10 posts tagged with "AI"
The same CEOs who sold boards on replacing people with AI are now walking it back. The receipts from Microsoft, Nvidia, Uber, and the BLS say what I've been saying all along: AI is a tool that makes talented people better, not a one-for-one swap for them.
The industry keeps promising AI will get cheap. The math doesn't support it, and leaders planning on cheap-AI as a future certainty are walking into a wall they can't see. Three structural reasons the cheap-AI forecast can't be defended.
Boardrooms are pricing engineering as a token line item. The math looks like obvious arbitrage — until you check what the spreadsheet is missing. Three holes in the assumption, with receipts.
Anthropic tested 16 frontier models and found that instructions alone don't prevent harmful behavior. The implications for every organization deploying AI agents are severe — and most aren't ready.
Token spend is the new cloud bill — except it's growing faster, harder to predict, and almost nobody has governance around it. Here's what the shift from compute-based to intelligence-based costs means for data leaders.
AI is making software nearly free to build. But the companies winning the next era aren't the ones shipping fastest — they're the ones customers trust most. Here's why the shift from SaaS to Outcome as a Service changes everything.
Every company says data is strategic. Almost none of them fund it like it is. Here's what happens when you treat your data organization as a cost center — and how to fix it before the crisis forces your hand.
Everyone is focused on AI models getting smarter. Almost nobody is talking about the hardware crisis that could stop AI scaling dead in its tracks: overheating chips, melting data centers, and the death of Moore's Law.
AI-generated code is flooding codebases everywhere. But what happens when the developers who inherit this code can't read it, can't debug it, and can't explain why it exists? We might be creating a technical debt apocalypse.
Every enterprise is running AI pilots. Almost none are reaching production. Here are the 10 systemic traps that kill corporate AI initiatives — and what leaders can do about it.