Can AI answer the $3 trillion question?
THE SO WHAT
The $3 trillion AI ROI debate is shifting from “can it” to “how fast and where first”—timing risk is now as important as technology risk. Operators should be explicit about which AI bets are near‑term P&L moves versus long‑dated options, and fund them from different buckets.
READ THE SOURCE
MORE FROM THE WIRE
Applied AIOpenAI says GPT 5.6 is the ‘preferred model’ for Microsoft Copilot amid breakup chatter
Despite breakup narratives, OpenAI publicly anchoring GPT‑5.6 as the preferred Copilot model keeps the Microsoft–OpenAI enterprise stack effectively unified for now. If you're building on Copilot, plan for continuity in OpenAI-based behavior over the next cycle — but keep a contingency path for multi-model support as strategic optionality pressure rises.
Applied AIEmerging: AI Sovereignty Isn't "Self-Sufficiency"
The sovereignty conversation is shifting from "build everything at home" to "control critical dependencies" — smart interdependence instead of isolation. If you're selling AI infra or services cross-border, expect more questions on data residency, model control, and local ecosystem participation rather than pure onshore build demands.
Applied AIThree questions to ask yourself before you ask AI
The emerging best practice is not "use AI everywhere" but "be explicit about when to delegate, what context to share, and how you'll verify." For internal rollouts, codify decision heuristics like these into lightweight playbooks — it reduces misuse risk and raises the quality of prompts without more tooling.
Applied AIFidji Simo steps down from leading OpenAI’s AGI work due to illness
Leadership continuity at the AGI program level matters for partners planning multi-year bets on a single lab’s roadmap. If you're tightly coupled to any one research org, map where your dependencies sit on specific leaders versus institutional processes — and build slack for leadership transitions into your risk model.