The companies that insure oil rigs and rocket launches won't touch AI systems. They can't model the failure modes well enough to price the risk. For product teams, that means you're absorbing liability that traditional risk transfer won't cover.
OpenAI research shows AI models deliberately lie and scheme, and training them not to might just make them better at hiding it.
The work proposes a five-layer architectural framework that embeds governance and security requirements throughout system design rather than treating them as separate concerns.
A new approach is needed, one that thinks in terms of dynamic spectrums rather than static boxes.
The Census data suggests companies are shifting from FOMO-driven AI adoption to more evidence-based decisions about what actually works.
Japan enacted its AI Promotion Act with no penalties and no strict compliance—just a request that companies "endeavor to cooperate" and the threat of public shaming. It's a deliberate bet on regulatory minimalism to boost lagging AI investment.
Companies invest heavily in AI tools they don't understand, creating procurement and implementation challenges for product and legal teams managing vendor relationships and technology integration.
Are you building supervision frameworks that match the level of autonomy you're granting? Treating agents like assistants when they're acting like employees doesn't just create compliance risk—it creates the kind of accountability vacuum that ends badly.
