Scope & Liability Rationale

The AI Governance Liability Radar provides an indicative, board-level view of liability exposure arising specifically from the governance of AI systems, including AI agents, models, and AI-enabled tools. It enables boards and executive management to assess whether oversight, accountability, controls, and evidencesurrounding AI use are sufficiently established to remain defensible under regulatory scrutiny, audits, investigations, or incident-driven escalation.

The focus is not on technology performance, accuracy, or model quality, but on governance defensibility.
In enforcement, litigation, and supervisory review, liability is not determined by intent, explanations, or technical sophistication, but by the ability to demonstrate effective oversight, accountable decision-making, enforceable controls, and documented board action at the point where AI systems materially influence outcomes.

This score does not indicate wrongdoing — it indicates where personal accountability would be examined first.

Explicit scope: What this tool covers

This assessment covers AI-specific governance and oversight duties that can trigger personal or organisational liability when they are absent, ineffective, or cannot be demonstrated under scrutiny.

It evaluates liability exposure across six governance dimensions that determine board-level defensibility of AI use:

AI use in decisions
Whether AI systems support, influence, or automate decisions, including AI agents with autonomous behaviour, continuous operation, or tool-enabled actions that materially affect outcomes.

Regulatory exposure related to AI use
Whether AI use cases operate in regulated or sensitive decision contexts (e.g. employment, access, scoring, safety) and whether classification, obligation awareness, and governance readiness exist.
This dimension assesses governance exposure triggered by AI use, not jurisdiction-specific compliance.

Governance & ownership
Whether accountability for AI risks is explicitly assigned at board or executive level, including clear mandate, authority to act, escalation rights, and stop-use powers.

Controls & oversight
Whether AI systems are subject to ongoing monitoring, review, and intervention, including defined escalation thresholds, incident handling, and enforceable stop/go criteria.

Third-party & shadow AI
Whether externally provided AI capabilities and decentralised or unapproved AI tool usage are visible, governed, approved, and controllable by the organisation.

Evidence & auditability
Whether AI oversight can be demonstrated with evidence under time pressure, including AI inventories, ownership records, governance decisions, board actions, controls, and audit trails.

The radar reflects governance outcomes, not isolated controls or checklist completion.
AI-related liability is treated as a systemic governance condition, arising from patterns of decision authority, oversight, escalation, and evidence — not from single technical or procedural failures.

What this tool explicitly does not cover

This tool intentionally focuses on AI governance liability.
It therefore excludes assessments that do not materially determine board-level oversight, decision accountability, or governance defensibility of AI use.

To preserve clarity, precision, and legal robustness, the AI Governance Liability Radar does not replace, replicate, or certify:

• General IT or cybersecurity audits, except where security controls directly affect AI governance, oversight, or escalation authority
• Comprehensive data protection or privacy compliance programs, except where governance failures impair accountability for AI-driven decisions
• Product safety or consumer protection assessments that are unrelated to AI decision logic, autonomy, or governance control
• Financial, operational, or enterprise risk management frameworks that do not specifically address AI-related decision authority, oversight, or evidence

Where such domains intersect with AI governance, they are considered only to the extent that they influence board-level accountability, oversight obligations, or the ability to demonstrate defensible AI governance.Where such areas are relevant, they are considered only insofar as they relate directly to AI governance, oversight, and decision accountability.

Intended use and interpretation

This tool is intended to:

• Enable informed board-level discussion on AI oversight, accountability, and liability readiness
• Surface governance blind spots before incidents, audits, investigations, or regulatory intervention
• Prioritise concrete governance actions across a pragmatic 30 / 60 / 90-day horizon
• Strengthen the defensibility of AI oversight, not to certify compliance or replace formal assessments

Scores are derived from user-provided input and a simplified, systemic AI governance model.
Higher scores indicate increased liability pressure resulting from governance gaps, uncertainty, or insufficiently demonstrable oversight.
They do not constitute findings of wrongdoing, legal violations, or regulatory determinations.

Results should be interpreted as a governance signal, designed to inform decision-making, mandate corrective action, and support accountable board oversight.

Legal position and disclaimer

The AI Governance Liability Radar provides an indicative governance signal based on user input and a simplified AI governance model.

It does not constitute legal advice, a formal compliance assessment, certification, or a regulatory determination, nor does it replace engagement with qualified legal or regulatory advisors.

Boards and executive management retain full responsibility for ensuring that AI systems are governed, monitored, and documented in line with applicable laws, internal policies, and the organisation’s defined risk appetite.

AI-related liability rarely arises because organisations used AI.
It arises when boards cannot demonstrate accountable ownership, effective oversight, enforceable controls, and documented decision-making at the point where AI systems materially influenced outcomes.

This tool is designed to surface such governance gaps early, before they escalate into incidents, enforcement actions, or personal liability exposure.