic Empire and effectively manoeuvre its strategic interests within the emerging AI-led global order. Not to forget, the failure to adopt this balanced and strategic approach poses an undeniable risk of forfeiting their strategic autonomy and locking developing nations into a perpetual state of technological dependency, hence making the future security and stability of the Global South depend critically on transforming AI from a source of geopolitical vulnerability into a pillar of national resilience.
Endnotes
i. Google. (n.d.). What is MLOps? | google cloud. Google. https://cloud.google.com/discover/what-is-mlops#
ii. Ibid
iii. Cybersecurity market size, share, Analysis: Global Report 2032. Cybersecurity Market Size, Share, Analysis | Global Report 2032. (2025, December 1). https://www.fortunebusinessinsights.com/industry-reports/cyber-security-market-101165#:~:text=CYBERSECURITY%20MARKET%20SIZE%20AND%20FUTURE%20OUTLOOK&text=The%20global%20cybersecurity%20market%20size,14.40%25%20during%20the%20forecast%20period
iv. Philip, S. A. (2025, October 7). Op Sindoor is India’s first AI-enabled operation. how “heavy use” of Modern Tech by Army played out. ThePrint. https://theprint.in/defence/op-sindoor-is-indias-first-ai-enabled-operation-how-heavy-use-of-modern-tech-by-army-played-out/2758797/#:~:text=Representational%20image:%20File%20photo%20of,military%20movement%2C%20enabling%20pinpoint%20targeting
v. Nguyen, N. (2025, September 10). Ai in military: Top use cases you need to know. SmartDev. https://smartdev.com/ai-use-cases-in-military/#:~:text=2.,well%2Dequipped%20for%20their%20missions
vi. Baha, A., & Morrell, H. (2023, July 3). Revolutionizing disaster response with Skai | by WFP Innovation Accelerator | Medium. MEDIUM. https://wfpinnovation.medium.com/revolutionizing-disaster-response-with-skai-1ae9e02e87e5
vii. Yu, D., Gupta, A., & Rosenfeld, H. (2023, January 16). The “Ai divide” between the Global North and Global South. World Economic Forum. https://www.weforum.org/stories/2023/01/davos23-ai-divide-global-north-global-south/
viii. Takyar, A. (2025, October 16). A guide to key AI Technologies. LeewayHertz. https://www.leewayhertz.com/key-ai-technologies/
ix. Appleton, B. (2025). Algorithmic empire and the new digital colonialism: The legal struggle for technological self-determination in the age of ai. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.5389292
x. Ziv, G. B. (2025, October 17). AI and National Security: Promise and peril. Cognyte. https://www.cognyte.com/blog/ai-national-security/#:~:text=It’s%20rapidly%20revolutionizing%20the%20way,insights%20and%20make%20smarter%20decisions
xi. Ministry of Electronics and Information Technology, Government of India. (2024, October 1). BharatGen: World’s first government-funded multimodal LLM Initiative launched in India. IndiaAI. https://indiaai.gov.in/article/bharatgen-world-s-first-government-funded-multimodal-llm-initiative-launched-in-india
xii. Google. (n.d.-a). What is MLOps? | google cloud. Google. https://cloud.google.com/discover/what-is-mlops
xiii. Article 9: Risk Management System. EU Artificial Intelligence Act. (n.d.). https://artificialintelligenceact.eu/article/9/#:~:text=Summary,shall%20comprise%20the%20following%20steps
