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Your cloud security stack was built for a world that no longer exists. Every enterprise I talk to has spent the last decade hardening cloud infrastructure against the usual suspects: misconfigurations, IAM sprawl, exposed storage buckets. Good. Necessary. Insufficient. AI has quietly become the new perimeter, and most security teams haven't updated their threat model to match. LLM integrations now touch production data, agentic workflows execute actions autonomously, and prompt injection attacks don't care about your firewall rules. The attack surface expanded, but the governance conversation stayed stuck in 2019. Here's the uncomfortable truth: you can have pristine ISO 27001 certification and a SOC 2 Type II report and still be blind to how your AI systems are accessing, transforming, and exposing cloud assets. Traditional controls assume deterministic systems. AI is probabilistic. That gap is where incidents live. Here's what smart teams are doing: → Mapping every AI touchpoint to cloud assets, not just the ones IT knows about → Treating model inputs and outputs as a distinct data flow requiring its own controls → Building AI-specific incident response playbooks before an incident forces one → Aligning AI governance work with ISO 42001 now, ahead of regulatory pressure, not after The organizations that treat AI security as an extension of cloud security, rather than a bolt-on afterthought, are the ones that will avoid the headline-making incidents in 2026. What's your organization doing to close the gap between cloud security maturity and AI governance readiness? #AIsecurity #CloudSecurity #ISO42001 #SOC2 #AIgovernance #CyberRiskManagement