The shift from on-premises computing to software as a service changed the technology model and forced information technology organizatios to modernize how it builds, buys and operates software. It also reshaped how software vendors price, deliver, and add value. But for most buyers, SaaS didn’t fundamentally change how the company made money or how work ...

As artificial intelligence agents become more powerful, agentic AI governance becomes increasingly important – and yet, today’s governance solutions struggle to keep AI agents from going off the rails. In my last article in this series, I discussed the state of the art for keeping agents on the rails: multiple diverse adversarial validators with multilayer ...

In just a short few months, we have witnessed several artificial intelligence technology events that deserve the overused “unprecedented” descriptor: a highly complex supply chain attack by TeamPCP, Anthropic PBC’s Claude Code source leak, and the debut of Anthropic’s Claude Mythos, a tool said to be so powerful that its use was immediately restricted to ...

The market is trying to price a transition it hasn’t fully internalized. It sees Nvidia Corp.’s market cap with a five-handle and assumes the valuation is too high to grow further. We believe that’s the wrong mental model and it underestimates the market potential. Though the shift underway resembles the RISC-to-x86 transition, it is far ...

Agentic AI is already becoming a common part of how enterprises operate. But getting real value from AI depends on how well it fits into a company’s existing governance and compliance processes, especially in highly regulated industries. Process-centric AI describes an architectural approach in which businesses integrate agentic AI into existing workflows from the ground ...

It’s 2:17 a.m., and your application monitor flags elevated database latency. Before your on-call engineer finishes reading the alert, three agents have already responded. The performance agent doubles the database capacity. The cost agent, seeing what appears to be overprovisioning, starts consolidating database instances. The routing agent reroutes traffic through the database tier. Each decision ...

Enterprises are entering a new phase of cloud adoption where flexibility, control and performance are no longer trade-offs but requirements. As AI workloads become more distributed and data-intensive, organizations are rethinking traditional SaaS-first strategies in favor of hybrid and sovereign cloud models that bring compute closer to data while maintaining operational consistency. At the same ...

The race for AI dominance is about more than which model will reign supreme. The real action is happening underneath the surface, where hyperscalers such as Google LLC are focused on the infrastructure and the data pipelines that models run on — especially as agentic AI infrastructure becomes the true battleground for enterprise scale.  In ...

Most discussions about artificial intelligence security are focused on what models might do wrong. The more urgent issue is what our detection systems still cannot see — and side-channel attacks are making that gap visible. Side-channel attacks gather information or interferes with a program’s execution by targeting physical factors such as power consumption, electromagnetic emissions ...

Enterprises are moving fast to embed artificial intelligence into everything from customer interactions to decision-making. The benefits are undeniable: speed, efficiency and scale. The danger isn’t necessarily sudden or dramatic. It’s quieter, more gradual, invisible and easy to justify along the way: It’s the slow loss of agency inside the company. A company loses agency ...