There is a quiet panic settling into enterprise AI rooms right now. Not the loud kind. The expensive kind. Teams finally proved agentic AI works, then watched sensitive data sprint across prompts, logs, tools, and integrations like it found an unlocked side door. Innovation moved fast. Governance showed up late. Legal noticed. Risk noticed louder.
This is the moment Skyflow is responding to, not with optimism theater, but with architecture. On Tuesday, January 20, 2026 at 9:00 AM PT, Skyflow is hosting a live webinar called “Agentic AI Breaks Traditional Data Security,” and the title is doing real work. Agentic systems do not behave like users, and pretending they do is how regulated enterprises end up in board decks for the wrong reasons.
Autonomous agents move data at machine speed, without tickets, without intent, without pauses for approval. Once sensitive data hits a prompt or an external tool, control becomes a memory. Financial services, healthcare, enterprise SaaS, everyone carrying PII is learning the same lesson from different angles. The productivity upside is undeniable. The risk exposure is equally real. That tension is no longer theoretical.
The room for this conversation is digital, but the stakes are physical. Budgets, fines, careers. The EU AI Act clock is ticking toward August 2026, and suddenly CISOs, CROs, product leaders, and general counsel are all sitting at the same table, realizing none of their old playbooks map cleanly to autonomous decision-making systems.
The speakers matter here. Amruta Moktali has built enterprise-grade analytics and AI platforms at Salesforce, Microsoft, and beyond, shipping systems that had to scale without breaking trust. Sam Sternberg comes from the hard edges of identity, access, and government-grade security, translating policy into systems that actually hold under pressure. This is not theory. This is muscle memory.
Skyflow, under Anshu Sharma’s leadership, is not introducing itself. It is drawing a boundary. Data security for agentic AI is no longer an add-on or a patch. It is the constraint that determines whether these systems make it out of pilot purgatory and into production reality.
This webinar is a signal. Agentic AI is graduating from curiosity to consequence, and the companies that understand that early will move faster with fewer scars. The rest will learn the long way, one incident report at a time.
