Enterprise AI is at an inflection point. What began with centralized, cloud-scale large language models (LLMs) is moving ...

From data foundations to skills and culture, most organizations aren’t operationally ready to succeed with AI. Here’s where ...

Buy-side firms are consistently faced with burgeoning volumes of data, necessitating adept management of expansive data extractions, a task fraught with intricacies and considerable costs. Arthur Orts ...

Many higher education institutions are migrating their data centers to a cloud operating model. It's a movement that has its roots over a decade ago. And while that may not be news, it's a growing ...

The AI data center of the future will not be defined by one end-state architecture. It will be defined by optionality, ...

A CX operating system isn't a platform you buy — it's how modern enterprises coordinate data, AI and people to execute ...

If things continue at this pace, it won't be surprising if CPA firms have a 40-to-one agent-to-human ratio in the near future ...

For decades, banks have wrestled with fragmented regulatory data by investing billions in lakes, warehouses and point solutions that promised control but delivered more silos. What financial ...

Railpen, the fiduciary and investment manager of the UK railways’ pension schemes, has appointed BNY Mellon to provide a data operating model. BNY Mellon’s cloud-based data platform aims to deliver ...

Slapping AI onto a broken workflow is like putting a rocket engine on a tricycle; you need to redesign your entire operating ...