FACTS AND NEWS SUMMARY ON 2026.03.16

The common denominator of all described phenomena is the rapid “internalization” of artificial intelligence within key institutions of power and control – from internal politics and recruitment processes, through the international security system, to military structures. AI ceases to be a technological curiosity and becomes a tool of real power: it defines who gets a job, how nuclear arms are monitored, how armies conduct operations, and how political elites organize themselves against new threats. This shift from the “consumer market” to “systemic infrastructure” has direct and indirect consequences for the labor market and socio-financial security.

AI in Recruitment and Inequality

On the labor market, AI simultaneously appears as a filter, judge, and surveillance tool. The development of recruitment systems based on algorithms means that the first “supervisor” evaluating a candidate will increasingly be a model, not a human. The ability to “fit” the requirements of machine screening (keywords, format, structure) is becoming a new fundamental competence. Inequalities are growing: individuals with greater technological awareness and access to advisory services will cope better in this environment, while less privileged groups may be systemically weeded out. At the same time, demand is rising for specialists capable of designing, auditing, and controlling these systems – but this is a relatively narrow group in relation to the total workforce.

Erosion of Stability in Strategic Sectors

Employment stability is eroding because AI is entering areas previously considered “resistant” – strategic analytics, defense, arms control, administration. When the Pentagon pushes for access to the most powerful models on classified systems, and supervision of nuclear arsenals is considered based on satellites and algorithms, the signal to states and corporations is clear: automation may also encompass tasks of the highest responsibility. This opens the way to reducing staff in analytical, intelligence, and some expert functions – even if positions are formally maintained, their scope of tasks and decision-making power may be significantly reduced.

Professions Most at Risk

Among the group of professions most at risk are: lower and mid-level HR specialists (routine screening, CV selection), administrative and back-office employees whose tasks can be automated with analytical tools, as well as rank-and-file data and intelligence analysts whose work consists of repetitive information interpretation. In the longer horizon, this group will be joined by some consultants, advisors, and public policy experts if institutions start relying on recommendation systems to generate scenarios and recommendations. Paradoxically, the importance of professions related to regulation, ethics, and AI supervision is growing, but this will not compensate for the loss of routine and mid-level work.

Threats to Financial Security

Employees’ financial security is indirectly undermined by the lack of transparency and accountability in how AI is used. If algorithms – in recruitment, but also in security systems or politics – operate as “black boxes”, it is harder to question decisions leading to exclusion from the labor market, and the risk of systemic errors spills over onto entire social groups. In the case of flawed candidate assessments or biased models, the result can be long-term gaps in employment, inadequacy of wages to competencies, and greater sensitivity to economic fluctuations.

Two-Track Unemployment Risk

The risk of unemployment runs on two tracks. First, in professions exposed to automation, a “silent” crowding out may occur – not necessarily mass layoffs, but a lack of new positions and natural extinction of roles. Second, at the macro level, if Europe – as Macron warns – does not build its own position in the AI race, it may lose technological competition with the USA and China, translating into slower growth, fewer high-quality jobs, and pressure to lower labor costs. In such a scenario, automation will mainly serve to cut expenses rather than create new economic sectors, increasing structural unemployment within less competitive economies.