Senior advisory for AI that legal, risk, and engineering all approve.
We help legal, risk, and engineering leaders move AI through governance, EU AI Act readiness, model risk management, bias auditing, and the documentation that gets a high risk system over the line.
Where we sit in
your governance stack.
We work alongside your DPO, GC, CISO, and CTO, translating regulatory ambiguity into engineering decisions, and engineering reality into something your board can sign off.
EU AI Act Readiness
Risk classification, conformity assessment support, technical documentation, and post market monitoring frameworks for high risk systems.
Model Risk Management
SR 11 7 / NIST AI RMF aligned model inventories, validation regimes, challenger frameworks, and ongoing monitoring controls.
Bias & Fairness Audits
Statistical and qualitative audits across protected attributes, with remediation plans your engineering team can actually execute.
AI Governance Frameworks
Policies, intake processes, review boards, and escalation paths, designed to fit your existing risk and compliance machinery.
Vendor & Model Risk Review
Independent reviews of external AI vendors and foundation models, covering data flows, IP risk, and contractual gaps.
Executive Education
Briefings and workshops for boards, exec teams, and risk committees, translating AI capability and risk into decisions they can make.
Moments that turn AI governance from a slide into a mandate.
Nobody budgets for AI governance in the abstract. A deadline, a questionnaire, a board question, or an uncomfortable audit finding makes it concrete. These are the six moments that bring legal, risk, and engineering leaders to this practice.
The Deadline Landed on Your Desk
The EU AI Act's high risk obligations are no longer a policy paper, they are conformity assessments, technical documentation, and logging requirements with dates attached and fines behind them. We run the readiness program end to end: classify what you own, map obligations to your systems, and produce the documentation a market surveillance authority accepts. When the gap is architectural rather than procedural, the build work runs through our GDPR compliant AI practice, so the advice and the engineering come from the same map.
The Enterprise Customer Sent an AI Questionnaire
The newest deal killer: a prospect's procurement team sends forty questions about your AI governance, bias testing, and incident processes, and the deal freezes until the answers exist. We build the governance evidence that turns that questionnaire from a threat into a differentiator, and for vendors selling into government or regulated buyers, we run the ISO 42001 path that increasingly appears as a contract requirement. Deals should close on product, not stall on paperwork you could have had ready.
The Board Asked Who Owns AI Risk
C-suite surveys now rank regulatory non-compliance as the top AI risk, and boards are asking a question most organizations cannot answer cleanly: who is accountable when a model makes a consequential mistake? We design the governance operating model, intake, review board, escalation, and ownership, sized to your risk appetite rather than lifted from a template, and we brief the board in the language of decisions, not architecture. Governing AI agents that act autonomously raises the stakes on every one of those answers, and we design for that reality rather than the chatbot era the templates were written for.
Model Risk Management Meets Generative AI
Banks and insurers have run SR 11-7 model risk programs for a decade, and generative AI just broke most of their assumptions: models that update behavior without retraining, outputs that resist point validation, and vendors who will not hand over documentation. We extend existing MRM frameworks to cover LLMs and agents, aligned to NIST AI RMF, so your second line can validate what your first line is shipping without inventing a parallel bureaucracy.
The Bias Audit You Cannot Run on Yourself
Hiring, credit, insurance, and access decisions increasingly carry audit obligations, and an internal team grading its own model convinces no regulator and no plaintiff's counsel. We run independent statistical and qualitative bias audits across protected attributes, and the deliverable is not a verdict, it is a remediation plan your engineers can execute and a documentation trail that stands up when an affected individual exercises their right to an explanation. Where the audit needs adversarial depth, our AI and LLM security testing team probes the same systems from the attacker's side.
The Vendor Nobody Assessed
Your teams have already adopted AI vendors and foundation models that no one reviewed: data flows unmapped, IP terms unread, and, in the sharpest trap, fine tuning arrangements that can quietly reclassify your company from deployer to provider under the AI Act, with the full obligation stack attached. We run independent vendor and model risk reviews before the contract, and triage of the ones already signed, because the cheapest time to find these problems is before a regulator or an acquirer does.
87 Percent Have a Framework. Fewer Than 25 Percent Made It Real.
Deloitte's finding is the quiet scandal of AI governance: nearly nine in ten executives claim frameworks, while fewer than a quarter have operationalized them. A policy PDF that no workflow enforces is not governance, it is future evidence of what you knew and did not do. Our engagements end when the framework is running inside your intake, your tooling, and your review cadence, applied to a real high risk system first, because that is the difference between having governance and having a document.
The Bottleneck Nobody Budgets For: Qualified People.
The honest market condition in 2026: genuinely qualified AI governance practitioners are scarce, ISO 42001 certification bodies carry lead times measured in months, and compliance talent commands salary premiums. This is not a sales line, it is a planning fact: if a deadline, a certification, or a major deal sits in your next two quarters, the scarce resource is calendar, and starting the diagnostic now is cheaper than paying rush premiums later.
