Universal (All Sectors)

AI Policy Generator for Universal (All Sectors)

Horizontal AI governance overlay for organisations with no single sector classification, multi-sector operations, or use cases where a sector-specific overlay is not applicable. Provides cross-cutting AI laws, risks, prohibited practices, and vendor and policy guidance that apply regardless of industry.

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Why Responsible AI matters in all sectors

Organisations in all sectors face AI obligations that generic templates don’t cover — clinical-safety duties, sector-specific regulators, data protection expectations for the populations you serve, and emerging AI-specific legislation. Blanket policies written for software companies miss most of what matters.

The AI Policy Generator produces a draft-ready AI usage policy tailored to your jurisdiction, risk appetite, and the specifics of all sectors. It is a drafting aid built to accelerate — not replace — qualified review by your in-house practitioners or external counsel.

Industry-specific risks

AI risks that matter in all sectors

Drawn from published evidence and regulatory guidance specific to all sectors. Each is pre-scored on a 5×5 likelihood × impact matrix in the Risk Register tool and referenced in the generated policy.

CriticalLikelihood 5 · Impact 5

Algorithmic Bias and Discriminatory Outcomes Across Protected Characteristic Groups

AI systems trained on historical or unrepresentative data produce systematically different outputs across gender, racial, ethnic, age, disability, and socioeconomic groups — either by direct reliance on protected attributes or through proxy variables — resulting in disparate treatment, indirect discrimination, and legal exposure under equality and anti-discrimination law in the operating jurisdiction.

CriticalLikelihood 5 · Impact 4

Generative AI Hallucination and Confabulation in Consequential Decision Workflows

Large-language-model and multimodal-generative AI tools produce plausible-sounding but factually incorrect output — fabricated citations, invented statistics, non-existent sources, hallucinated product or legal information — that is acted upon by staff or customers without independent verification, resulting in financial loss, regulatory exposure, reputational harm, and third-party liability.

CriticalLikelihood 5 · Impact 5

Personal Data Leakage Through AI Training, Inference, or Telemetry

Personal data is exposed to AI systems without a valid lawful basis — either through staff pasting personal or confidential information into public AI chatbots, through vendor telemetry and logging arrangements not covered by a Data Processing Agreement, through model-memorisation enabling adversarial extraction of training data, or through cross-border inference endpoints lacking a valid transfer mechanism — triggering GDPR, national privacy-law, and contractual breach consequences.

HighLikelihood 4 · Impact 4

Automation Bias and Unsafe Over-Reliance on AI Outputs

Staff accept AI recommendations without applying independent judgment — particularly in high-volume workflows where AI is used for triage, prioritisation, or draft generation — resulting in systematic failures to catch AI errors that a vigilant human would have identified, and in erosion of the human-in-the-loop safeguards on which regulatory and contractual commitments depend.

HighLikelihood 4 · Impact 4

Third-Party AI Vendor Concentration and Supply-Chain Risk

Critical AI capabilities are concentrated in a small number of foundation-model providers, cloud-inference endpoints, and AI-service vendors — creating systemic exposure to correlated failure, vendor outage, unilateral pricing or terms changes, model-behaviour changes breaking downstream integrations, and vendor insolvency or sanctions-regime changes that can make a mission-critical AI service abruptly unavailable.

HighLikelihood 4 · Impact 4

Prompt Injection, Data Poisoning, and Adversarial Attacks on Production AI

AI systems face attack vectors unique to AI — direct and indirect prompt injection, adversarial inputs, model-extraction through API probing, training-data poisoning via compromised third-party datasets, and supply-chain attacks on model components and adapters — that can cause the AI system to leak confidential information, execute unauthorised actions through tool-use or agentic integrations, or produce attacker-controlled outputs.

Responsible AI principles applied

How the five principles apply to all sectors

Human oversight

Outputs support, rather than replace, the qualified practitioners in your all sectors team. Human review is treated as a core step, not a rubber stamp.

Safety & validation

Before any AI system is acted on in all sectors, it is tested in the specific population, workflow, and risk context of your organisation — not just in a vendor's demo environment.

Transparency & explainability

Outputs carry enough context — regulatory references, assumptions, known limitations — that a reviewer in all sectors can trace and challenge them.

Accountability

Named roles — named individuals, named committees — are accountable for the AI decisions that affect people in your all sectors organisation.

Equity & inclusiveness

Performance is reviewed across the demographic groups your all sectors organisation actually serves, not just a representative-of-the-dataset average.

