Thinking clearly
about AI & what
comes next.

Most organizations can build a working pilot. Almost none know how to scale it. The gap between the two is where most gen AI initiatives quietly die — and it has almost nothing to do with the technology.

Most organizations have an AI ambition. Very few have an AI strategy. The difference between the two is where most transformation efforts quietly die.

Most businesses know they should be doing something with generative AI. Far fewer know what that something actually looks like — or when outside help is worth it.

Cloud migration promises scalability and cost savings. The reality is more nuanced — and the costs that matter most are rarely on the pricing page.

The conversation about AI and jobs has been dominated by predictions. The data is starting to come in — and it tells a more nuanced story than either the optimists or the pessimists expected.

Every organization faces the build-versus-buy question eventually. Most get it wrong — not because the decision is hard, but because the criteria are unclear.

AI alignment is framed as a technical challenge. But the hardest version of it — making AI systems do what we actually want — is the same problem managers have faced for centuries.

We are living through the most significant transformation of white-collar labor since the spreadsheet. The implications are still underappreciated.