AI Governance
A structured approach to managing AI risk, ensuring compliance, and building trust across your organisation.
What happens without a policy
Right now, someone in your organisation is pasting sensitive data into an AI tool. Do you know where that data goes?
Every prompt is a data decision. Is yours governed?
OUR PROCESS
How we work
A structured engagement from first conversation to working framework. Typical timeline: 2–4 weeks.
Discovery
Stakeholder interviews to map current AI usage, identify ungoverned tools, and establish your leadership team’s risk appetite.
Logging
Build your AI register — every tool documented, mapped to teams and individuals, with data flow and vendor terms reviewed.
Governance
Write your bespoke framework: acceptable use policies, data classification rules, accountability structure, and regulatory alignment.
Monitoring
Configure tooling to detect policy violations and shadow AI adoption. Quarterly reviews keep the framework current.
Discovery
Stakeholder interviews to map current AI usage, identify ungoverned tools, and establish your leadership team’s risk appetite.
Logging
Build your AI register — every tool documented, mapped to teams and individuals, with data flow and vendor terms reviewed.
Governance
Write your bespoke framework: acceptable use policies, data classification rules, accountability structure, and regulatory alignment.
Monitoring
Configure tooling to detect policy violations and shadow AI adoption. Quarterly reviews keep the framework current.
Typical engagement: 2–4 weeks end-to-end. Monitoring phase optional.
OUR CLIENT BASE
Client
Company Size
Typically 20–100 staff. Large enough to have meaningful AI adoption across departments, small enough that governance has fallen through the cracks. No dedicated compliance or legal team.
Company Size
Typically 20–100 staff. Large enough to have meaningful AI adoption across departments, small enough that governance has fallen through the cracks. No dedicated compliance or legal team.
What's at stake
These organisations learned the hard way. Without governance, AI risk becomes business risk.
Engineers pasted proprietary source code into ChatGPT. The data was stored on OpenAI servers. Samsung subsequently banned generative AI company-wide.
No policy means no control over what leaves your organisation.
An AI chatbot provided incorrect bereavement fare information. A tribunal ruled Air Canada liable for its AI's output.
Deployed AI creates legal accountability whether you're ready or not.
MAS and HKMA have both issued binding guidance on AI use in financial services. Firms without documented governance frameworks face supervisory scrutiny.
APAC regulators are moving faster than most organisations expect.
GET STARTED
Ready to build your framework?
We scope every engagement before any commitment.
Tell us about your organisation and we'll respond within 2 business days.
FAQ
AI governance is the set of policies, processes, and accountability structures that determine how your organisation uses AI, covering data handling, risk classification, staff responsibilities, and regulatory compliance.
Any organisation using AI tools with staff or customer data. This includes businesses subject to Singapore's PDPA and Model AI Governance Framework, Australia's Privacy Act 1988 and AI Ethics Principles, Hong Kong's PDPO and HKMA AI guidance, and the UK GDPR and ICO guidance on automated decision-making. If your team uses ChatGPT, Copilot, or any AI-assisted tool, you need a framework.
Our guided tool produces a first-draft framework in under an hour. For organisations requiring bespoke consulting, a full implementation typically takes two to four weeks depending on complexity.
Our framework tool is structured around the EU AI Act (the global benchmark), with modules relevant to Singapore's PDPC Model Framework, Australia's Privacy Act and AI Ethics Principles, Hong Kong's PDPO and HKMA guidance, and UK GDPR. We update coverage as regulations evolve.
Regulatory fines under the EU AI Act reach up to €35 million or 7% of global annual turnover. Under UK GDPR, fines reach £17.5 million or 4% of global turnover. Beyond fines: data breach liability, reputational damage, loss of enterprise contracts that require vendor AI policies, and personal liability exposure for directors in some jurisdictions.