01
CISOs & risk leaders
Bring shadow AI, third-party AI and internal development into a consistent view. Establish risk classification, vendor assessment and reporting that connects technical exposure with business decisions.
AI ADVISORY · UK & GULF
AI governance,
risk management
and security.
Clear decisions. Accountable AI.
For the UK and the Gulf.
Senior-led AI governance consultancy for organisations in the UK, Saudi Arabia, the UAE and Qatar. We help CISOs, government leaders and investors understand AI exposure, establish accountability and put proportionate controls into practice.
Discuss AI governance & riskTHE DECISIONS THAT MATTER
AI governance and
risk management.
AI governance defines who decides, which uses are acceptable and how accountability works. AI risk management evaluates the consequences for people, information and business outcomes. AI security protects the data, models, prompts and integrations on which those uses depend.
We bring these decisions together. Your governance should cover the tools staff use today, the AI embedded in supplier products and the systems you plan to build. It should make adoption manageable, with clear approval routes, risk ownership and evidence for leadership.
WHO WE HELP
AI governance consulting
for leaders and investors.
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Government & public sector
Create accountable routes for AI adoption across departments and agencies. Address sensitive information, supplier dependencies and human oversight within existing security, procurement and governance arrangements.
03
Investors & portfolio leaders
Understand AI exposure in due diligence and across portfolio companies. Set proportionate expectations for ownership, controls and board reporting, linked to investment and operational priorities.
OUR APPROACH
Our AI governance approach:
from use case to oversight.
Start with the decisions your organisation needs to make. Build a framework that people can use, then establish the ownership to sustain it.
01
Map use cases
Identify where AI is used or proposed, its purpose, the information involved and the accountable business owner. Include generative AI tools, supplier features and internal systems. Take forward a use-case inventory and an initial risk classification.
02
Assess exposure
Review security, data, supplier and operational risks in context. Consider who could be affected, the limits of model outputs and the controls already in place. Take forward use-case assessments, prioritised risks and proportionate treatment recommendations.
03
Define decisions
Set policy, responsibilities, approval gates and escalation routes. Clarify when human review is needed and who accepts residual risk. Take forward decision rights, assessment templates and a controls roadmap aligned with your existing governance.
04
Maintain oversight
Define monitoring, reporting and review triggers as models, suppliers and use cases change. Establish how incidents and exceptions reach the right decision-makers. Take forward practical reporting measures and ownership for continued oversight.
SECURITY THROUGHOUT THE LIFECYCLE
AI security assessment:
secure the use.
An AI policy needs to address how systems are configured, connected and used. Threat references such as the OWASP Top 10 for Large Language Model Applications and MITRE ATLAS help structure consideration of AI-specific attack paths. An AI security assessment should consider prompt injection, exposure of sensitive information, insecure integrations, excessive permissions and dependencies in the AI supply chain.
We help connect these risks with control ownership: who can access the tool, what information it can retrieve, which actions it can perform and how outputs are checked. We agree the advisory scope, assessment boundaries and required evidence at the outset.
The NCSC guidelines for secure AI system development provide a lifecycle reference across secure design, development, deployment, operation and maintenance. The UK AI Cyber Security Code of Practice offers a further reference for security expectations.
Our wider AI-assisted vulnerability research focuses on mobile platforms and browsers. Our Kearney partnership supports specialist project delivery in AI security, information security risk management and enterprise cyber strategy.
UK & GULF CONTEXT
UK and GCC AI regulation,
mapped to your organisation.
Start with your activities, operating locations and sector. Distinguish legal obligations from guidance and voluntary standards, then connect relevant requirements with owners, controls and evidence.
| Context | What to address | Practical outcome |
|---|---|---|
| United Kingdom | Law and sector rules: applicable UK data protection and sector obligations. Guidance: ICO guidance on AI and data protection, NCSC guidance and the voluntary UK AI Cyber Security Code of Practice. | Align AI approval and oversight with existing information security, privacy and risk processes. |
| Saudi Arabia | Law and applicable controls: the Personal Data Protection Law (PDPL), National Cybersecurity Authority (NCA) controls and relevant sector requirements, including SAMA’s IT Governance Framework for regulated organisations. Guidance: SDAIA AI Ethics Principles and the National AI Risk Management Framework; see SDAIA publications. | Document the local requirements relevant to your use cases, data and operating model. |
| United Arab Emirates | Law and sector rules: applicable federal data protection, sector and free-zone requirements, including DIFC rules where relevant. Policy and guidance: the UAE Charter for the Development and Use of AI and AI Ethics Principles and Guidelines. | Clarify which entities, data flows and decision-makers fall within each part of the framework. |
| Qatar | Law and sector rules: applicable personal data privacy, security and regulated-sector requirements. Guidance: MCIT’s Principles and Guidelines for Ethical AI, informing responsible development and deployment. | Integrate AI ownership, assessment and oversight into organisational and sector governance. |
| European Union exposure | Assess whether the EU AI Act applies to your role, market activities or use of AI outputs. High-risk Annex III obligations apply from 2 December 2027; product-related Annex I obligations from 2 August 2028. Other duties apply earlier. | Work with legal advisers to establish scope and connect relevant requirements with an evidence plan. |
ISO/IEC 42001
An AI management system standard covering the establishment, maintenance and continual improvement of organisational AI management. Use it to structure responsibilities and processes. Certification is a separate decision.
