The value here comes from role clarity, not just access to AI.
Vendors who treat the runtime environment as someone else’s problem are betting their reputation on strangers.
The most expensive mistake I see leaders make is treating the shift to a new way of working as a training sprint that wraps when the system goes live.
How do organizations safely deploy AI systems that take action, make decisions and influence business outcomes at scale?
Sometimes, the best response for a predictive ML system is to pause, acknowledge that it does not have enough information and escalate the case to a clinician.
The pressure for proven data lineage is arriving from several directions at once.
The ability to recover institutional knowledge is only as valuable as the organization’s ability to keep it current.
The challenge with AI in finance is that it has no inherent concept of accountability or consequences.
Samsung debuts new connected Slide-in Ranges and an Over-the-Range Microwave featuring Air Fry Max, but skips Matter support in favor of SmartThings
What happens when intelligence begins optimizing for the future instead of preserving the past?