Setting baselines and goals could help companies be more stringent about which AI projects they pick.
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AI’s enterprise value exists on a “bell curve” – one which, at the current rate of AI development, we’re nearly at the top of.
“We’re getting an opportunity to really bring in a very, very talented team who has been in the middle of AI evolution.”
The frenzied speed at which enterprises are adopting the tech amplifies the hazards.
Many enterprises are in a “phase of investigation” with AI deployment.
For some tasks, less power might be good enough, an expert said.
Oracle’s tech aims to weed out and fix vulnerable bits of code in software.
A recent patent is just one representation of its massive push toward agentic AI.
You may get left behind if you delay adoption of AI until its problems are solved, said ServiceNow’s Paul Smith.
“It’s not OK to leave any part of your business behind.”
While these machines provide the “awe factor,” they may serve little purpose for enterprises, one expert said.
When it comes to ethics, “the tone is set at the top.”
Enterprises are reeling from the growing cost of infrastructure and cloud.
The company may want its models to be the default in the developer community.
“You have to be tracking open source as an option.”
With less safety regulation and more infrastructure, AI companies are ready to sprint.