Technorealism offers a strategic framework for global and national leaders to balance innovation with regulation in AI governance, emphasizing power dynamics, data sovereignty, and inclusive collaboration.

Artificial intelligence is no longer a futuristic concept—it is a present-day force reshaping every facet of human life, from governance to commerce and defense to education. Yet, while innovation charges ahead at breakneck speed, laws and regulations lag far behind, straining to keep pace with technologies that are evolving in real time.

This disconnect poses a unique challenge for global leaders. At the heart of this problem lies an emerging framework known as technorealism, a philosophy that draws from political realism to evaluate technology not merely as a tool of convenience but as an instrument of power. Technorealism argues that our intrinsic drive for survival and identity formation elevates technology to a central axis of geopolitical influence, where even non-state actors play increasingly pivotal roles.

AI is now a means to achieve political ends and a contested domain where power is claimed, wielded, and recalibrated. The strategic tug-of-war between the U.S. and China for AI supremacy exemplifies this dynamic. Meanwhile, the European Union has taken a different approach, introducing its own regulations, the AI Act, which sets global standards and builds a foundation for responsible innovation.

Leadership in this new era demands more than authority—it requires comprehension. To govern it effectively, today’s decision-makers must acquire deep, technical fluency in AI’s mechanics and implications. But the pace of innovation has outstripped many leaders’ ability to understand, let alone regulate, this fast-changing landscape—the result: a precarious balancing act between the imperatives of progress and the necessity of protection.

Regulatory clarity is essential, but overregulation could suffocate innovation, while underregulation risks unleashing a cascade of social harms—from privacy violations and algorithmic bias to mass job displacement through automation. Navigating this middle ground is the defining challenge of the AI age.

At its core, AI is driven by data, making data governance an equally urgent concern. Without strong privacy, security, and transparency standards across the entire data lifecycle—collection, storage, usage—AI systems are vulnerable to misuse and abuse. Leaders must, therefore, establish rigorous protocols that safeguard public interest without stifling the technology’s transformative potential.

Technorealism offers a compelling lens for analyzing these challenges. It recognizes AI as a geopolitical asset and highlights the importance of understanding nation-state strategies in regulatory design. Countries and corporations that control AI technologies don’t just win market share—they gain disproportionate influence over global norms and power structures.

This interplay between state and non-state actors is central to the future of AI governance. Tech giants such as Google, IBM, and Microsoft are no longer just vendors; they are policy influencers and de facto regulators. In this reality, effective governance hinges on dynamic partnerships between governments, industry, and civil society—each contributing to a regulatory ecosystem as adaptive as the technologies it seeks to manage.

Under technorealism, the goal is stability and security—not just for national defense but for societal well-being. This demands a risk-calibrated approach to regulation that differentiates between various categories of AI risk. The European Union’s AI Law provides a useful model, classifying AI systems into levels of risk—unacceptable, high, medium, and low—each requiring corresponding legal safeguards. This risk-based model strengthens oversight while preserving flexibility.

Data governance must also be robust and comprehensive. Frameworks should include provisions for data classification, access controls, privacy audits, and impact assessments. These are not just technical details—they are ethical imperatives in an age where data is currency and control over data is power.

A collaborative model of governance—one that brings together states, corporations, academic institutions, and civil society—is essential to building a set of AI norms and protocols that reflect collective values. Adaptive and iterative strategies, such as regulatory sandboxes, allow for experimentation without full-scale rollout, striking a balance between innovation and oversight.

These efforts must also be international in scope. Divergent regulatory regimes could hamper innovation and create legal inconsistencies that weaken global safeguards. Harmonization—through bilateral and multilateral agreements—is essential to crafting a coherent global AI governance system.

Indonesia’s growing digital economy offers a case study in how developing nations can chart their course through the AI frontier. Applying technorealism, Indonesia can design regulatory systems tailored to its unique cultural, legal, and economic realities. Building domestic capacity in AI regulation—through policymaker training and institutional development—will be key to crafting effective, enforceable rules.

Indonesia must prioritize data sovereignty, ensuring that sensitive data is processed and stored locally to protect national interests. Ethical and safety standards, if enforced, can simultaneously foster innovation and uphold regulatory compliance—offering advantages to local companies while maintaining public trust.

Active engagement in global AI discourse is equally essential. Indonesia’s participation in international rulemaking processes will help shape standards that reflect the interests of emerging economies, not just those of technological superpowers. In doing so, the country can ensure it is not a passive recipient of foreign norms but an active architect of its digital future.

A holistic approach to AI regulation must integrate technical, ethical, societal, and geopolitical dimensions. Technorealism, with its focus on power dynamics and non-state actors, offers a strategic framework for navigating this complexity. For leaders everywhere, understanding AI is no longer optional—it is an imperative. Balancing innovation with protection, managing ethical and social risks, and ensuring responsible data stewardship are the non-negotiables of 21st-century leadership.

By embracing risk-based strategies, establishing rigorous data governance, fostering inclusive partnerships, and pushing for global regulatory convergence, we can build an AI ecosystem that is both resilient and just. For Indonesia and other developing nations, technorealism provides a roadmap to harness AI for national development while safeguarding sovereignty, ethics, and equity in the digital age.