Following a protracted international invasion of Afghanistan, the Taliban administration took control in 2021 but chose neither broad political legitimacy nor a democratic institutional system. Their path was slow at first due to ineffective ministries, an uncertain economy, and a lack of international recognition. However, in spite of these institutional shortcomings, the administration has successfully consolidated power at a startling rate. This consolidation cannot be explained solely through military means, ideological supremacy, or social agreement. Rather, it signals a more subtle but significant shift i.e. the increasing use of digital technology, especially artificial intelligence (AI), to control, monitor, and regulate society (Feldstein, 2019; Crawford, 2021).

In Taliban controlled Afghanistan, AI does not simply enhance the governance capacity, but it works as a compensation for the government. The expression of AI authority through surveillance, data restrictions, and algorithms does not require a strong political institution or popular consent. This poses a significant threat to traditional security studies. Conventional frameworks, such as the Copenhagen school of thought anchored by Barry Buzan's seminal five-sector model of security (military, political, economic, societal, and environmental), find it difficult to encompass a type of authority that functions through automation, prediction, and data rather than force, legitimacy, or identity (Buzan, 1991; Buzan et al., 1998). Artificial intelligence constitutes a different dimension of security, one that rewrites power by reshaping how threats are identified, how populations are governed, and how resistance is neutralized. Afghanistan under Taliban rule offers a stark empirical illustration of this shift.

Barry Buzan made a significant contribution to security studies by expanding the definition of security outside of the military. His concept encapsulated the multifaceted nature of survival in the contemporary state system by identifying political instability, economic hardship, environmental crises, and societal disintegration as existential dangers (Buzan, 1991). Buzan's approach, however, rests on this presumption that power is exercised by distinct and identifiable individuals and institutions, such as governments, markets, social groups, or militaries, within each sector. AI challenges this presumption because it shapes perceptions of security, risk assessment, and response across all domains (Amoore, 2013; Rouvroy & Berns, 2013). The situation in Afghanistan, during which the Taliban ruled in a setting with limited institutional capacity and contentious legitimacy, makes this quite clear. Instead of serving as an additional tool, AI often replaces governance.

Digital tools are now essential to daily governance. Tens of thousands of CCTV cameras have reportedly been installed throughout Kabul and other major cities by the Taliban since 2021. Many of these cameras are part of centralized monitoring systems that can track behavior in real time (Amnesty International, 2023; Afghanistan International, 2024). These developments coincide with intentional limitations on public connectivity, such as prohibitions on high-speed internet services, localized Wi-Fi shutdowns, and sporadic nationwide disruptions to mobile data—measures that are widely recognized to restrict social coordination and political communication but are officially justified on moral or security grounds (Reuters, 2024; Freedom House, 2024). Altogether, this model illustrates a unique model of control. Rather than relying on a physical mode of coercion, this government is relying on its algorithmic capacity to control digital space.

Large-scale conventional conflict no longer characterizes Afghanistan today, but the logic of security has not changed. Rather, anticipatory control, a defining feature of algorithmic governance, has replaced reactive coercion (Amoore & de Goede, 2008; Amoore, 2013). Widespread surveillance systems suggest a system of governance that places more emphasis on tracking presence, conduct, and movement than on using force all the time. This transformation from conventional security threat to digital dissent cannot be analyzed within Barry Buzan’s security dimension. The risk of dissent, deviation, or disruption now poses a greater threat than an opposing armed force. The Taliban can now anticipate and handle such scenarios before they arise because of AI, which changes security from a defensive response to an anticipatory administration (Brayne, 2020). Control is achieved by making violence unnecessary rather than by reacting to it.

