Not forecasts, not opinion borrowed from the feed. This is that reading, in the open: the world examined along every dimension that decides an institution’s next decade — and a place to bring the question it raises for yours.
The evidence sits on both sides at once. MIT finds 95% of enterprise AI initiatives produce no measurable impact on the P&L; RAND puts project failure near 80%. Yet in the same window, DBS attributes over S$1bn of value to AI, and JPMorgan discloses material uplifts with its method shown. Same technology, opposite results.
The difference is what the few asked first. Not which tools do we deploy, but given what intelligence now costs, what should this business become — and then they rebuilt to receive the answer. It is a question of business architecture, not of technology — which is exactly why it is available to anyone willing to ask it.
How the role of leaders changes in the AI world — what a leader stands on when everything is in motion, what institutions owe their leaders, and what you owe yourself.
The Chief AI Officer is the fastest-growing seat in the C-suite — and the one its own holders doubt
On the RBI’s draft model-risk framework — and what it actually asks of boards
Why no nation owns the AI stack — and the deliberate path to standing where it matters
The reasons everyone gives — and what the data says is actually driving it
Why we are looking for 1940s signals in a 2020s structural conflict
The hedge that defined a generation of portfolios has inverted
What can’t be written is the judgement of using it inside your own institution — in your room, against your numbers, with your people. That is not a document. That is the conversation.
No intake process, no gatekeeper. A note reaches me directly, and I reply myself — usually within a day or two.
It comes straight to my inbox, and I reply personally — usually within a day or two.