The rise of large language models (LLMs) has transformed our interactions with technology, necessitating a focus on their safety, reliability, and ethical deployment. This guide discusses essential concepts of LLM safety, including the implementation of guardrails to mitigate risks such as data leakage and bias.
The AI Act reshapes the roles of corporate governance by making AI oversight a crucial responsibility for board secretaries, compliance officers, and general counsel. This legislation not only imposes new fiduciary duties but also highlights the need for U.S. corporations to align their governance structures with evolving regulatory frameworks that extend beyond Europe.
AI is no longer just a research tool; it has become integral to products and services, which brings risks such as misuse and errors. To ensure its safe implementation, strong cybersecurity measures, governance, and responsible AI practices are essential for maintaining public trust and accountability.
Apple’s Live Translation feature for AirPods, designed to enhance real-time communication through AI, will not be available to EU users due to strict regulations. This decision highlights ongoing challenges between tech companies and European regulators regarding data privacy and AI compliance.
The EU AI Act establishes a comprehensive legal framework to regulate artificial intelligence, focusing on transparency and human oversight in customer service interactions. Companies must prepare to comply with these regulations by August 2, 2026, ensuring responsible AI use that builds customer trust and mitigates risks of hefty fines.
U.S. Senator Ted Cruz has introduced a bill that would allow artificial intelligence companies to apply for regulatory exemptions to foster innovation. The proposal includes a two-year exemption period and requires companies to outline potential risks while addressing concerns from consumer advocacy groups about the implications of such regulatory changes.
As organizations rapidly adopt AI, the need for a scalable AI governance program becomes crucial to manage the risks associated with this technology. This guide emphasizes the importance of defining roles, implementing strong frameworks, and ensuring continuous oversight to facilitate responsible AI deployment across enterprises.
This guide emphasizes the importance of AI governance for developers, positioning it as a crucial framework to ensure that AI systems are ethical, compliant, and safe. By integrating governance into the development lifecycle, developers can proactively address risks such as bias and privacy violations while building trustworthy AI solutions.
It remains unclear whether OpenAI is complying with the EU’s AI Act training data disclosure requirements for its latest model, GPT-5, which was released shortly after the deadline for compliance. Although OpenAI has signed the EU’s code of practice, it has yet to publish a training data summary or a copyright policy for GPT-5.
This post presents a comprehensive AI Risk & Governance Checklist that helps organizations ensure compliance with the EU AI Act. It covers key areas such as risk identification, governance, data management, transparency, human oversight, testing, monitoring, impact assessment, regulatory compliance, security, and training.