AI Governance

You cannot govern AI you cannot see.

AI is already operating across vendor platforms, embedded product features, internal tools, model APIs, agents, automations, and individual workflows. Oculus provides an AI governance assessment for regulated and high-consequence organizations to establish visibility, ownership, risk-based decisions, and a practical path to governed adoption.

Examples include organizations in healthcare, financial services, insurance, government, critical infrastructure — not an exclusive list.

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Assessment method

From visibility to governed adoption

1

Discover and inventory

Identify sanctioned and unsanctioned AI use across tools, models, agents, vendors, and workflows.

2

Capture ownership and context

Establish who uses each system, where, why, what data it touches, and its lifecycle stage.

3

Tier risk and map threats

Classify use cases and identify data leakage, decision, security, privacy, supply-chain, and regulatory exposures.

4

Review policy and control gaps

Compare current policy and controls with the organization’s actual AI use and risk.

5

Define roles and approval paths

Establish accountable owners, review responsibilities, and practical decision workflows.

6

Deliver a prioritized roadmap

Provide recommendations and an evidence model the organization can act on.

Our assessment approach is informed by contextual frameworks such as the NIST AI RMF and ISO/IEC 42001 — as guidance for structuring oversight, not as certification claims.