Governance framework

A practical system built around evidence.

Six Governance Pillars and 48 controls turn responsible AI from an abstract goal into clear requirements, accountable owners, and visible progress.

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6 Pillars · 48 Controls · Evidence-Based Scoring

What responsible AI looks like in practice.

Each pillar examines a connected part of the operating system, from AI visibility to sustained oversight and improvement.

PILLAR 1

AI Visibility

Does the organization know how AI is being used?

What we review: AI tools, use cases, owners, data types, business purpose, and vendor status.
Evidence: AI Tool Register, AI Use-Case Register, interviews, and vendor records.
Maturity indicator: Material AI use is documented, owned, risk-classified, and reviewed.

PILLAR 2

Policy and Accountability

Are clear rules, responsibilities, and approval processes in place?

What we review: Acceptable use, ownership, approvals, exceptions, and review cycles.
Evidence: Policies, governance charter, approval records, and meeting records.
Maturity indicator: Rules are current, understood, and supported by accountable owners.

PILLAR 3

Workforce Awareness

Do employees understand how to use AI responsibly?

What we review: Training coverage, role-based guidance, knowledge checks, and acknowledgements.
Evidence: Training materials, attendance, results, acknowledgements, and guidance.
Maturity indicator: Employees receive practical, recurring, role-relevant guidance.

PILLAR 4

Risk and Human Oversight

Does the organization identify AI risks and require appropriate human review?

What we review: Risk assessment, human-review standards, incident escalation, and corrective action.
Evidence: Risk assessments, approval records, incident records, and action logs.
Maturity indicator: Risk determines required review, approval, escalation, and oversight.

PILLAR 5

Technical and Vendor Guardrails

Are practical protections in place around AI tools, data, access, and vendors?

What we review: Existing controls, access, data protection, vendor diligence, and technical requirements.
Evidence: Configurations, vendor reviews, approved-tool records, and IT action plans.
Maturity indicator: Controls match risk and implementation is verified where appropriate.

PILLAR 6

Oversight and Improvement

Is AI governance actively managed after the policies are written?

What we review: Metrics, governance reviews, decisions, corrective actions, and reassessment.
Evidence: Dashboards, meeting records, decisions, action trackers, and roadmaps.
Maturity indicator: Leadership reviews evidence and drives measurable improvement over time.

Illustrative data

See the whole system at a glance.

The scorecard gives leaders a concise view of strengths, gaps, and priorities. These fictional results demonstrate the format and are not an assessment.

ILLUSTRATIVE69Overall maturity / 100

AI Visibility78

Policy and Accountability64

Workforce Awareness71

Risk and Human Oversight58

Technical and Vendor Guardrails67

Oversight and Improvement74

TrustBridge designations

Progress described clearly—not overstated.

A designation reflects independently assessed evidence within a defined scope and assessment period.

TrustBridge Bronze — Assessed

We understand where we stand.

Material AI use is visible, major risks are identified, leadership responsibility is assigned, and an improvement roadmap is approved.

Awarded when applicable requirements are met.

TrustBridge Silver — Implemented

We have established the governance program.

Core elements of an operational AI governance program have been implemented and evidenced.

The Sprint target—not a guaranteed outcome.

TrustBridge Gold — Mature

We have demonstrated that the program works over time.

The program is operating, evidenced, reviewed, and improved over time.

Requires at least six months of operating evidence.

Important distinction

TrustBridge Silver — Implemented is not guaranteed by completing the Sprint. TrustBridge Gold — Mature requires at least six months of operating evidence and cannot be awarded during the initial Sprint.

TRUSTBRIDGE

AI Governance Playbook

A maintainable operating system

A major Sprint deliverable

An operating system for governing AI.

The AI Governance Playbook organizes the program for leadership, governance owners, IT, and employees—and is designed to be maintained after the Sprint, not placed on a shelf.

Program overview, charter, and ownership

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AI policies and permitted-use standards

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AI Tool and Use-Case Registers

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Risk assessment and human-review standards

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Tool, vendor, and high-risk approval workflows

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Technical Guardrail Recommendations

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Employee training, knowledge checks, and acknowledgements

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Incident and corrective-action records

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Executive dashboard and review agenda

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Twelve-Month Governance Calendar

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Assessment and Designation Package

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