Our approach

How the AI Policy Generator works

You describe your organisation — jurisdiction, industry, staff size, AI tools in use, and risk appetite. The tool produces a structured policy tailored to that context in under five minutes.

The output is a complete Word document with inline review notes citing the specific regulations each section is derived from. It is an AI-assisted drafting aid intended to accelerate — not replace — review by your in-house or external practitioners.

The output is a draft calibrated to all sectors — it still requires review by qualified in-house or external practitioners before adoption.

Benefits

What you get — measured and defensible

Starts you at a complete structured draft instead of a blank template or generic boilerplate.
Sector-aware clauses that reflect clinical safety, data protection, or financial-conduct obligations as relevant to your industry.
Editable and auditable — every section is editable and carries the regulatory basis it was built from.
Reduces the time your compliance, legal, and governance practitioners spend on the first draft, so they can focus on review and adaptation.

Regulatory context

Regulatory and governance considerations

Selected obligations the tool’s output references for all sectors. This is not a complete statement of your legal obligations — qualified counsel should verify applicability in your jurisdiction and context.

EU AI Act — Article 5 Prohibited AI Practices (Regulation (EU) 2024/1689)

Article 5 of the EU AI Act establishes eight categories of absolute prohibitions that apply to all AI providers and deployers regardless of sector, including subliminal manipulation, exploitation of vulnerabilities, social scoring by public authorities, individual crime-prediction based solely on profiling, untargeted scraping of facial images, emotion recognition in workplaces and educational institutions, biometric categorisation inferring protected characteristics, and real-time remote biometric identification in public for law enforcement (subject to narrow exceptions). These prohibitions have applied since 2 February 2025.

EU AI Act — Article 4 AI Literacy Obligation (Regulation (EU) 2024/1689)

Article 4 requires providers and deployers of AI systems to ensure a sufficient level of AI literacy among their staff and other persons dealing with AI systems on their behalf, applicable since 2 February 2025. The obligation applies to any organisation regardless of sector that provides or deploys AI in the EU, including general-purpose AI tools used by staff, third-party AI tools embedded in business processes, and AI assistants or copilots.

GDPR — Horizontal Personal Data Processing and Automated Decision-Making (Regulation (EU) 2016/679)

The General Data Protection Regulation applies horizontally to any organisation — regardless of sector — that processes personal data of EU or EEA residents, whether established inside or outside the EU. All AI systems that process personal data in training, inference, fine-tuning, or telemetry fall within GDPR scope. Article 22 specifically governs automated individual decision-making including profiling producing legal or similarly significant effects, and Article 35 mandates DPIAs for high-risk processing including most AI deployments.

GLOBAL

ISO/IEC 42001:2023 — Artificial Intelligence Management System (AIMS)

International management-system standard for Artificial Intelligence, certifiable analogously to ISO/IEC 27001 and applicable to organisations of any sector, size, and AI maturity. Referenced in the EU AI Act harmonised-standards pipeline, in Singapore Model AI Governance Framework, in UK DSIT Pro-Innovation Framework, and in enterprise AI-vendor procurement as evidence of AI governance maturity. Serves as the default horizontal AI governance baseline where no sector-specific framework applies.

Trust & transparency

Built to strengthen in-house expertise

Every output is an editable draft. Every section carries the regulatory basis it was built from, so reviewers in your all sectors team can verify, challenge, and adapt it to local context. Nothing is a finished legal instrument; nothing is intended to bypass qualified review.

We publish explicit disclaimers in the generated documents themselves, and treat human oversight as a default — not an opt-in. The tool’s role is to reduce the time your qualified practitioners spend on the first draft, so they can focus on review and adaptation.

Explore the AI Policy Generator for Universal (All Sectors)

Review a sample of what the tool produces, then generate a draft tailored to your own all sectors organisation. $29.95 · one-time.

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Related laws & frameworks

Laws the output references for all sectors

10 regulations across 2 jurisdictions. This list is descriptive, not exhaustive, and is subject to change — verify applicability with qualified counsel before relying on any reference.

