The problem it solves
In 2026, the question isn’t whether to use AI. That decision has already been made in most boardrooms. The questions being made now are which AI, how fast, and how much.
That’s the wrong level to pressure-test.
Most AI initiatives fail not because of the technology but because of the reasoning that preceded it. “AI will make us more efficient” — efficient at what, exactly? “We’ll lose competitive advantage if we don’t act” — compared to whom, on which dimension? “Our people are resistant to AI” — or are they noticing something the strategy missed?
These aren’t rhetorical questions. They’re the questions that should have been asked before the initiative started — and can still be asked before the next phase of investment.
What this assessment is not
It is not an AI strategy consultation. I won’t tell you which tools to adopt, which vendor to choose, or how to manage your rollout. There are plenty of people who will do that — most of them with a stake in your answer.
This assessment does one specific thing: it finds the assumptions your AI strategy depends on and asks whether any of them deserve scrutiny before you spend more on them.
How it works
You share the relevant documents — the vendor proposal, the internal roadmap, the strategic rationale, whatever exists. We spend one structured call working through the specific AI decision: what you’re planning, what you’ve committed, what assumptions are driving it.
Over 5–7 working days, I work through the initiative systematically. Every vendor claim examined. Every internal assumption named. The strongest available counter-evidence applied to each.
You receive a written assessment. Clear verdict. Documented reasoning.
Who runs the assessment
André Daus — 15 years of structured adversarial analysis across financial services, technology, and organisational strategy. Not an AI vendor. Not an implementation partner. No stake in your choice of tooling.
"Everyone is being told to act on AI. Hardly anyone is being told which assumption is wrong."
What you leave with
Not deliverables. Capabilities and clarity.
- A documented assumption map Every belief your AI strategy depends on, named and examined — including the ones nobody in the room had stopped to question.
- Tested vendor claims The specific claims in the vendor proposal or internal roadmap, assessed against available counter-evidence and the most relevant failure cases.
- A written verdict Clear documented recommendation: proceed, pause, or rethink — with the reasoning documented for your board, leadership team, or internal record.
- Priority-ranked risks Which assumptions, if wrong, would do the most damage — and which parts of the strategy are actually solid.
Good fit / not a fit
- Good fit: You're about to commit significant budget A board has approved an AI initiative. A vendor contract is on the table. You want someone with no stake in the decision to examine the reasoning before more budget goes in.
- Good fit: Something about the initiative doesn't add up The logic sounds right. Everyone is aligned. But something nags. You need someone to take the reasoning seriously — not to reassure you, but to find what you're missing.
- Good fit: An initiative is underway and results aren't landing The tools are in place. The training happened. Adoption is low or outcomes don't match the pitch. Before you invest more, you want to understand whether the problem is execution or diagnosis.
- Not a fit: Not a fit AI vendor selection, technical implementation, or change management. This assessment examines the reasoning behind the initiative — it does not execute it.
Try it free first
Paste an AI offer or proposal and get a first assumption breakdown emailed back — a live demo of exactly this kind of analysis.
Run a free assumption check