Political power is also reshaped by this anticipatory logic. According to Buzan, political security is about the legitimacy and stability of the ruling class. Although legitimacy is still poor in Afghanistan, AI diminishes its significance. Political authority is no longer dependent on people’s participation, persuasion, or ideological alignment when obedience can be gained through data control and surveillance. Political authority gives way to technical administration, where governance is more subdued, less obvious, and harder to challenge (Rouvroy & Berns, 2013). This change is further demonstrated by the Taliban's approach to internet connectivity. Although censorship, blackouts, and internet limitations are sometimes presented as cultural or moral measures, their security purpose is obvious. The dictatorship restricts collective political action by restricting access to information and communication networks (Morozov, 2011; Human Rights Watch, 2023). By permitting selective monitoring as opposed to total repression, AI strengthens this control. Political insecurity is managed not through mass arrests or overt violence, but through the continuous regulation of visibility. This calls into question a fundamental tenet of conventional political security, which holds that risks arise from institutional failure or organized opposition. Threats are preempted, segmented, and personalized under algorithmic control. The focus of politics shifts from conflict to conformity. Though it gets more difficult to organize, perceive, and neutralize, resistance does not vanish.

Digital restrictions in Afghanistan have serious economic repercussions, especially for young people and women who depend on internet platforms for international connections, education, and income (Reuters, 2024). In Buzan's view, this represents economic uncertainty, but AI brings about a more profound change. Access to data infrastructures and digital visibility, rather than just markets and labor, is becoming more  important for economic survival. People who are not able to participate in such scenarios are not only lacking an economic tool for survival, but being digitally erased. AI-powered governance erases the digital footprint by identifying which actions should be public and which should be hidden (Crawford, 2021). As a result, economic insecurity and digital marginalization are becoming inseparable from each other. There are equally significant societal ramifications. Buzan's theory of societal security is centered on the preservation of social cohesiveness, culture, and identity. The threat of ideological enforcement is evident in Afghanistan. But AI offers a more subdued level of control. Constant monitoring encourages self-censorship and conformity, changing behavior long before overt repression is necessary (Foucault, 2007). In addition to ideological constraints, algorithms also discipline identity.

Artificial Intelligence as an additional dimension of security

These dynamics reveal why AI cannot be considered one of the security dimensions given by Buzan and why it should be studied in a separate manner. Unlike military, political, economic, societal, or environmental security, AI poses a distinct form of power that deals with data, algorithms, and logic. Rather than responding to a direct threat, AI is enabling the government to perceive what can be a threat for them. It helps to recognise the suspicious or risky behaviour that can be harmful for the governance or their ideology. Because of its ability to influence how threats are perceived, AI has what Amoore (2013) refers to as epistemic authority, which puts it analytically outside of Buzan's initial sectoral framework. This change from material protection to algorithmic supervision of security decision-making itself can be captured by conceptualising AI as an extra dimension of security. AI cannot directly maintain political security, economic security, societal security, control environmental security, or military security. Instead, it affects every one of these sectors that interpret the domain in one way or another. In this way, rather than just governing security results, AI also controls the conditions in which security practices are possible. The AI component is especially important in the Afghan context because of the country's political division, inadequate institutional framework, and isolation from the rest of the world. Since the other components of administration such as bureaucratic depth, intelligence capability, and international legitimacy are in some ways deficient, the Taliban regime is becoming more and more reliant on AI for governance. They also don't fully innovate the AI tools utilized for digital spying. The international community provided some of the equipment, which was left over from the previous administration. This development deviated from Barry Buzan's classic securitization theory. Instead of coming from public discussions, political choices are made from data collection. Individuals can face restrictions or be excluded from any kinds of activities just on the basis of suspicion. Normally in other countries, AI is being used in enhancing security to the citizens of that particular country. But in a country like Afghanistan, permanent surveillance and anticipatory control are used to enhance governmental control over the life of Afghans.

The sectoral paradigm developed by Barry Buzan is still essential for comprehending how security has expanded beyond military threats. But in the digital age, the Afghan instance shows its limitations. Artificial intelligence does more than just change political power, economic access, military strategy, social standards, and environmental concerns. It restructures the framework that governs the exercise of power. AI rewrites authority in Taliban-ruled Afghanistan by facilitating government without institutions, security without visibility, and control without legitimacy. Thus, acknowledging AI as an extra layer of security is an analytical requirement rather than a theoretically abstract step. Without it, security studies run the risk of missing one of the most significant changes in modern power: the move from rule by consent or coercion to rule by algorithm.

Dr. Rajarrshhi Chakrabborttyi is an Assistant Professor at Mody University of Science and Technology. His academic interests include foreign policy and strategic studies, with a focus on contemporary geopolitical trends and evolving strategic landscapes.

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