The Schellman Blog

As organizations scale their use of AI systems in key business processes, customer-facing products, and high impact decisions, the question is no longer whether AI can deliver value, but whether it can be deployed in a way that is reliable, secure, fair, and sustainable over time.

As artificial intelligence continues to rapidly evolve, from generative tools to increasingly autonomous systems, governments around the world are accelerating efforts to formalize AI governance. Regulatory frameworks are becoming enforceable on legal requirements that shape how AI systems are designed, deployed, and monitored.

As the EU AI Act moves from legislation to implementation, organizations across Europe and beyond are working to operationalize AI governance in practical, auditable ways. Compliance and governance leaders, AI product teams, and executives are asking the same question: How can we demonstrate EU AI Act compliance in a structured and defensible way?

The information in this article was originally presented on January 15, 2026, at a Public Hearing to the New York State Senate Standing Committee on Internet and Technology to discuss risks, solutions, and best practices with respect to the use of artificial intelligence in consequential or high-risk contexts, and related issues.

As interest in ISO 42001 certification has surged over the past year, we've heard a steady stream of questions from organizations seeking to build their AI governance strategy and operationalize their Artificial Intelligence Management Systems (AIMS) responsibly. From understanding practical preparation steps to what to expect during the audit, many teams are looking for clearer guidance as they navigate this newer management system standard.

As artificial intelligence becomes increasingly embedded in core business operations and customer-facing product offerings, organizations are under growing pressure to ensure their AI systems are safe, ethical, transparent, and well-governed. ISO 42001, the world’s first international standard for AI management systems, provides the structure needed to build trustworthy AI and demonstrate responsible governance to customers, regulators, and partners.

Not only is artificial intelligence changing how businesses operate; it's also changing how cybercriminals attack. As organizations rush to adopt AI systems, they face new security risks that traditional defenses can't handle.

As artificial intelligence continues to become widely embedded in critical business decisions, strategies, and processes, it increasingly faces growing scrutiny from regulators, customers, and the public. While AI offers unprecedented opportunities for operational enhancements and innovation, it also introduces new risks.