Pitfall radar
What is going to go wrong in our programme, and what will it cost?
Deterministic rules applied to your maturity profile. Each detected pitfall states the exact condition that produced it, its probability and its cost.
- ≈ 2 min
- 100% free · no AI · nothing is sent
- You leave with: Detected pitfalls, their weighted cost and the fix for each
Where you stand, axis by axis
Score each axis from 0 to 4. Pitfalls appear when particular combinations occur — deployment running ahead of governance, for instance. These are not generic warnings: each one states the exact condition that produced it.
Usage charter, approved tools, GDPR compliance.
Training received, genuine team autonomy.
AI connected to real data and business systems.
Signed DPAs, partitioning of sensitive data.
Breadth of use, measurement, steering.
The sum of the 6 detected pitfalls, each weighted by its probability. This is the amount to provision, not the amount to fear.
What was detected
Integration targeted without engineering capacity
High50 %What triggered it: Target of 3/4 against current integration at 1.0/4.
Moving from a generic assistant to AI connected to real business data is an engineering project, not a licence purchase. With no internal capacity, the estimate slips on the least predictable part of the programme.
What to doScope one integration end to end before promising five. The first connector reveals the true state of the data; the ones after cost a fraction of it.
- Impact if it lands
- €60,000
- Weighted cost
- €30,000
The pilot that never scales
Medium50 %What triggered it: 120 people, deployment at 2.0/4 — experiments running with no path to scale.
Pilots succeed because they run on enthusiastic volunteers under close attention. Neither survives the scale-up, and a result obtained with fifteen people does not reproduce with three hundred.
What to doChoose the pilot for representativeness, not enthusiasm: an average team with its real constraints. A pilot that succeeds with difficulty predicts far better than one that succeeds easily.
- Impact if it lands
- €45,000
- Weighted cost
- €22,500
Timeline shorter than the work
Medium55 %What triggered it: 8.5 level-steps to close in total, planned over 12 months. An absorbable pace is closer to 14 months.
Either the scope quietly narrows, or the date holds at the price of unbudgeted external help. Either way the gap gets paid for; the only choice is which budget line it lands on.
What to doSpread over 14 months, or cut the target to what fits in 12. Prioritise Governance and Security: they are the only axes where delay costs more than waiting.
- Impact if it lands
- €30,000
- Weighted cost
- €16,500
It all rests on one person
Medium35 %What triggered it: Use is established (deployment 2.0/4) while collective skill is low (1.5/4) across 120 people.
That gap is the signature of capability concentrated in a few individuals rather than spread. Their departure takes the practice with it, and the training budget then re-buys what already existed.
What to doDocument what works — prompts, procedures, worked examples — and have those people run the training rather than an external provider. Transfer becomes a deliverable instead of a hope.
- Impact if it lands
- €25,000
- Weighted cost
- €8,750
Security debt on data
High9 %What triggered it: Security at 1.0/4 across 120 people with access to AI tools.
With no signed DPAs and no data partitioning, confidential or personal information passes through third-party services with no documented legal basis. The incident is not certain; its cost, if it happens, is known.
What to doSign DPAs with the chosen vendors, turn on the no-training settings, and update the processing register. A few days of legal and technical work.
- Impact if it lands
- €60,000
- Weighted cost
- €5,400
- Cost to prevent
- €9,000
Deployment ahead of governance
High40 %What triggered it: Deployment at 2.0/4 against governance at 1.0/4 — a 1.0-point gap.
Practice sets before the rules do. Compliance work then lands on established habits: withdrawing tools people already rely on, reconstructing what data went where, and redoing work produced outside the framework.
What to doPublish a usage charter and an approved-tool list BEFORE widening the rollout. Two to three weeks of work, against a remediation measured in months.
- Impact if it lands
- €10,800
- Weighted cost
- €4,320
- Cost to prevent
- €12,000
These pitfalls come from deterministic rules, not from a language model. The same profile always gives the same result, and a healthy profile produces none — that silence is what makes the list useful. The probabilities are calibrated judgements, not measurements: they exist to rank risks against one another and to give a basis for provisioning, not to predict an event.
What the calculation does, what the AI does
Every figure on this page comes from a deterministic algorithm running in your browser: the same input always gives the same result, and nothing is sent to produce it. This tool uses no language model at all: every sentence shown is written into the rule that triggered it.
Where to go next
See all 19 tools →- GDPR exposure
What is ungoverned AI use already costing us?
≈ 2 min · The annual risk in euros, against the cost of compliance - EU AI Act
Is our system high-risk, and what does that oblige us to do?
≈ 4 min · The classification and the applicable obligations, article by article - Assess vendors
Which vendor should we trust with our data?
≈ 5 min · A ranking of vendors, knock-outs included - Cost calculator
What does our AI transformation actually cost, and when does it break even?
≈ 3 min · A line-by-line budget, the return and the break-even month - AI usage policy
Our teams already use AI: what rules do we give them, in writing, this week?
≈ 4 min · A complete AI usage policy, ready to sign - Roadmap
In what order, and over how long?
≈ 3 min · Quarterly phases and what each one delivers