In an era where artificial intelligence systems process billions of personal data points daily, questions about digital sovereignty and data ownership have moved from theoretical discussions to urgent policy debates. Maxim Ageev, co-founder and CEO of De Novo, a prominent technology company, has raised alarming concerns about what he terms “techno-fascism” — the potential for AI systems and the corporations controlling them to wield unprecedented power over individuals and nations through data control. His warnings come at a time when governments worldwide are scrambling to establish frameworks for AI governance while tech giants continue to amass vast repositories of personal information.
The concept of techno-fascism, as Ageev describes it, represents a new form of authoritarian control enabled by technology rather than traditional political structures. Unlike historical fascism, which relied on state apparatus and physical coercion, this digital variant operates through algorithmic manipulation, data harvesting, and the concentration of technological capabilities in the hands of a few powerful entities. The theory suggests that whoever controls the data and the AI systems that interpret it effectively controls the population — not through force, but through influence, prediction, and the subtle shaping of behavior and choices.
The Personal Data Arms Race
The scale of personal data collection has reached staggering proportions in recent years. According to various industry estimates, the average person generates approximately 1.7 megabytes of data every second, encompassing everything from location information and purchasing habits to health metrics and social interactions. This data, when processed by sophisticated AI systems, can predict behavior, influence decisions, and create detailed psychological profiles of individuals. Ageev argues that this capability represents both an economic asset and a potential weapon, depending on who wields it and for what purpose. The implications extend beyond individual privacy concerns to questions of national security and economic competitiveness.
The rise of economic nationalism in the technology sector has further complicated the landscape. Countries increasingly view data as a strategic resource akin to oil or minerals, leading to policies that restrict cross-border data flows and require local storage of citizen information. The European Union’s General Data Protection Regulation, China’s Cybersecurity Law, and similar legislation in dozens of other countries reflect a growing recognition that data sovereignty is inseparable from national sovereignty. This fragmentation of the global digital ecosystem creates both opportunities and challenges for businesses operating across borders while raising fundamental questions about who should have access to personal information and under what conditions.
AI Systems and the Future of Control
Ageev’s concerns about AI extend beyond simple privacy violations to more fundamental issues of autonomy and self-determination. Modern machine learning systems can identify patterns in data that humans cannot perceive, making predictions about health outcomes, creditworthiness, criminal behavior, and countless other aspects of life. When these systems are deployed by governments or corporations without adequate oversight, they can entrench biases, restrict opportunities, and create feedback loops that prove nearly impossible to escape. The opacity of many AI systems — often described as “black boxes” even by their creators — makes accountability difficult and appeals nearly impossible.
Historical parallels, while imperfect, offer some guidance for understanding the current moment. The industrial revolution concentrated economic power in factory owners and financiers, leading to social upheavals and eventually new forms of regulation and worker protection. The information revolution may require similar adaptations, though the intangible nature of data makes traditional regulatory approaches less effective. Some experts advocate for treating personal data as a form of property that individuals can license or sell, while others argue for treating it as an inalienable right that cannot be traded away. The debate remains unresolved, with significant implications for the future development of AI systems and the digital economy.
Navigating the Path Forward
As societies grapple with these challenges, several approaches have emerged. Technical solutions such as differential privacy, federated learning, and homomorphic encryption offer ways to extract value from data while limiting exposure of individual information. Regulatory frameworks continue to evolve, with some jurisdictions experimenting with algorithmic auditing requirements and mandatory impact assessments for AI systems. Civil society organizations have mobilized to advocate for digital rights, while some technology companies have begun to position themselves as privacy-focused alternatives to data-hungry incumbents. The outcome of these competing forces will shape not only the technology industry but the fundamental relationship between individuals, corporations, and governments in the digital age.
Expert Opinion: The convergence of AI capabilities and massive data collection represents perhaps the most significant shift in power dynamics since the industrial revolution. Organizations and governments that establish robust data governance frameworks now will be better positioned to protect their citizens and maintain competitive advantages. The next decade will likely see increased regulatory intervention and potentially the emergence of new international norms around data sovereignty and AI accountability.
