U.S. officials rejected the establishment of a global AI governance framework at the United Nations General Assembly, despite broad support from many nations, including China. Michael Kratsios of the U.S. Office of Science and Technology Policy emphasized that Washington opposes centralized control over AI, advocating instead for responsible diffusion and national sovereignty.
As companies increasingly adopt agentic AI systems for autonomous decision-making, they face the emerging challenge of agentic AI sprawl, which can lead to security vulnerabilities and operational inefficiencies. Experts urge businesses to implement robust governance frameworks to navigate these risks effectively and avoid the pitfalls seen in past technology deployments.
As large language models (LLMs) become increasingly integrated into sectors like healthcare and finance, a new study highlights the potential for subtle biases in AI systems to distort public discourse and democratic processes. The research calls for regulatory reforms to address communication bias, emphasizing the need for a more inclusive AI governance framework that enhances user self-governance and fosters a diverse ecosystem of information sources.
The burgeoning world of Artificial Intelligence (AI) is at a critical juncture as regulatory actions signal a new era of accountability and ethical deployment. Recent events highlight the shift towards increased compliance, transparency, and governance in the rapidly evolving AI landscape.
As generative AI continues to evolve, so do the associated risks, making AI governance tools essential for managing these challenges. This initiative, in collaboration with Tokio Marine Group, aims to evaluate and select the most effective AI governance solutions through a structured process involving extensive criteria and datasets.
The United Nations is working to influence global policy on artificial intelligence by establishing an expert panel to develop standards for “safe, secure and trustworthy” AI. This initiative aims to facilitate international cooperation and discussions on AI governance while addressing concerns related to the technology’s impact on society and the workforce.
The conversation between Thomas Roehm from SAS and Frankie Phua from United Overseas Bank at the SAS Innovate On Tour in Singapore explores how data-driven regulation can effectively govern rapidly evolving AI technologies. Their discussion highlights the collaborative approach of Singapore’s Project MindForge, which aims to create practical frameworks for AI governance by involving industry practitioners in the regulatory process.
Small and medium-sized enterprises (SMEs) must navigate the complexities of the EU AI Act, which categorizes many AI applications as “high-risk” and imposes strict compliance requirements. To adapt, SMEs should develop strategies that include forming strategic partnerships, implementing compliance-by-design, and leveraging ethical AI adoption to differentiate themselves in the market.
On September 26, 2025, the European Commission published draft guidance on serious incident reporting requirements for high-risk AI systems under the EU AI Act. Organizations developing or deploying such AI systems must understand these new reporting obligations for compliance planning, as the requirements will take effect in August 2026.
The United States rejected calls for international oversight of artificial intelligence at the U.N. General Assembly, emphasizing the importance of national sovereignty over centralized governance. This stance contrasted with global leaders advocating for collaborative frameworks to address the challenges posed by AI.