Description

A focused course, tailored for you

Frontier AI Governance: From Capability Evaluation to Regulatory Submission

Build the governance artefacts that turn a frontier model's capability profile into an auditable regulatory submission package.

Your red-team findings, capability evaluations, and risk assessments exist as separate documents. The EU AI Office's GPAI technical file requirement asks you to integrate them into a single auditable package with a named accountability chain. Nobody on the governance team has done this before, and the documentation deadline doesn't move.

$199 one-time

Tailored to your situation. Access within 24 hours. 30-day money-back.

Includes a hand-built implementation playbook delivered alongside course access, generated for your specific situation.

Why this course

Frontier AI governance roles carry a specific accountability trap. The capability evaluation team produces rigorous outputs. The red-team produces detailed findings. Legal produces the policy commitments. But when the EU AI Office or the UK AI Safety Institute asks for a consolidated technical file, the governance professional has to integrate three separate workstreams into a coherent auditable package against a regulatory schema none of them designed for. The integration gap is where submissions fail or get delayed. The course teaches the integration skill, not the individual disciplines.

What you walk away with

Map frontier model capabilities to the specific threshold criteria in the EU AI Act GPAI provisions and equivalent national frameworks.
Integrate red-team evaluation outputs into a formal risk assessment that satisfies regulatory documentation standards.
Produce a model card that cross-references capability thresholds, evaluation methodology, and accountability assignments in a format auditors can verify.
Structure a GPAI technical file that meets the EU AI Office's documentation schema, including the required safety policy, capability evaluation record, and incident reporting mechanism.
Build an accountability chain document that maps governance responsibilities to named roles and survives regulatory scrutiny.
Run a pre-submission audit against the GPAI technical file checklist and close the gaps before the filing deadline.

The 12 modules

Module 1. The GPAI Obligation Map

Before building any artefact, you need to know exactly which obligations apply to your model's capability profile. This module maps the EU AI Act's GPAI provisions to the specific documentation triggers: systemic risk thresholds, compute thresholds, and the distinction between general-purpose and high-risk deployment contexts. You produce a one-page obligation register scoped to your model's current capability classification.

Module 2. Capability Evaluation Taxonomy for Governance Use

Capability evaluations produced by research teams are not in a format regulators can audit. This module teaches how to re-express a capability evaluation in governance terms: what the evaluation measured, against which benchmark or elicitation protocol, at which capability level, and what the threshold implications are. You produce a capability taxonomy table that becomes the spine of the GPAI technical file.

Module 3. Red-Team Output Integration

Red-team findings are typically structured as research outputs, not regulatory evidence. This module covers the translation: how to extract the risk-relevant findings, classify them by severity and deployment context, cross-reference them to your capability taxonomy, and express them in the risk assessment format the EU AI Office's documentation schema requires. You produce a red-team integration log that maps findings to regulatory artefacts.

Module 4. The GPAI Technical File Structure

The EU AI Office has published a documentation schema for GPAI providers. This module walks through each required section: the safety policy, the capability evaluation record, the red-team methodology summary, the incident reporting mechanism, and the compliance contact. You build a technical file shell with the correct section headings, cross-reference fields, and version control structure that a regulatory examiner expects to navigate.

Module 5. Model Card Auditing Standards

A model card that satisfies internal publication standards is not the same as a model card that satisfies regulatory documentation requirements. This module covers the gap: what the EU AI Office looks for when reviewing a model card (capability claims cross-referenced to evaluation evidence, threshold disclosures, known limitations in deployment-specific contexts), and how to audit your existing model card against those criteria before filing.

Module 6. Accountability Chain Documentation

Regulators require a named accountability chain, not an org chart. This module teaches how to produce an accountability assignment document that maps specific governance responsibilities (capability threshold monitoring, red-team commissioning, incident escalation, regulatory contact) to named roles with decision authority. The output is a one-page accountability matrix that can be filed as part of the GPAI technical file and updated when roles change.

Module 7. Threshold Monitoring and Change Management

GPAI obligations are not static. A model that falls below the systemic risk threshold today may cross it after a fine-tune or a deployment context change. This module covers the monitoring protocol: how to define the capability thresholds that trigger obligation review, what events require a documentation update, how to log capability changes in a way that produces an auditable version history, and when to notify the EU AI Office proactively.

Module 8. Downstream Deployer Obligations and the Governance Interface

GPAI providers have documentation obligations to downstream deployers, not just to regulators. This module covers the information package a deployer needs to satisfy their own high-risk AI obligations: the capability disclosure, the known limitations relevant to specific deployment contexts, and the terms-of-use clauses that shift accountability. You produce a downstream deployer information pack template scoped to your model's deployment contexts.

Module 9. Incident Reporting Mechanism Design

The EU AI Act requires GPAI providers to have a functioning incident reporting mechanism before a serious incident occurs, not after. This module covers the mechanism design: what qualifies as a reportable serious incident under GPAI provisions, what the reporting timeline is, what information the report must contain, and how to build the internal escalation chain that gets the right information to the regulatory contact within the required window.

Module 10. Engaging with the EU AI Office and National Authorities

The EU AI Office is the primary regulator for GPAI providers. This module covers the practical engagement model: how to respond to an information request, what a voluntary consultation looks like, how to manage a formal investigation under Article 90, and how to coordinate with national competent authorities when a downstream high-risk deployment is under scrutiny. You produce a regulatory engagement protocol for your governance team.