Read the ISO standard overviewNIST AI RMF
A voluntary risk management framework organised around Govern, Map, Measure and Manage. Use it to structure how risks are understood, assessed and treated in the context of each use case.
Explore NIST AI RMFRegulatory scope is specific to your organisation and activities. This overview is not legal advice. Consult the European Commission’s AI Act overview for the current EU framework and timeline.
WHAT YOU TAKE FORWARD
Your AI governance framework
and risk management tools.
We agree the scope around your priorities. Deliverables can include:
- An AI use-case inventory and risk classification model
- An AI governance framework with defined policy and approval processes
- Use-case, data and vendor risk assessment templates
- Decision rights, accountable owners and escalation routes
- A prioritised roadmap for proportionate controls
- Monitoring and reporting measures for leadership oversight
Walkthroughs and knowledge transfer help your teams apply the framework. The aim is a repeatable decision process that works within your organisation, with clear responsibility for maintaining it.
WHY CYBERSHIELD PARTNERS
Senior expertise.
Practical commitment.
A named senior practitioner leads your engagement, with specialists involved where their expertise matters. We begin with your business priorities and make the responsibilities across advisory, specialist delivery and partner technology clear.
Headquartered in London, with Gulf reach across Doha, Dubai and Riyadh, we support delivery in English and Arabic through local partners and a specialist associate network. We build on your existing governance and transfer the tools and knowledge your teams need.
Meet our firm or explore how we connect cyber risk with business and investment decisions.
PRACTICAL ANSWERS
AI governance and security FAQs.
What is AI governance?
AI governance defines who is accountable for AI and how its use is approved, monitored and challenged. It connects policies with practical decisions about purpose, data, suppliers, human oversight and acceptable risk. A useful framework helps teams make consistent decisions throughout the AI lifecycle.
How does AI governance differ from AI risk management and security?
Governance establishes accountability and decision rights. AI risk management identifies, evaluates and treats potential harm to people, data and the business. AI security addresses threats to the systems, models and information involved. These disciplines work together: a policy needs controls, and controls need owners.
Where should a CISO start?
Start with an AI use-case inventory: what is being used, by whom, for which decisions and with what data. Include purchased software with embedded AI and unapproved tools. Classify exposure, identify accountable owners and introduce proportionate approval and escalation routes before expanding the policy set.
What does an AI risk assessment cover?
An assessment considers the purpose and context of a use case, affected people, data sensitivity, supplier dependencies, security exposure, reliability and human oversight. It records existing controls, remaining risk and the decision needed. The depth should reflect the potential impact, rather than treating every AI tool alike.
What is ISO/IEC 42001, and do we need certification?
ISO/IEC 42001 specifies requirements for an AI management system. It can provide a structure for policies, responsibilities, risk assessment and continual improvement. Whether to pursue certification depends on your objectives, customers and procurement requirements. Our advisory work helps establish governance; Cybershield does not issue ISO certificates.
How does NIST AI RMF fit with an AI governance framework?
NIST AI RMF is a voluntary framework organised around Govern, Map, Measure and Manage. It helps structure the identification and treatment of AI risks. It can inform operational risk processes alongside an AI management system, with responsibilities and evidence mapped to the organisation’s needs.
Can the EU AI Act affect UK or Gulf organisations?
Yes. Depending on the activity and role, organisations outside the EU can fall within scope when placing AI systems or models on the EU market, or where system outputs are used in the EU. Applicability requires a specific assessment. We help organise governance evidence alongside your legal advisers.
How should private equity firms approach portfolio AI risk?
Establish a common minimum view of AI use, ownership, sensitive data and material supplier dependencies across the portfolio. Prioritise companies and use cases with the greatest exposure, then agree practical controls and reporting. Connect findings with due diligence, post-close priorities and the value-creation plan.
How long does an engagement take?
Scope depends on the number of entities and use cases, existing governance, supplier complexity and the decisions you need to make. We agree priorities and deliverables in an initial conversation. Work can focus on a defined use case or a wider organisational governance framework.
Is there an AI law in the UK?
The UK approach is sector-led rather than a single EU-style AI Act. Existing laws, including data protection law, and sector regulators’ requirements can apply to AI activities. Voluntary guidance adds practical expectations but does not replace those duties. Assess the rules relevant to your organisation and use case.
Are SDAIA’s AI principles mandatory in Saudi Arabia?
SDAIA’s AI Ethics Principles are guidance, not a standalone AI law. Its National AI Risk Management Framework provides a structured risk reference. Binding duties can arise separately under the PDPL, applicable NCA controls and sector rules. Identify those obligations before mapping guidance into your governance framework.
When do EU AI Act high-risk obligations apply?
The European Commission’s current timeline gives 2 December 2027 for high-risk uses under Annex III and 2 August 2028 for high-risk systems linked to regulated products under Annex I. Other provisions already apply. Confirm the classification, role and relevant transition rules for each system with your legal advisers.
What is the NCSC’s guidance on secure AI?
NCSC’s Guidelines for Secure AI System Development cover secure design, development, deployment, and operation and maintenance. They address lifecycle risks such as supply-chain security, protecting models and infrastructure, monitoring and incident management. They are guidance for building and operating secure AI, rather than a certification scheme.
Regulatory overview reviewed 17 October 2026. Sources: European Commission AI Act timeline, UK government regulatory approach and NCSC secure AI guidelines.
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