AI Security in 2026: Turning Best Practices into Meaningful Governance

As artificial intelligence becomes embedded across business operations, products, and decision-making, the conversation around AI security is shifting. It is no longer just about technical safeguards. It is about governance, accountability, and trust.

A recent article by Sarah Cottone for Vanta, highlighted eight fundamental AI security best practices that teams should be prioritizing as we move into 2026. The guidance reflects a broader reality many organizations are facing AI risk is not hypothetical. It is operational, reputational, and regulatory.

What stands out most is that these best practices are less about any single control and more about building structured, repeatable systems that govern how AI is designed, deployed, monitored, and improved over time.

From AI controls to AI management systems

Several of the recommended practices emphasize the need for clear ownership, documented processes, and lifecycle oversight. These are familiar principles to organizations that already operate under management system standards, and they translate directly into how AI should be governed.

This is where ISO/IEC 42001, the international standard for Artificial Intelligence Management Systems, becomes especially relevant. Rather than focusing narrowly on model performance or security testing alone, ISO 42001 provides a framework for managing AI risks across the full lifecycle, from design and development through deployment, monitoring, and change management.

By treating AI as a managed system rather than a collection of tools, organizations can better address risks such as unintended bias, lack of transparency, model drift, and misuse, all of which are increasingly cited in AI security discussions.

The continuing role of information security

The article also reinforces a point that is sometimes overlooked in AI conversations: many AI risks are still information security risks at their core. Data integrity, access control, secure infrastructure, and incident response remain critical foundations.

AI systems are only as secure as the data pipelines, environments, and governance structures that support them. This is why alignment with ISO/IEC 27001, the international standard for Information Security Management Systems, remains essential. An effective ISMS helps organizations systematically identify, assess, and mitigate risks related to data and information assets, including those used to train, operate, and monitor AI systems.

When AI initiatives are built on top of mature information security practices, organizations are better positioned to manage emerging threats such as data poisoning, unauthorized model access, and exposure of sensitive outputs.

Moving from intent to evidence

Another recurring theme in AI security best practices is the need to demonstrate that controls are working in practice, not just on paper. As regulators, customers, and partners ask more questions about how AI systems are governed, organizations are being pushed to move beyond intent and toward evidence.

This is where independent assurance plays an important role. Assurance helps organizations validate that their AI governance, security, and risk controls are not only designed appropriately but are implemented consistently and operating as intended.

Intertek’s AI² program was developed to support this type of end-to-end evaluation, focusing on how AI systems align with governance frameworks, security expectations, and emerging standards. In the context of AI security best practices, independent assessment can help organizations identify gaps, strengthen controls, and demonstrate accountability in a rapidly evolving landscape.

A practical path forward

AI security in 2026 will not be achieved through isolated technical fixes. It will require integrated management systems, alignment between AI governance and information security, and ongoing oversight as systems evolve.

The best practices outlined in the article point to a clear direction of travel: organizations that treat AI as a managed, assured, and continuously improving capability will be better equipped to manage risk and maintain trust.

By grounding AI initiatives in established frameworks such as ISO 42001 and ISO 27001, and by seeking independent assurance where appropriate, organizations can turn AI security from a reactive concern into a structured, forward-looking discipline.

In a world where AI is increasingly central to how decisions are made and value is created, that discipline will matter more than ever.

For more information on how Intertek can support your organization visit ISO 42001 | Artificial Intelligence Management System (AIMS) Certification and ISO 27001 Certification | Information Security Management Systems.