Abstract

As artificial intelligence (AI) becomes increasingly integrated into critical sectors such as healthcare, finance, law enforcement, and education, the need for effective regulation and governance becomes more urgent. This paper explores current global approaches to AI governance, identifies major challenges including bias, accountability, and transparency, and compares frameworks from different countries and organizations. It evaluates both binding regulations and soft-law instruments, proposing a hybrid, adaptive governance model that balances innovation with ethical responsibility.