Agent Governance Diagnostic
Your Agents are making decisions, accessing data, and generating legal consequences on your behalf. Without governance infrastructure, you have no systematic basis for knowing what they are authorised to do, or what your position is when something goes wrong.
HOW IT WORKS
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We establish what Agents you are deploying or intend to deploy. What they are doing, what systems and data they can access, and what cross-enterprise interactions are occurring or planned. Most organisations are surprised to find that the gap between what their Agents are technically authorised to access and what they are legally authorised to do is significant, and entirely undocumented.
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Each Agent is classified by risk profile, privilege level, and cross-enterprise exposure. We identify what IAM permissions, Agent Workforce Mandates, and Cross-Enterprise Relationship Contracts each Agent requires, whether those instruments exist, and whether their contents are consistent with what the Agent is actually doing. The classification framework connects the technical assessment to the legal instrument requirements.
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You receive a classification of each Agent in the estate, a governance gap analysis, and a prioritised remediation roadmap covering IAM, Agent Workforce Mandate (AWM), and Cross-Enterprise Relationship Contract (CERC) requirements. The Agents that require formal authentication via LAS Object registration are identified. The pathway to Phase Two is set out clearly.
THE PRACTICE
Every enterprise deploying Agents is accumulating legal exposure it cannot currently quantify. Agents are making decisions, accessing data, generating obligations, and interacting with counterparty Agents across organisational boundaries without the identity, authority, and governance infrastructure that would make any of that legally legible. An Agent without a defined scope, a documented mandate, and authenticated authority is a workforce member with no employment contract, no defined role, and no accountability framework.
The organisations that establish the governance infrastructure first will be the ones that can deploy Agents into consequential workflows, across enterprise boundaries, and at regulatory scale, without stopping to rebuild the foundation under pressure. The Agents are already in the field. A-Gov is what makes their deployment legally real.
THE CLIENT
“Legal frameworks governing liability, attribution, and duty of care were designed for a world in which consequential decisions were made by identifiable human actors operating within knowable organisational structures. AI changes every one of those assumptions simultaneously. The governance frameworks that exist today are not inadequate at the margins. They are structurally misaligned with the risk environment organisations are increasingly operating in.”
CASE STUDY
ILLUSTRATIVE · ENTERPRISE · 2026
A large financial services organisation has deployed Agents across its operations division over an eighteen-month period.
The Agents are technically authenticated. None of them have an Agent Workforce Mandate (AWM). Several are interacting with counterparty Agents at partner organisations without a Cross-Enterprise Relationship Contract (CERC) governing any of those interactions.
An A-Gov engagement would assess the full Agent estate, classify each Agent by governance requirement, and identify the cross-enterprise interactions as the highest-priority gap. AWM requirements would be produced for all Agents. CERC requirements would be identified for every cross-enterprise interaction. The Agents requiring Phase Two LAS Object registration would be flagged with a recommended pathway. For the first time the Chief Risk Officer and General Counsel would have a foundation from which risks could be properly assessed and legal advice on the Agent estate could be given efficiently.
INDICATIVE OUTCOME
Complete Agent classification and prioritised governance remediation roadmap
INDICATIVE TIMELINE
3 months to final report
SCOPE
A-Gov classification, AWM gap analysis, CERC identification, Phase Two pathway
