"enterprise AI strategy"

Current assumption is whoever builds the smartest model will control the future of AI. Recent events suggest a different possibility.

To understand this new race, we must look at how data centers are changing and examine the rapid evolution of data center design.

If your agentic AI project is failing, your problem is likely that you treated the integration work as somebody else's issue to solve after...

A program that started with the team, not the tool, shifted the outcome.

Meta, OpenAI and Anthropic are spending billions on forward-deployed engineers, putting frontier labs on a collision course with Accenture,...

Many AI initiatives struggle to move beyond pilot phases, with Gartner predicting 40% of agentic AI projects will be canceled by 2027 due to...

​As AI moves further into everyday operations, companies are learning that deploying technology is only part of the challenge.

The objective is not to use the fewest tokens. It is to extract the highest return from every unit of intelligence consumed.

That gap between the impressive demo and real business change is the cost that most finance teams won’t be able to measure.

"Most companies use AI. At Capital One, we build it," said Milind Naphade, SVP of AI Foundations at Capital One. Discover how Naphade is lea...

Sustained success with AI depends on enterprises strengthening governance and security by implementing both from the outset.

Just as the AI-native human has no unaugmented surface area in their work, the AI-native organization must have no unaugmented surface area...