AI Systems & Governance — John H. Snyder PLLC
Builder, Not ObserverMaterial Consequences OnlyInstitutional Design
AI Systems & Governance
For organizations deploying AI into consequential decisions where accountability is undefined and governance must be built.

Institutional design for the deployment of artificial intelligence — ensuring intelligence is introduced without loss of control.

Snyder advises on system design, governance frameworks, legal and regulatory risk, and implementation coordination — drawing on direct experience building AI systems on large unstructured data environments.

Background
Builder
Founder, Agnes Intelligence.
Scope
System to Governance
Design, rules, risk, implementation.
Deploying AI Without Losing Control

Most organizations are not limited by access to AI. They are limited by their ability to deploy it without creating institutional liability.

The failure mode is not technical. It is structural: AI systems that operate without clear accountability, produce outputs that cannot be audited, and create legal exposure that no one planned for.

The organizations that deploy AI effectively are not those with the most advanced systems — they are those that built the governance architecture before they needed it.

Intelligence without accountability is not a capability. It is a liability.
The Method

Four layers. Each must be addressed before the next can function.

ISystem Design
Where automation is appropriate — and where it is not.
Structure workflows that incorporate AI into decision processes. Define boundaries. Align system outputs with human accountability structures that can be audited and defended.
Who is responsible when the system produces a consequential output?
IIGovernance
Rules for how AI-generated outputs may be relied upon.
Establish frameworks for reliance, auditability, and traceability. Define responsibility across teams and functions. Maintain accountability as AI becomes embedded in institutional decision-making.
How do we know what the system did, and can we explain it?
IIIRisk & Constraints
Legal, regulatory, and operational exposure — mapped before deployment.
Identify where AI use creates legal exposure. Integrate deployment with existing institutional obligations. Prevent fragmentation between technical capability and legal accountability.
What obligations does this deployment create, and are we meeting them?
IVImplementation
Coordinating across technical, legal, and operational teams.
Ensure systems function as designed under real conditions. Manage the gap between intended and actual behavior. Adjust governance architecture as constraints emerge and the system scales.
Does the system behave as designed when it matters most?
The Work

Four categories of institutional AI work where governance is the product.

Deployment Governance
Rules, accountability, and auditability
Establish the governance framework before deployment — not after the first failure. Define who can rely on AI outputs, under what conditions, and with what oversight.
Legal & Regulatory Risk
Exposure that standard counsel misses
AI deployment creates exposure under existing legal frameworks that most legal teams have not mapped. Identify it, address it, and build compliance into the system design.
Institutional Design
Accountability structures for AI environments
Design the organizational structures, reporting lines, and decision protocols that allow AI deployment to scale without losing institutional control.
Crisis & Failure Management
When the system produces a consequential error
When an AI system produces a harmful output or creates legal exposure, the response requires both technical and legal coordination. Snyder manages both dimensions.
Why Snyder

The person advising you on AI governance built an AI system.

John H. Snyder
Founding Principal · AI Systems Advisor · Institutional Designer
John H. Snyder
Harvard Law School
Brown University · Phi Beta Kappa
Federal Clerkship · Proskauer Rose
Founder, Agnes Intelligence

Snyder founded and built Agnes Intelligence — an AI platform applied to large unstructured data environments — before returning to full-time legal practice. That background provides something unusual: direct experience with the gap between what AI systems are designed to do and what they actually do under real conditions.

Agnes Intelligence placed 4th among more than 1,000 entries in the 2018 IBM Watson Build competition. The work involved applying machine learning to complex institutional knowledge environments — exactly the context where governance architecture matters most.

Corporate & Structural Counsel
Thomas C. Sima
Duke Law (J.D. & LL.M., cum laude) · Shearman & Sterling, NY & HK · NY · FL · SDNY · EDNY
20+ years in institutional design, corporate governance, and regulatory compliance across multiple jurisdictions. AI governance ultimately reduces to questions of institutional accountability — who is responsible, what frameworks apply, and how obligations are met. Sima provides the structural and regulatory depth that AI system design requires.
Engagement

Engagements begin with a direct assessment of the deployment and governance gaps.

We evaluate the current state of AI deployment, the existing accountability structures, and the specific legal and operational risks. That assessment frames the scope of engagement.

Initial discussions are confidential. Engagements are structured to produce governance architecture that can be implemented and maintained — not reports that sit on a shelf.

Contact
$100,000–$500,000. Structured by scope, system complexity, and integration required.
An Early Conversation
Costs Nothing.

We engage organizations where AI deployment has material operational or legal consequences and governance must be built before the system scales further. Briefly describe the current deployment and the governance gaps you have identified.

Email inquiry@jhs.nyc
We Are a Fit When
AI is entering consequential decisions, accountability is undefined, and governance must be built — not retrofitted after a failure.
We Are Not a Fit When
The deployment is limited, low-stakes, or the governance framework is already in place and functioning.
The Engagement
$100,000–$500,000, structured by scope, system complexity, and integration required.