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Insights & Perspectives
Field notes from our ISO/IEC 42001, EU AI Act and CMMI engagements — written for the people who have to make AI defensible, auditable and useful at the same time.
Most organisations treat 42001 as a documentation exercise. The ones that certify on the first attempt treat it as an operating-model change — and start with the inventory, not the policy.
Seven articles define what a high-risk AI system must do. Translated out of legal language, they are a product requirements document — and they are all testable.
Seven dimensions, one board-legible index. Why 70–85% of enterprise AI initiatives stall for organisational reasons, not technical ones.
Autonomy is only safe when it is attributable. The passport model borrows from identity management to make agentic systems auditable from day one.
A one-day structure for getting risk, legal, engineering and the business into the same register — and out with an owned treatment plan.
Process maturity did not become irrelevant when engineers started pairing with models. It became harder to evidence — and more valuable to hold.
A decision-support tool that is never questioned is a decision-making tool wearing a disguise. Designing for productive disagreement.
People can tell when a transformation programme has an unstated headcount thesis. Saying it out loud, early, is the difference between cooperation and quiet sabotage.
The strongest evidence that a governance methodology works is that the people selling it operate under it.
If you have 500 employees, you probably have 500 unsanctioned AI pilots running right now — and the largest exposure is not data leakage, it is unaccountable decision-making.
A folder full of downloaded compliance templates is not an AI Management System — it is a costume. Certification bodies have gotten very good at spotting the difference in the first hour.
The Digital Omnibus on AI entered into force on 27 July 2026 and pushed the high-risk regime out by sixteen months — but left untouched the obligations most likely to touch your business, which land on 2 August 2026.
Your board does not want to hear about model parameters. It wants to know whether the organisation can demonstrate that its AI is fair, transparent, and overseen — and under ISO/IEC 42001, that obligation sits with top management by design.
Building governance into the AI lifecycle from day one costs a fraction of retrofitting it — the difference between a planned workstream and a hostage situation.
Everyone is talking about AI regulation. Far fewer can answer the follow-up: how do you actually prove you are governing AI responsibly? That is the specific job ISO/IEC 42001 was built to do.
For the Defense Industrial Base, the self-attestation era is over. CMMC 2.0 turns cybersecurity from something you assert into something an independent assessor verifies — and the consequence of failing is ineligibility, not a fine.
CMMI has an image problem. V2.0 is performance-focused, Agile-compatible, and for organisations selling into defence or government, Level 3 is frequently the difference between bidding and not bidding.
Running ISO 9001, ISO 27001 and ISO 42001 as three separate programmes is one of the most expensive avoidable mistakes in corporate compliance. They share a skeleton — most organisations pay three times to build it.
ISO/IEC 42001 Clause 6.1 requires two distinct assessments. AI risk asks what could go wrong for the organisation. AI impact asks what could go wrong for everyone else. Confusing them is the most common gap we find.
Your best engineers did not join to fill out duplicate compliance spreadsheets. When you run SOC 2, ISO 27001, GDPR and AI governance as separate programmes, the cost lands in your attrition numbers.
I spent 21 years leading digital transformations from the inside — which means I have been on the receiving end of the deliverable that looks impressive, satisfies the statement of work, and quietly fails six months after the consultants leave.
AI is moving faster than the talent pool can adapt. Average time-to-hire for AI compliance roles now exceeds six months — and that is before you have decided what the role should actually do.
I speak to founders every week who have stalled their AI rollout because they are afraid of the compliance exposure. The irony is that the fear costs them more than the compliance would have.
Good governance pays for itself — and the mechanism is not mysterious. The outcome of a CMMI appraisal or an ISO certification is a measurable reduction in the work you were doing twice.
There is a widening gap in the market: large enterprises get governed AI because they have the leverage to insist on it. Everyone else gets a click-through terms page. We built the gnaan.ai suite for the second group.
In most applications, a confidently wrong AI output is an annoyance. In legal drafting and compliance management, it is a case, a client, or a certification. LegalSense™ and AuditSense™ were designed around that constraint from the first line.
EduSense™ handles student records. MindSense™ handles employee mental wellbeing. These are two of the most sensitive data categories in existence — which makes them the right places to demonstrate that governed AI can carry real responsibility.
Stop wondering whether your AI systems are compliant. Our AI Governance Readiness Assessment is complimentary, takes forty-five minutes, and is led by a Senior Lead Auditor. There is no deck.
Leaders do not lack AI ambition. They lack a defensible way to prove it is under control. Twenty articles later, this is still the only problem worth solving.
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