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AI Governance & Cyber Strategy

Policy and model-risk frameworks, red-teaming of LLMs and agents, and board-level security strategy that survives contact with budget.

AI RED TEAMPOLICYBOARD
Overview

What the practice does.

AI is in your business whether or not it is in your policy. Staff are pasting data into assistants, vendors are shipping models inside products you already pay for, and someone is about to connect an agent to a system that matters.

We help you govern it without stopping it: a usable policy, a model and vendor risk process, testing that shows what the systems actually do under pressure, and a security strategy the board can fund.

What you get

Deliverables.

Each item is something you keep: a document, a register, a plan. All of it is scoped and priced before the work starts.

01

AI use and governance policy

What is allowed, with which data, through which tools, and who approves exceptions. Aligned to ISO/IEC 42001 and the NIST AI Risk Management Framework where you need the mapping.

02

Model and vendor risk assessment

A repeatable way to assess an AI feature, model or vendor before it goes live: data flows, retention, training use, access, and the controls that close the gaps.

03

LLM and agent red team

Adversarial testing of your assistants, copilots and agents: prompt injection, data exfiltration, tool misuse, permission abuse, and the guardrails that fail under pressure. Findings are reproduced and scored like any other test.

04

Cyber strategy and roadmap

A three-year security strategy in business language: risk appetite, priorities, budget, metrics and the sequence of work, written to be approved rather than admired.

05

Board briefing

A short briefing and a question set so directors can oversee cyber and AI risk with confidence.

How it runs

The four steps, applied.

The method is the same for every practice. This is what each step means here.

01 / SCOPE

Which systems, models, agents and decisions are in scope, which data they touch, and what the board needs to decide.

02 / TEST

Policy and process review, data flow tracing, and hands-on adversarial testing of the AI systems in scope.

03 / VERIFY

Every finding is reproduced by a second analyst. Policy recommendations are checked against the frameworks you have to answer to.

04 / REPORT

Governance documents ready to adopt, a scored findings report, and a strategy and roadmap with a budget case.

When to call us

The situations this is built for.

You have AI in production and no policy

Teams are already using assistants and agents. You need rules that are specific enough to follow and short enough to read.

A vendor or customer is asking about AI risk

Procurement questionnaires now ask how you govern AI. You need an answer that is true.

The board wants a strategy, not a tool list

Security spend has grown without a plan behind it. Leadership wants priorities, a budget and measures of progress.

Questions

Asked before most engagements.

Do you test AI systems or only write policy?

Both. Policy without testing is a document; testing without policy is a list of bugs. Most engagements include a red team of the systems that matter most.

Which frameworks apply to AI governance?

ISO/IEC 42001, the NIST AI Risk Management Framework, and the privacy laws that already apply to your data, including PIPEDA and provincial legislation in Canada. We map to what your customers and regulators will ask about.

How long does a strategy engagement take?

Typically six to ten weeks: discovery, interviews, drafting, a review cycle with leadership, and a board presentation.

Request a quote

Tell us what you need tested, assessed or governed.

A consultant, not a sales team, replies within one business day with a scope and a fixed price. For self-serve testing, go straight to Frontier Verify.

Start on Frontier Verify