AI adoption is rapidly increasing, yet many projects fail to move from successful pilots to reliable long-term products. The key to scaling these initiatives is implementing ethical AI practices that ensure accountability, transparency, and consistent performance in real-world conditions.
Artificial intelligence (AI) is increasingly shaping the customer journey in financial services by enhancing onboarding, risk assessment, fraud detection, and customer support. As firms adopt AI, they must navigate regulatory requirements to ensure fairness, accountability, and positive outcomes for customers.
Pacific AI’s 2025 AI Policy Year in Review highlights the rapid shift from voluntary AI guidelines to enforceable legal frameworks across 30+ nations and the EU, emphasizing the increased operational burdens for organizations with incident reporting requirements rising by 200%.
As AI becomes increasingly integrated into pharmaceutical marketing, organizations must prioritize compliance with evolving privacy regulations. Establishing robust AI governance and designing privacy-focused data architectures are essential to navigate the high-risk environment surrounding health-related data.
New York Governor Kathy Hochul proposes creating the Office of Digital Innovation, Governance, Integrity and Trust under the Department of Financial Services to enforce AI regulations.
LōD Technologies, based in Vancouver, addresses Canada’s AI adoption challenges by offering CLōD, an innovative platform that optimizes energy costs, ensures data governance, and provides comprehensive control over AI workloads. This solution aims to make AI usage more predictable and accessible for organizations in regulated industries.
ScreenPoint Medical and Ferrum Health have partnered to offer the Transpara Breast AI Suite through Ferrum’s Model Hub, enhancing breast cancer detection and improving radiologist workflow. This collaboration provides healthcare organizations with a validated, integrated AI solution to improve screening outcomes and operational efficiency.
Training organisations have until February 2026 to influence the EU’s AI regulations in aviation through EASA’s public consultation on its AI Trustworthiness Framework. This initiative aims to provide technical guidance on AI trustworthiness for high-risk systems as outlined in the EU AI Act.
President Donald Trump’s executive order on artificial intelligence raises complex questions about the boundaries of state authority in AI regulation and the challenges posed by the AI Litigation Task Force against conflicting state laws.
The upcoming EU Article 73 guidelines mandate reporting serious AI incidents in high-risk environments, but focus too narrowly on single-agent failures. This oversight risks accountability and systemic harms from interactions between multiple AI systems, which must be addressed to protect collective interests.