EU

EU AI Act — Article 5 Prohibited AI Practices (Regulation (EU) 2024/1689)Article 5 of the EU AI Act establishes eight categories of absolute prohibitions that apply to all AI providers and deployers regardless of sector, including subliminal manipulation, exploitation of vulnerabilities, social scoring by public authorities, individual crime-prediction based solely on profiling, untargeted scraping of facial images, emotion recognition in workplaces and educational institutions, biometric categorisation inferring protected characteristics, and real-time remote biometric identification in public for law enforcement (subject to narrow exceptions). These prohibitions have applied since 2 February 2025.
EU AI Act — Article 4 AI Literacy Obligation (Regulation (EU) 2024/1689)Article 4 requires providers and deployers of AI systems to ensure a sufficient level of AI literacy among their staff and other persons dealing with AI systems on their behalf, applicable since 2 February 2025. The obligation applies to any organisation regardless of sector that provides or deploys AI in the EU, including general-purpose AI tools used by staff, third-party AI tools embedded in business processes, and AI assistants or copilots.
GDPR — Horizontal Personal Data Processing and Automated Decision-Making (Regulation (EU) 2016/679)The General Data Protection Regulation applies horizontally to any organisation — regardless of sector — that processes personal data of EU or EEA residents, whether established inside or outside the EU. All AI systems that process personal data in training, inference, fine-tuning, or telemetry fall within GDPR scope. Article 22 specifically governs automated individual decision-making including profiling producing legal or similarly significant effects, and Article 35 mandates DPIAs for high-risk processing including most AI deployments.

GLOBAL

ISO/IEC 42001:2023 — Artificial Intelligence Management System (AIMS)International management-system standard for Artificial Intelligence, certifiable analogously to ISO/IEC 27001 and applicable to organisations of any sector, size, and AI maturity. Referenced in the EU AI Act harmonised-standards pipeline, in Singapore Model AI Governance Framework, in UK DSIT Pro-Innovation Framework, and in enterprise AI-vendor procurement as evidence of AI governance maturity. Serves as the default horizontal AI governance baseline where no sector-specific framework applies.
NIST AI Risk Management Framework 1.0 and Generative AI Profile (NIST AI 600-1)Voluntary cross-sector framework issued by the US National Institute of Standards and Technology providing internationally applicable guidance for organisations to manage AI risks throughout the AI lifecycle. The GenAI Profile (NIST AI 600-1, July 2024) supplements the core framework with 12 generative-AI-specific risk categories. Widely adopted as the de facto baseline across US enterprise, US state AI laws, international procurement, and investor ESG reporting regardless of sector.
OECD Recommendation of the Council on Artificial Intelligence (2024 update)Internationally agreed principles on responsible stewardship of trustworthy AI adopted by OECD member countries and partner economies, revised in 2024 to address generative AI and evolving AI governance needs. Operates as the reference international benchmark for organisations with multinational operations or supplying AI into jurisdictions without a binding national AI framework, and as the values baseline underlying many national AI statutes and soft-law instruments.
Council of Europe Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (CETS No. 225, 2024)The first legally binding international treaty on AI, open to signature by Council of Europe member states and non-member states. Requires state parties to ensure AI lifecycle activities are consistent with human rights, democracy, and the rule of law. Ratifying states translate the convention into domestic obligations binding on organisations operating in their jurisdiction, creating a developing international legal floor that applies regardless of sector.
G7 Hiroshima Process International Code of Conduct for Advanced AI System Developers (2023)Voluntary code of conduct agreed by the G7 for organisations developing and deploying advanced AI systems — explicitly including foundation and generative AI models. Endorsed by G7 nations, adopted into national expectation frameworks in Japan, the UK, and the EU, and referenced in the AI Safety Institute network's frontier-model evaluation programmes. Provides an international expectation baseline for any organisation developing or distributing advanced AI regardless of sector.
UNESCO Recommendation on the Ethics of Artificial Intelligence (2021)Adopted by all 193 UNESCO Member States in November 2021, the Recommendation is the first global normative instrument on the ethics of AI. It establishes values, principles, and policy action areas that Member States commit to implementing, with direct relevance to any organisation operating under national policies that give effect to the Recommendation — particularly in jurisdictions without binding AI legislation.
ISO/IEC 27001:2022 Information Security Management and ISO/IEC 27701:2019 Privacy Information ManagementInformation security and privacy management system standards that provide the foundational cybersecurity and privacy-governance baseline referenced across regulated sectors and incorporated by reference in national cybersecurity laws globally. AI systems are information systems — the ISO 27001 and 27701 controls apply to AI infrastructure, training data, model artefacts, and inference endpoints regardless of sector. Increasingly required or expected alongside ISO/IEC 42001 as evidence of AI governance maturity in enterprise and government procurement.