Since the early 2000s NATO countries’ defence expenditure has increasingly been driven by hardware procurement, while public debate has largely overlooked the implied social trade-offs. In the wake of Russia’s full-scale invasion of Ukraine, broadcast and print media have amplified calls for accelerated ‘modernisation’ through increased military spending, even as scrutiny of procurement priorities and their beneficiaries remains limited. Beyond the battlefield, war-driven procurement and the profits it generates fuel emergency rationalities and enable the adoption of military technologies into urban governance. While the media frames their products as technical solutions to risk and disorder, firms like Palantir, Altia, Pimloc, DataWalk, and Milestone power AI-enabled surveillance systems and predictive policing tools leverage the potential to mine data from physical and digital public spaces to feed their battlefield-grade tech. Drawing on evidence from Bulgaria this talk tests a structural hypothesis grounded in political economy: that the normalisation of militarisation is patterned by market-mediated corporate ties (ownership relations, board interlocks, and intermediary firms) linking arms producers to the media ecosystem thereby helping to manufacture consent for security expansion across scales, from national defence budgets to urban control infrastructures.
To move beyond simplistic ‘who owns whom’ claims, a measure of control distance is introduced to capture how influence is transitively consolidated across chains of intermediaries, including shell firms. Formal analysis identifies a distinctive ‘bow-tie’ architecture: military firms occupy the controlling pole, media firms the target pole, and dense intermediary clusters function as the knot through which influence is channelled and obscured. These findings translate into a concrete policy argument: the securitisation of urban and peace-time governance relies on this kind of corporate-media infrastructure to manufacture consent and to stabilise militarised common-sense. Quantitative network methods, used critically, can therefore help shift securitisation from a technical object to a measurable political-economic formation.
Fabio Ashtar is a PhD researcher in Statistics at the University of Ljubljana using network analysis, machine learning, and AI to study international trade, applied political economy, and economic policy.