Pricing depends on your organisation's size and complexity. The initial 30-minute consultation is free with no obligation, and we provide a fixed-price proposal before any work begins. Most UK businesses find the cost is far lower than a single AI-related data exposure incident.

Yes. Our governance approach is tool-agnostic — it covers Microsoft Copilot, ChatGPT, Google Gemini, Claude and any other AI tools your team is using, including the ones you may not know about yet.

Most reviews are completed within 2-3 weeks. The first discovery conversation is around 30 minutes; full delivery depends on the size of your organisation and current AI usage.

No — the opposite. Clear governance gives employees the confidence to adopt AI tools because they know what's allowed. Most organisations find AI use accelerates after governance is in place because the fear and confusion is removed.

AI governance overlaps with cyber security, data protection and HR policy — but adds AI-specific risks around prompt injection, training data exposure, output accuracy, intellectual property and bias. Our approach aligns AI governance with your existing policies rather than duplicating them.

Yes. An AI acceptable-use policy gives employees clear rules: which tools are approved, what data can be entered, when human review is required, and how AI-generated outputs should be handled. It's becoming an expected control for cyber insurance, customer due diligence and ISO 27001 audits.

Shadow AI is the use of AI tools by employees outside IT's awareness or approval — for example, pasting sensitive documents into free public AI tools, using personal AI accounts for work tasks, or relying on browser extensions and unreviewed AI features. It's the modern equivalent of shadow IT, and it's already happening in most organisations.

AI governance is the framework of policies, training and controls that ensure AI tools are used safely, responsibly and consistently across your business. Without it, employees may use unapproved AI tools, enter confidential data, or act on inaccurate outputs — creating data security, compliance and reputational risk.