Breaking Analysis with Dave Vellante

The cloud shared responsibility model was initially not well understood by many customers. In fact, early adopters often believed that simply having data in the cloud meant that Amazon, or a SaaS vendor were responsible for safeguarding it. Amazon had to educate its customers and partners that security and compliance duties were split between the vendor and the client organization. In short, the vendor was responsible for securing the cloud resources but you, the buyer, were responsible for securing what you put inside the cloud; based on your policies, priorities and budget. We believe a similar but much more consequential dynamic is unfolding with respect to agentic AI. Specifically, Cloud computing divided responsibility by infrastructure layer. Agentic AI distributes authority across a chain of models, platforms, clouds, partners and customers. Our premise is the industry now needs a shared accountability model for the decisions, actions and outcomes that chain produces.

In short - The cloud shared-responsibility model told customers who secures what. The agentic shared-accountability model must define who can do what, who can stop it, who can prove what happened and who pays when it goes wrong.
Welcome to episode 326 of Breaking Analysis. Beyond Shared Responsibility - When AI Acts, Who owns the Blast Radius. 

In this Breaking Analysis, Principal CUBE Research Analyst Krista Case and I explain why the agentic era demands a new accountability model. We’ll draw on learnings from last week’s CrowdStrike Fal.Con event, where the post Mythos moment and the OpenAI/Hugging Face “accident” were front and center. We’ll also draw on other new datapoints, including conversations with CISOs at Fal.Con and Palo Alto Networks’ earnings print from last week, to unpack what we’ve defined as a new AI accountability model. We’ll also test this new model against our Sovereignty framework, developed by Amit Govrin and assess sovereignty in the context of business recovery. We’ll explore the sequence of events that leads up to the ultimate question of who pays when something goes wrong?

Breaking Analysis with Dave Vellante

Breaking Analysis with Dave Vellante and Amit Eyal Govrin

Breaking Analysis with Dave Vellante.

We get a lot of questions about whether we're in a bubble & if so when will it burst. Many feel that "Bubble" is a pejorative. I see it differently. To me a bubble is an economic event where asset prices & valuations in a new or growing market rise far above their current value. Bubbles are characterized by media hype, investor exuberance, fast/easy money & FOMO. Bubbles do not always burst in a sudden, catastrophic event. Sometimes they have a "soft landing." 
AI can be technologically transformative and still produce a capital bubble. Those two ideas are not in conflict.
The bubble bursting does not require AI to fail. It only requires deployable supply and capital commitments to grow faster than monetizable demand. When productive, revenue-producing AI capacity takes longer to materialize, pricing will normalize and financing will no longer bridge the gap. That’s when the capital cycle possibly resets and a liquidity crunch ensues.