Module 11. Aligning with UK AISI, US EO, and Equivalent Frameworks

Frontier AI governance does not map to a single regulatory scheme. This module covers the overlap and the divergence between the EU AI Act GPAI provisions, the UK AI Safety Institute's evaluation framework, the US Executive Order's safety commitments, and Singapore's FEAT principles. You produce a cross-framework alignment table that shows which governance artefacts satisfy multiple schemes simultaneously and which require jurisdiction-specific additions.

Module 12. Pre-Submission Audit and Filing Checklist

The final module is a structured pre-submission audit. You run your assembled GPAI technical file against the EU AI Office's documentation checklist, identify gaps in cross-referencing, capability disclosure, or accountability assignment, and produce a gap closure plan with named owners and a timeline. The output is a submission-ready package and a signed-off audit log that documents the review process.

How this addresses your situation

Specific modules that map to what you said you are dealing with.

You have a capability evaluation report from the research team and a red-team findings document. Neither is in a format the EU AI Office's GPAI schema recognises. Modules 2-3 teach the translation.

Your internal model card was written for developers. Regulators need cross-references to capability thresholds and named accountability. Module 5 covers the audit and the rewrite.

The EU AI Office sent an information request. You have 30 days to respond. Module 10 covers the response protocol and what the office expects to receive.

A fine-tune is about to ship. You need to know if it crosses the systemic risk threshold and triggers a documentation update obligation. Module 7 covers the monitoring protocol.

What you get with this course

12 written modules in the Art of Service learning environment, self-paced
Downloadable templates for every module: capability taxonomy table, red-team integration log, GPAI technical file shell, accountability matrix, downstream deployer information pack, incident reporting template, cross-framework alignment table, pre-submission audit checklist
Hand-built implementation playbook scoped to GPAI obligations, delivered alongside course access

What you will have in hand by Day 1, Week 1, Month 1

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

Before and after

Before

Capability evaluations, red-team outputs, and policy commitments sit in separate documents. When a regulatory deadline arrives, the integration work is manual, rushed, and produces a submission that doesn't cross-reference correctly.

After

You have a repeatable process for translating technical capability inputs into an auditable GPAI technical file. Every artefact cross-references. The accountability chain is documented. Pre-submission audit is a checklist, not a scramble.

What happens if you do not address this

The GPAI documentation obligations under the EU AI Act apply now. Providers who cannot produce a compliant technical file on request face regulatory investigation, mandatory compliance measures, and potential fines. The accountability gap between research outputs and regulatory artefacts is the most common reason submissions fail or trigger follow-up inquiries.

Who it is for

You are in a frontier AI governance role at a company developing or deploying general-purpose AI models at scale. You are accountable for translating technical capability evaluations into regulatory documentation, managing the interface between red-teaming outputs and formal risk assessments, and producing the artefacts that satisfy GPAI obligations under the EU AI Act, the UK AISI's evaluation framework, or equivalent national schemes. You know the technical content. The course teaches you how to assemble it into a submission-ready package.

Who this is NOT for. This course is not for policy analysts writing position papers on AI regulation. It is not for researchers conducting capability evaluations. It is not for compliance professionals managing a checklist against a finished product. It is for governance practitioners who are accountable for producing the actual regulatory artefacts from raw technical inputs.

How it arrives

Text-based course in the Art of Service learning environment, plus downloadable templates and worked examples for every module, plus the hand-built implementation playbook delivered alongside course access.

Time investment. Each module is designed to be completed in one focused session of 45-60 minutes. The full course takes 8-10 hours across two weeks. The implementation playbook accelerates application to your specific model and regulatory context.

Why $199 is the right number

External regulatory counsel can advise on GPAI obligations but cannot produce the governance artefacts or teach the internal team how to build them. Internal policy teams have the domain knowledge but often lack the structured process for integrating technical inputs into regulatory documentation. This course bridges the two: it teaches the integration skill so the governance team can execute without external dependency on every documentation cycle.

FAQ

Is this course specific to the EU AI Act, or does it cover other jurisdictions?

The primary framework is the EU AI Act's GPAI provisions, because that is the most detailed and legally binding scheme currently in force. Module 11 covers alignment with the UK AISI framework, US EO safety commitments, and Singapore FEAT. The cross-framework alignment table helps you see which artefacts satisfy multiple schemes.

Does this require a legal background?

No. The course is designed for governance practitioners who understand the technical content of capability evaluations and red-teaming but need the regulatory documentation skill. Legal review of the final submission is a separate step; this course teaches you how to produce what legal needs to review.

What if our model is below the systemic risk threshold today?

Module 7 covers threshold monitoring and change management specifically. The course teaches you how to build a monitoring protocol that flags when a capability change or deployment context change triggers an obligation review, so you are not caught by a threshold crossing after the fact.

How is the implementation playbook tailored?

The playbook is hand-built for your specific situation: your model's capability profile, your regulatory context, and your governance team structure. It is delivered alongside course access within 24 hours of purchase.

30-day money-back guarantee. If after a week of working through the materials this is not what you needed, reply to the receipt email and a full refund is processed. No questions, no forms.

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.