Victoria Gayton
Latest from Victoria Gayton
Enterprise AI adoption, demystified: What enterprises learned building with Google Cloud
Enterprise AI didn’t slow because the technology wasn’t ready. It slowed because people weren’t sure what to trust, what to learn or where to begin. Over the past year, conversations with Google Cloud leaders and industry experts revealed a consistent pattern: Enterprise AI adoption advances when confidence replaces complexity. That pattern became clear over the ...
How Google Cloud is shaping the enterprise AI inference moment
Enterprise technology investment continues to accelerate, but the friction point has shifted. The hard part is no longer training models or selecting architectures. It’s getting those models into production, keeping them responsive under real-world conditions and proving they deliver value once they’re live. AI inference is where initiatives either prove their value or grind to ...
AI agents face a widening trust gap, theCUBE Research finds
AI agents are fast becoming the defining force behind the enterprise shift from simple automation to true decision intelligence. If the first satisfactory phase of enterprise artificial intelligence was about automation, the next is clearly about augmentation: enhancing human intelligence in knowledge work. TheCUBE Research’s “Agentic AI Futures Index” shows that shift accelerating. Sixty-two percent ...
Three insights you may have missed from theCUBE’s coverage of AWS re:Invent
Something that’s been building for several years has finally come into clearer view as enterprises shift their attention from model performance to the systems that bring intelligence into production. The conversation now centers on how agentic AI fits into real workloads, reshaping expectations for automation, performance and the work developers can hand off to software. ...
Union.ai on the rise of experimental AI development infrastructure in the enterprise
Building software has long followed a reliable playbook: Write code, test, deploy and iterate. But when deterministic algorithms give way to artificial intelligence models that learn and adapt, the old playbook falls apart. AI development infrastructure has become essential for enterprises trying to move projects from prototype to production. The shift stems from a fundamental ...
Synthetic recovery gains traction as a new frontline defense against escalating cyberattacks
When a cyberattack hits, organizations face an impossible choice: Roll back to a known, clean copy and accept significant data loss or push forward with potentially compromised systems. That no-win gamble has defined disaster recovery for years. A new approach, synthetic recovery, is reframing the equation entirely. The concept, introduced by Commvault Systems Inc. at ...
Developer workflow poised for change as AWS advances continuous-learning AI agents
For all the hype around artificial intelligence coding assistants, many treat every session as a blank slate — no memory of yesterday’s preferences, context or institutional knowledge. That’s the gap agentic AI aims to close, not just helping developers write code but functioning as persistent, context-aware teammates. Developers typically spend only 20% to 30% of ...
AI agents reshape expectations for data connectivity as Salesforce expands its ecosystem strategy
Enterprise data integration is fast becoming the quiet power broker behind modern AI, reshaping how companies stitch together sprawling data estates, evolving application stacks and an ever-widening menu of model options. What’s emerging is less a tooling problem and more a coordination challenge — one that surfaces the moment agentic workflows and AI-driven operations start ...
AI-native observability is becoming the new enterprise compass, says Honeycomb.io CMO
Cloud-native practices have matured into stable foundations, and the industry is accelerating toward an AI-native observability future. Observability is becoming essential for ensuring direction and measurable outcomes in this fast-paced environment. Cloud-native and AI-native observability are reshaping workflows, data practices and engineering culture. With the rise of agentic systems, enterprises face unprecedented volumes of data ...
How Zendesk built the AI engine powering billions of customer interactions
Customer service automation has become one of enterprise tech’s most AI-intensive workloads. The shift goes beyond chatbots to multimodal interactions, proprietary training data and infrastructure handling hundreds of billions of application programming interface requests annually. Cloud-based software company Zendesk Inc.’s approach is built on a multifaceted relationship with Amazon Web Services Inc., spanning infrastructure, voice ...