Governance and Economic Policymaking in the Artificial Intelligence Era

Introduction
The rapid evolution of artificial intelligence (AI) and digital technologies has fundamentally transformed governance structures, economic systems, and mechanisms of social control. As traditional state-centric models give way to networked governance, power becomes increasingly distributed among states, multinational corporations, transnational organizations, and digital platforms. This transformation reflects key theoretical perspectives from International Political Economy (IPE), Network Governance, Foucauldian Discourse Analysis, World-Systems Theory, and AI Governance.
AI now serves as a critical driver in reshaping economic and geopolitical landscapes. Policymakers, financial institutions, and technology firms increasingly rely on AI-driven data analytics for decision-making, economic forecasting, and policy implementation. These developments extend beyond purely economic considerations, significantly impacting political legitimacy, digital surveillance practices, security paradigms, and the shaping of public discourse.
This study examines the defining characteristics of governance and economic policymaking in the AI era, guided by the hypothesis that contemporary governance models depend on four key factors: process transparency, multilateral cooperation, expanding consumerism, and the production of legitimizing narratives. The research employs a network society and digital economy framework to analyze the complex interactions between AI systems, governance structures, and global economic dynamics.
 
Methodology
This study adopts a descriptive-analytical methodology that combines qualitative content analysis with secondary data examination, drawing on peer-reviewed academic literature, policy reports, economic analyses, and institutional publications from organizations including the World Bank, IMF, and OECD to systematically evaluate AI's role in transforming economic governance and policymaking through critical discourse evaluation and pattern analysis of emerging AI-driven approaches across different political and economic systems.
 
Results and Discussion
The findings reveal a fundamental decline of the Westphalian state model, replaced by networked governance structures where AI facilitates power decentralization, corroborating Castells' (2009) network society theory. This shift redistributes governance authority among corporations, AI platforms, and supranational entities, diminishing traditional state monopolies. AI transforms decision-making through predictive analytics and automated policymaking, reducing bureaucratic intervention and enabling decentralized, algorithmic public administration.
Crucially, the research identifies the rise of cognitive control via AI surveillance, reflecting Foucault's (1977) power-knowledge paradigm where influence operates through discourse control rather than coercion – exemplified by digital corporations (Google, Meta, Amazon) using predictive AI to shape behavior and public sentiment.
Shoshana Zuboff’s (2019) theory of surveillance capitalism supports this argument, emphasizing how AI-driven platforms commodify user data to influence individual and collective decision-making. This raises concerns about algorithmic bias, privacy violations, and the monopolization of digital public spheres.
AI intensifies global economic stratification, reinforcing the core-periphery divide within Wallerstein’s World-Systems Theory (2004). The study reveals that countries in the core (e.g., the U.S., China, EU nations) dominate AI research, innovation, and data control, while semi-periphery and periphery nations remain dependent on these technological advancements, exacerbating digital colonialism.
AI has fundamentally altered economic policymaking and financial governance, moving towards data-driven decision-making models. This paradigm shift aligns with Brynjolfsson & McAfee’s AI Governance Theory (2014), emphasizing the role of AI in augmenting policy decisions, enhancing economic efficiency, and restructuring global financial markets.The findings suggest that AI accelerates geopolitical rivalries and regional conflicts, particularly in the Middle East. AI-driven warfare, automated surveillance, and cyber operations have transformed security paradigms.
 
Conclusion
The research concludes that AI is not merely a technological innovation but a transformative force in governance and economic policymaking. AI’s ability to optimize administrative functions, influence public discourse, and reinforce economic hierarchies creates new governance challenges and opportunities. The study highlights:

AI-driven governance models are replacing traditional bureaucratic systems.
Surveillance capitalism enables cognitive control through AI-based data surveillance.
AI exacerbates global economic inequalities, reinforcing digital colonialism.
Algorithmic policymaking is reshaping economic governance structures.
AI-driven geopolitical rivalries and digital sovereignty disputes are intensifying.

The study raises a fundamental question: Will AI governance enhances democratic accountability and economic fairness, or will it deepen authoritarian control and digital monopolization? Future research should explore ethical AI governance frameworks and policy mechanisms to mitigate AI-driven inequalities and ensure its benefits are equitably distributed.