The AI burn book: Decoding the cat fights between Sam Altman, Elon Musk, and Anthropic
THE SO WHAT
Public friction between high-profile AI leaders is less about personalities and more about competing narratives on pace, control, and risk. Operators should read these spats as early indicators of where regulation, capital, and talent might polarize—not as day-to-day operating guidance.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIFrom pilot to production: How scaling companies are making AI work
The gap between AI pilots and production is now mostly about process and ownership, not models. If you don't have a clear path from experiment to P&L impact, your 'AI strategy' is just a demo reel.
Applied AI‘We want to make bookkeeping less painful’: How Visma and its AI portfolio are reshaping accounting
Accounting is turning into a human-in-the-loop QA layer on AI workflows rather than manual data entry. Finance leaders should be piloting AI-native tooling now, or risk being locked into legacy systems while competitors compress close cycles and headcount.
Applied AIMany businesses are deploying AI faster than they’re preparing employees — leading to an 'AI underclass' at some firms
Rolling out AI faster than you upskill staff creates a two-tier workforce—those who can leverage the tools and those who are displaced by them. This week, audit where AI has landed without training or process redesign; that's where adoption will quietly stall or backfire.
Applied AIMost enterprise AI governance is already out of date
Static AI governance frameworks are breaking under the pace of model and use-case change—policy has to become a living, operational function, not a PDF. If your AI governance hasn’t been updated in the last 6–12 months, treat it as a risk, not a checkbox.