"AI failures"

More than 600,000 police reports have been written with help from Axon’s AI tools. Public records obtained by Forbes show that they can intr...

Many enterprise AI outputs look polished and authoritative until you peel back the top layer and realize there isn’t much substance.

In the next wave of healthcare AI, differentiation will turn less on model sophistication and more on the quality and structure of the clini...

If AI adoption is lagging or not bringing any real value, the problem might be your operating model.

AI models without strong business context risk costly errors, but vendor approaches to “context” vary. Enterprises must take ownership of th...

Where execution breaks down is in the tension I’ve been calling FOMO (fear of missing out) versus FOMU (fear of messing up).

AI systems rarely fail for one reason; they fail when real-world conditions introduce complexity that teams did not fully account for during...

Start by figuring out if the systems organizations build around AI are designed to produce trustworthy outcomes. That's an architectural que...

While the model is often the first suspect for AI pilots stalling, the architecture is the more likely culprit.

Organizations need people who can turn AI capability into secure, measurable, governed production systems.

Meta has since fixed the exploit, but it's yet another example of AI doing it worse than humans.

Modern institutions increasingly govern through representations of reality rather than direct contact with reality itself.