Foundations

IBM's framework begins with a reversibility assessment that determines which of three automation tiers applies to a given task.

The work proposes a five-layer architectural framework that embeds governance and security requirements throughout system design rather than treating them as separate concerns.

A new approach is needed, one that thinks in terms of dynamic spectrums rather than static boxes.

The rise of autonomous AI agents is fundamentally expanding the attack surface for zero-click exploits, creating new and unpredictable risks.

Agentic AI demands a different approach to governance—proactive, structured, layered.

The architectural shift to persistent, structured memory is happening now. Teams building these systems need to classify the memory types their agents require and define the associated governance policies upfront.

The NIST AI RMF shifts AI risk management from abstract principles to a structured, operational process...When AI is ubiquitous, trust matters. The RMF provides a tool for building that trust through continuous improvement.

The shift to widespread AI requires a shift in approach: from reactive problem-solving to intentional design... The organizations that get ahead of this will be the ones that can prove their AI systems work as intended—and can be trusted accordingly.