Between Innovation and Oversight: A Cross-Regional Study of AI Risk Management Frameworks in the EU, U.S., UK, and China

As artificial intelligence (AI) technologies increasingly enter critical sectors like healthcare, transportation, and finance, developing effective governance frameworks is crucial for managing ethical, security, and societal risks. This paper conducts a comparative analysis of AI risk management strategies across the European Union (EU), United States (U.S.), United Kingdom (UK), and China. Using a multi-method qualitative approach, we investigate how these regions classify AI risks, implement compliance, structure oversight, and respond to innovation. Findings from high-risk contexts demonstrate the advantages and limitations of different regulatory models. The EU implements a structured, risk-based framework prioritizing transparency, while the U.S. uses decentralized, sector-specific regulations that promote innovation but risk fragmented enforcement. The UK's flexible strategy facilitates agile responses but may lead to inconsistent coverage, whereas China's centralized directives allow rapid implementation while constraining public oversight. These insights highlight the need for AI regulation that is globally informed yet context-sensitive, balancing effective risk management with technological progress. We conclude with policy recommendations for enhancing effective, adaptive, and inclusive AI governance globally.