Power Without Rules: The Global Policy Vacuum Around General Purpose AI

General Purpose AI is advancing faster than any regulatory system designed to govern it. Models capable of writing code, generating images, analyzing data, and reasoning across domains are now deployed globally within months of release. Yet the rules that determine how these systems should be built, deployed, and constrained remain fragmented, inconsistent, or entirely absent.

This growing mismatch between capability and governance has created a global policy vacuum, one that may define the next decade of technological risk and opportunity.

What Makes General Purpose AI Different

General Purpose AI, often referred to as foundation models, is not built for a single task. It can be adapted across sectors including healthcare, finance, education, defense, and media. This flexibility is precisely what makes GPAI powerful and difficult to regulate.

Traditional technology laws are sector-specific. They assume clear boundaries between use cases. GPAI breaks those assumptions. A single model trained for general reasoning can be repurposed in ways its creators never intended.

Research and deployment by organizations such as OpenAI and Google DeepMind illustrate how rapidly general capabilities now scale once models are released.

Why Existing Regulations Fall Short

Most current AI regulations focus on outcomes rather than capabilities. They regulate applications like credit scoring, facial recognition, or medical diagnosis. GPAI does not fit neatly into these boxes.

This creates enforcement gaps. A general model may be lawful at release but harmful in downstream use. Liability becomes unclear. Is responsibility held by the model developer, the deployer, or the end user.

According to analysis published by MIT Technology Review, regulators worldwide struggle to define jurisdiction, accountability, and risk thresholds for systems that operate across borders and industries simultaneously.

The Geopolitical Dimension of the Vacuum

The absence of shared global rules has geopolitical consequences. Nations fear that strict regulation will slow domestic innovation while competitors accelerate unchecked. This dynamic encourages regulatory hesitation rather than leadership.

At the same time, GPAI capabilities increasingly affect national security, labor markets, and information ecosystems. Without coordination, policy fragmentation risks a race to the bottom where safety standards erode in favor of speed and market dominance.

Institutions such as MIT have warned that governance delays could allow irreversible societal impacts before safeguards are established.

Emerging Proposals and Their Limitations

Some regions are beginning to act. Proposals include model registration, compute thresholds, mandatory risk assessments, and transparency requirements for training data and capabilities.

However, these efforts remain uneven. Many frameworks focus on high-risk applications rather than the underlying general-purpose systems. Others rely on voluntary commitments that lack enforcement.

The result is a patchwork of guidelines that fail to address the systemic nature of GPAI risk.

What Responsible Global Governance Could Look Like

Closing the policy vacuum does not require stifling innovation. It requires clarity. Baseline global standards for transparency, evaluation, and accountability could coexist with national enforcement.

Shared definitions of General Purpose AI, independent auditing mechanisms, and cross-border cooperation would help align incentives. Crucially, governance must evolve alongside technical capability, not years behind it.

The alternative is reactive regulation shaped by crisis rather than foresight.

Conclusion

The global policy vacuum on General Purpose AI is no longer theoretical. It is shaping how power, risk, and responsibility are distributed in real time. As GPAI systems become embedded across economies and institutions, the absence of coherent governance grows more dangerous. The question facing policymakers is not whether to regulate, but whether they will do so before decisions are made for them by technology itself.

Fast Facts: The Global Policy Vacuum on General Purpose AI Explained

What is General Purpose AI?

The global policy vacuum on General Purpose AI refers to systems designed for broad, adaptable tasks across industries rather than single, predefined functions.

Why is GPAI hard to regulate?

The global policy vacuum on General Purpose AI exists because these models cross sectors, borders, and use cases, breaking traditional regulatory frameworks.

What are the biggest risks of inaction?

The global policy vacuum on General Purpose AI risks unchecked deployment, unclear accountability, geopolitical imbalance, and delayed responses to systemic harm.