Thought leadership
Notes from the middle of it.
Working notes on where AI capability, cost and adoption actually are — written for people who have to make decisions with them. Every figure is redrawn from published data and carries a table view, and where a source contradicts itself we say so on the chart rather than quietly picking a number.
Published pieces
The enterprise becomes programmable.
AI capability and cost moved further in twelve months than most operating models did. The constraint is no longer access to intelligence; it is how the enterprise is designed to use it. Interactive, fully sourced and built to present.
- 8shiftsin what AI can do and what it costs
- 6decisionsfor the leadership team, each with a suggested owner
- 90daysan agenda to assign, then copy as a brief
Open the briefingOr start in a reading mode
Frontier capability stopped being the bottleneck.
The price of frontier-class intelligence fell by roughly two orders of magnitude in thirty days, while the five leading models converged to within nine index points of each other.
- 137× spread in cost per task across the board
- More reasoning effort is a cost multiplier, not a quality dial
- 84% of the world has never used a model at all
Adoption is universal. Impact is not.
Almost everyone is using AI and a minority can find it in the P&L. The separation comes from redesigning the operating model, running agents under real controls, owning the intelligence layer, and building rather than renting.
- 88% use AI regularly; 39% see enterprise EBIT impact
- Under 12% of companies have AI-ready data
- The operating layer is the only tier where advantage compounds
Stop treating AI like a smart intern.
It stopped being a sidecar for note-taking and became an execution layer. What separates the next twelve months is cycle time, execution quality and the distance between a decision and the work that follows it.
- A 30-day operating review beats a 6-month pilot
- Anything built a year ago is almost certainly overspending
- Five moves, each with an owner, a clock and a target
The model is not the moat.
Access to a frontier model stopped being a differentiator the moment every serious competitor had the same access. What separates companies is the layer above it.
- The moat moved to the context layer
- Managed autonomy, not full autonomy, is what is working
- Software increasingly gets built rather than bought