From audit to approved system.
Most consulting deliverables die in PDFs. We work hands on with your teams so the framework actually changes how AI ships at your company.
Diagnostic
We inventory your AI systems, map them to regulatory exposure, and identify where governance is thinnest.
Framework Design
Policies, processes, and templates tuned to your risk appetite, not lifted from a generic compliance vendor.
Pilot Application
We apply the framework to one real high risk system, proving it works before you roll it out across the company.
Operationalize
Train your teams, embed the workflow into your tooling, and establish the governance cadence for ongoing reviews.
What AI governance actually costs, and where the budget does the most good.
This corner of consulting is famous for six figure engagements that produce a binder. Here are the real market numbers, the honest sequencing, and the question your engineers are already asking about all of this.
Industry benchmarks put ongoing compliance for a single high risk system at roughly €30,000 to €52,000 a year, with conformity assessments running €5,000 to €50,000 per system where required. Two numbers matter more than those. First, misclassification adds an estimated 20 to 40 percent to compliance outlays, which is why classification comes before any other spend. Second, around 85 percent of AI systems fall into the minimal risk tier with no significant obligations, meaning the realistic budget is concentrated on the two or three systems that genuinely qualify as high risk, not spread across everything with a model in it. The diagnostic exists to find that short list before the spending starts.
Increasingly yes, for one commercial reason: enterprise and government buyers are writing it into contracts, which converts a voluntary standard into a sales requirement. First year certification runs roughly $85,000 to $150,000 for smaller organizations and $180,000 to $320,000 at mid market scale, with a gap analysis at $5,000 to $15,000 telling you your real starting point. Two honest levers change the math: an existing ISO 27001 program roughly halves the cost and timeline because the management machinery transfers, and implementing the framework without formal certification captures most of the governance value while skipping audit fees, a legitimate path when no customer is demanding the certificate yet. We tell you which path fits before you commit to either.
Because enforcement and procurement both ask for evidence, not intentions, and the gap between the two is enormous: 87 percent of executives claim AI governance frameworks while fewer than 25 percent have operationalized them. A policy becomes governance when there is an intake every new AI use case passes through, a review that can actually say no, logs that prove the controls ran, and a named owner when something goes wrong. In an investigation, an unenforced policy is worse than none, it documents that the organization identified the risk and did not act. Our pilot application stage exists precisely to convert your policy into running controls on one real system before the rollout.
Fewer than you fear, and studies suggest around 40 percent of enterprise AI systems currently sit unclassified or misclassified, which is where both over spending and exposure hide. The triage is concrete: systems touching hiring, credit, education, essential services, biometrics, or safety functions likely land in the high risk tier with real obligations. Chatbots and generated content carry transparency duties. The large majority, recommendation engines, internal copilots, forecasting tools, sit in minimal risk. One classification exercise, typically days not months, replaces the anxiety with a short list and a budget that matches it.
Run badly, absolutely, and your engineers are right to fear it. Run properly, it does the opposite, because the alternative to governance is not speed, it is the stall: legal blocking launches ad hoc, procurement questionnaires freezing deals, and one incident triggering a company wide AI pause. A functioning intake gives builders a fast lane for low risk work, clear requirements for high risk work, and a decision in days instead of a debate every quarter. The proof point is structural in how we engage: the framework is applied to one real system before rollout, and if it cannot ship that system faster than the ad hoc chaos did, it is not finished.
The inventory and classification, without hesitation, because every other decision depends on it and it is the cheapest step in the entire program. Knowing which of your systems carry real obligations converts an unbounded anxiety into a scoped project, prevents the 20 to 40 percent misclassification premium, and reuses work you have already paid for, since mature GDPR and ISO 27001 programs cover a substantial share of what AI governance requires. Most organizations discover the delta is half the project a generic vendor would have sold them. That finding alone usually funds the rest.
The 30 minute diagnostic asks one question your organization should be able to answer today and probably cannot: how many AI systems do you run, and which ones could hurt someone? Come find out how close you are.
Questions about
Regulatory AI Consulting
No. We're engineers and risk practitioners. We work alongside your legal counsel and translate regulatory requirements into engineering, data, and operational decisions.
Yes. We work across EU AI Act, NIST AI RMF, ISO 42001, SR 11 7, and emerging US state laws (Colorado, NY), and design frameworks that span jurisdictions if you operate globally.
We're senior practitioners, no juniors writing slide decks. And we ship working code alongside the framework, so the policy actually constrains what gets deployed.
Yes. We routinely participate in regulator briefings, audits, and conformity discussions when the technical detail matters.
From a four week diagnostic to a six month framework build with embedded coaching for your governance team. We scope to the actual problem, not a packaged offering.
Stop experimenting.
Start deploying AI that works.
Book a free 30 minute briefing with a senior practitioner. We'll diagnose where your governance is thinnest and what to do first.
info@croncore.com