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CLEAR Methodology

CLEAR

Yunique AI's methodology for operational AI governance.

CLEAR is Yunique AI's proprietary methodology for examining how AI governance operates across five connected areas: Clarity, Legal & Risk Alignment, Enablement, Accountability and Responsible Execution.

It is built around a simple principle: governance must be more than documented intent. Organisations need visibility into AI use, clear accountability, appropriate controls and evidence of how governance operates in practice.

Explore the five areasStart the CLEAR Assessment

What is CLEAR?

CLEAR provides a structured methodology for examining the organisational conditions needed to govern AI in practice. It connects visibility of AI use with risk and obligations, organisational enablement, accountability and responsible execution.

CLEAR is designed to help organisations move beyond governance that exists only in policies and documentation towards governance that can be understood, operated, evidenced and reviewed.

CLEAR is Yunique AI's proprietary methodology. It is not a recognised standard, a certification, a regulatory framework or a substitute for applicable law. It does not itself guarantee legal defensibility, and applying it does not prove compliance or constitute legal advice.

The five CLEAR pillars

The five areas of CLEAR use these formal names consistently: Clarity, Legal & Risk Alignment, Enablement, Accountability and Responsible Execution.

C
Clarity
Know where AI is being used.
Clarity concerns visibility into AI systems, tools and use cases across the organisation, including AI capabilities embedded within third-party products. Meaningful governance depends on understanding where AI is being used, for what purpose, what it influences and who is involved.
L
Legal & Risk Alignment
Connect AI use to risk and obligations.
This area considers the legal, regulatory, contractual, privacy, security, sector-specific and organisational risk considerations that are relevant to the context of a particular AI use, so that decisions reflect the obligations that actually apply.
E
Enablement
Give people a governed path to use AI.
Enablement considers whether people have appropriate approved pathways, guidance, training and organisational capability to use AI within established governance expectations. Governance should enable appropriate AI use rather than simply restrict it.
A
Accountability
Make ownership and decision rights clear.
Accountability examines ownership, responsibility, approval, escalation and decision rights. What is appropriate varies with organisational context and risk, rather than requiring an identical ownership structure for every AI tool.
R
Responsible Execution
Make governance operate in practice.
Responsible Execution considers how governance continues through controls, appropriate human oversight, evidence, monitoring, review, incident response and change management, according to the nature and risk of the AI use. This is where documented expectations are connected to operational practice.

How the five areas work together

The five areas are connected rather than sequential.

  • Visibility informs risk decisions.
  • Risk and obligations shape appropriate controls and approved pathways.
  • Enablement helps people operate within those expectations.
  • Accountability establishes who owns decisions and actions.
  • Responsible Execution examines whether governance continues to operate as AI use changes.

The methodology should therefore be considered as a connected governance environment rather than five independent checklists.

Where CLEAR fits

CLEAR is a proprietary methodology developed by Yunique AI. It can be used alongside established governance frameworks, management systems, standards and regulatory requirements. Depending on organisational needs, these may include approaches such as:

  • NIST AI RMF
  • ISO/IEC 42001
  • ISO/IEC 42005
  • applicable AI, privacy and sector-specific regulatory requirements

CLEAR does not replace them. Its role is to provide Yunique AI's methodology for examining how governance is understood and operationalised across the organisation. No formal alignment, conformity or equivalence is claimed unless separately verified.

How CLEAR is applied

The five areas are a way of examining governance, not a five-step implementation sequence. CLEAR can inform different types of work across the governance lifecycle, following the Yunique AI journey where appropriate.

Step 1
Assess
Establish a reported baseline across the five areas.
Step 2
Discover
Understand where AI is used, by whom and for what purpose.
Step 3
Validate
Test relevant assertions against evidence where greater confidence is required.
Step 4
Remediate
Address prioritised gaps in governance design, controls or capability.
Step 5
Report & Track
Communicate position and progress to leadership and stakeholders.
Step 6
Review & Improve
Revisit governance as AI use, risk and obligations change.

The methodology can be applied through activities such as:

  • assessment
  • governance design
  • risk assessment
  • implementation
  • evidence review
  • assurance
  • training and enablement
  • ongoing review

Not every engagement includes every activity; the work is shaped by organisational need and risk.

Start with a baseline

The CLEAR Assessment is a self-reported diagnostic based on the five areas of the CLEAR methodology. It provides an initial view of the organisation's reported governance position and can help identify areas that may warrant further attention.

It does not independently verify that governance controls operate, and it does not establish that an organisation's AI use is legally defensible.

Self-assessment captures belief. Validation tests reality.

Assessment establishes a baseline based on the information provided. Where greater confidence is required, relevant assertions can be tested against evidence to determine whether governance operates as described. That distinction remains central to the CLEAR methodology.

Measuring progress

The CLEAR Assessment produces a score out of 110, a maturity band and recommended priorities. The score is generated from self-reported responses. It can help communicate an initial baseline and track reported change over time.

  • It is not certification.
  • It is not a legal opinion.
  • It is not independent assurance.
  • A “Defensible” band does not independently establish legal defensibility.

Review and continuous governance

Governance should be reviewed on a risk-based basis and when material changes occur. Possible triggers include:

  • significant new AI use
  • material system changes
  • changed data or purpose
  • new vendor AI functionality
  • incidents
  • material regulatory or contractual change

Organisations may also establish appropriate periodic review cycles suited to their context and risk profile.

Related resources

  • AI Policy Template — A practical starting point for establishing documented expectations for AI use — while recognising that policy is not evidence of operation.
  • AI Governance Tools — How technology can support governance without replacing accountability, judgement or governance design.
  • AI Governance Assessment Guide — How assessment establishes a baseline and where evidence-based validation becomes important.
  • NIST AI RMF and CLEAR — How NIST AI RMF and Yunique AI's CLEAR methodology can complement one another.
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This page describes Yunique AI's proprietary CLEAR methodology and is provided for general information only. It does not constitute legal advice. The CLEAR Assessment is a self-reported diagnostic and is not a certification, audit, or independent assurance of legal compliance.