Moving from AI race to AI governance

Trust is AI's best accelerator

The rapid pace of AI legislation around the world is an encouraging sign. China is moving decisively in this direction, and AI regulation will mature even faster than the data protection law did. In less than five years, robust legal frameworks could be in place.

Unlike data protection, AI regulation does not exist in isolation. It intersects with other areas of law. The European Union's AI Act alone overlaps with a wide range of legal instruments, creating a regulatory landscape that spans thousands of pages. This is not a criticism — it is simply the reality of governing a technology that touches nearly every sector. At the International Association of Privacy Professionals, we call this digital entropy, where complexity naturally accumulates as technology evolves.

That complexity is already evident. In Ireland, for example, some 15 regulators from different sectors share responsibility for enforcing the EU AI Act, each bringing its own mandate and interpretation. Similarly, within organizations AI governance is divided among teams handling privacy, consumer protection, intellectual property, trust and safety, content moderation and platform accountability. AI now sits at the center of all these functions, making governance inherently cross-disciplinary.

The history of privacy regulation tells us that while global coordination is important, diversity in governance is not a failure. Different countries will inevitably adopt different AI policies, reflecting their own values, cultures and legal traditions. That diversity is a feature, not a flaw. Innovation involves not just designing better technology, but also designing better governance.

Good governance, however, requires investment. Implementing AI responsibly demands people, expertise, funding and technical infrastructure. These are not needs unique to major AI companies. Every bank, insurer and enterprise deploying AI must build its own governance capacity.

As AI reshapes the regulatory landscape, long-standing privacy principles such as notice and consent are becoming harder to apply in practice. Policymakers must therefore look beyond legislation to technical standards and governance frameworks, embedding principles directly into technology.

The Dutch philosopher Desiderius Erasmus once warned that chasing two rabbits means catching neither. In the AI era, that wisdom deserves reconsideration. We should not see innovation and trust as competing goals. Consider the early automobile: before reliable brakes, cars could travel only at modest speeds. It was the invention of brakes — not their absence — that made faster, safer travel possible. Trust and accountability play the same role for AI. They do not constrain innovation; they enable it to move further and faster.

Entropy tells us that systems naturally tend toward disorder, but that tendency is not destiny. With thoughtful governance, strong institutions and responsible technology, we can create more order, more trust and ultimately more innovation in the age of AI.