Drata has released findings from its report, ‘The State of GRC in the Age of AI’.
AI resilience
AI resilience resources and information
AI resilience is the capacity of an organization to anticipate, withstand, respond to and adapt to disruption or harm involving artificial intelligence – whether caused by system failure, unreliable outputs, malicious manipulation, misuse, supplier dependency or wider systemic effects – while maintaining critical outcomes and recovering safely within acceptable limits.
AI resilience encompasses both:
– The resilience of AI systems themselves; and
– The resilience of the organization when AI systems become unavailable, degraded, unreliable or unsafe.
Organizational capabilities supporting AI resilience include effective governance and human oversight, understanding operational dependencies, contingency arrangements, exercising, recovery, learning and adaptation.
Orca Security has released its 2026 State of AI Security Report, offering a first-hand view into how AI is being deployed across more than 1,200 production cloud environments.
It’s July 2028 and a disgruntled employee is about to set a ball-rolling that will have unanticipated impacts around the world…
Your business is starting to depend on AI, but can it survive an outage? Why the most important AI conversation today is about resilience, not just innovation.
Sean Tilley explores why AI is a governance issue for boards. The article looks at how the pressure for speed is outpacing risk controls and resilience management.
As AI adoption rapidly gains speed, traditional linear recovery models are no longer enough. Mark Molyneux explains why the rise of agentic AI is forcing a critical shift to ‘resilience operations’ (ResOps).
FusionAuth’s 2026 State of AI and Identity Report finds that nearly two-thirds of organizations have experienced a confirmed AI identity breach in the past year, and among those who feel most secure, the rate jumps to 84%.
Jamf has released findings from a survey of 687 IT and security leaders that reveal a growing challenge for organizations adopting AI: as might be expected, the more deeply AI becomes embedded into daily work, the more AI-related incidents occur.
Anthropic has published an Advanced AI Framework which includes proposals for how governments should address catastrophic risks from the most powerful AI models.
Veeam Software has published new global research, the ‘Data and AI Trust Gap’ report. This exposes a ‘stark and widening gap at the heart of enterprise AI’.