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Solution Capability · 6.6

AI Operations Governance

Operate governance as a recurring production discipline covering ownership, evidence, risk, change, incidents, review, and accountability.

What problem does this solve?

Governance documents lose value when they are disconnected from production work. Teams need a practical way to apply policies to releases, incidents, evaluations, access, content, vendors, and changing use cases.

Who is it for?

AI governance and risk leaders

CIO, CTO, data and AI leaders

Application and product owners

Security, privacy, legal and compliance teams

Internal audit and operational control teams

How Ignatiuz delivers it

1

Translate policy into operational checks and workflows.

2

Maintain use-case, owner, model, data, tool, risk, control, and evidence record.

3

Define recurring reviews for access, performance, incidents, changes, vendors, content, and outcomes.

4

Connect governance decisions to evaluation, release, monitoring, and support.

5

Document exceptions, approvals, remediation, and review dates.

Common use cases

Production AI register.

Release and change governance.

Access and data review.

Evaluation and threshold approval.

Incident and exception review.

Vendor and model change review.

Human oversight and accountability review.

Platforms involved

Microsoft, Salesforce, OpenAI, Claude, and IGNA.

Service management, identity, and data platforms.

Observability, document, workflow, or GRC tools.

Security & Governance

Human in the Lead

This capability establishes controlled access, documented ownership, approved use, reviewable evidence, Human in the Lead decisions, incident procedures, change control, and recurring governance review. It does not replace client legal or regulatory advice.

Frequently Asked Questions.

How is this different from AI governance strategy?
Strategy defines the framework. Operations governance applies it to real systems, releases, access, incidents, evaluations, and evidence over time.
Ownership is shared. Executive, business, technology, data, security, risk, legal, privacy, and operational roles need defined responsibilities.
Evidence depends on risk and policy but may include approvals, evaluations, release records, access reviews, incidents, changes, human-review logs, and remediation.

Ready to talk about AI Operations Governance?

A readiness workshop is the fastest way to find out if this is the right starting point.

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