Through fiscal policy, the government can influence businesses and individuals in order to regulate their behaviour. The research used panel data from all 27 EU countries covering the period 2008–2020 to investigate the impact of direct taxation on economic growth at the level of two main clusters of countries concerning fiscal efficiency. Therefore, the analysis employed cluster methods to classify the main EU countries in both groups of countries with a high level of fiscal efficiency and those with a rather limited level of fiscal efficiency. The study employs fixed effect models and dynamic GMM methods to investigate the effect of direct taxation components (personal and corporate income taxes) on economic growth. The analysis also considers the informal economy’s role in relation to the official economy. The empirical results revealed that corporate income taxes significantly negatively impact economic growth for both clusters of high- and limited fiscal efficiency countries. Additionally, personal income tax was associated with lower economic growth for countries in the limited fiscal efficiency group. Thus, from the perspective of policymakers, lowering direct taxation can increase disposable income, stimulate consumption and economic growth, encourage investment leading to job creation, increase competitiveness, and reduce tax evasion and avoidance, thereby leading to a more efficient tax system.

Artificial Intelligence has become the light-motif of the much-cited technological revolution, which will change society as we know it at a paradigmatic level. The Security and Law Enforcement Sector is one of the preferred fields for integrating these disruptive technologies. In this study, I will highlight the main levels of integration of artificial intelligence (AI) into the security work toolkit, whether we are talking about detection, control, response or decision-making processes. Equally, the galloping dynamics of these technologies raise a series of challenges from the perspective of the fundamental rights and freedoms of the individual. Thus, advantages such as reducing human errors or increasing predictive capabilities are countered by challenges/risks such as algorithmic bias or excessive surveillance. The levels of autonomy specific to AI-based systems are also considered, in order to increase the efficiency of the collaborative human-machine approach. Finally, the article highlights the need to build a regulatory framework that balances the efforts to innovate and optimize security systems with the imperative need to respect fundamental individual rights and freedoms. As AI becomes increasingly present in the security field, careful regulation and oversight of its use are essential to prevent abuses and guarantee responsible and transparent use.

Artificial intelligence has introduced a qualitatively new layer of risk to cybersecurity in the financial sector, and the consequences reach well past the operational boundaries of any single institution. This paper looks at how exposed the emerging economies of the EU (Romania, Bulgaria, Poland, and Croatia in particular) are to AI-driven cyber threats aimed at financial systems. Working with secondary data from ENISA, the European Central Bank, Europol, and the IMF, the study traces the shifting threat landscape (deepfake fraud, AI-powered phishing, automated exploitation of software vulnerabilities) and maps it against indicators of digital maturity, financial depth, and institutional cyber readiness in the selected countries. The methodology blends documentary analysis with descriptive statistics, bivariate correlations, and a purpose-built composite index of cyber-financial vulnerability. What emerges is that the EU’s converging economies face a disproportionate risk profile: lower cybersecurity spending relative to GDP, heavier reliance on imported ICT services, and weaker institutional capacity for rapid incident response all contribute. These findings are discussed against the backdrop of DORA and NIS2, and the paper argues that fiscal exposure to AI-enabled cyber risk ought to be woven more deliberately into the macroeconomic surveillance frameworks that govern economic convergence in the EU.