AI governance briefing
For a board, AI governance is not a technology topic. It is four questions you need to be able to answer, in writing, when a client or a regulator asks.
The four governance questions
1. Who is accountable?
Every AI-supported process needs a named person with the authority to stop it. Not a committee. A named, accountable individual. When something goes wrong, a regulator starts with "who owns this?" - and "we don't know" is the worst answer.
2. Can you explain the output?
Regulators expect firms to explain why an AI system recommended or decided what it did, in plain English. If no one in the business can, the system is not governed, whatever the marketing says. This is why an evidence trail matters: a record of what the output was based on and who approved it.
3. Where does the data go?
Public AI tools process inputs on servers in other jurisdictions. For a regulated firm handling client data, that is a data-protection and contractual question before it is a technology question. Government and regulator expectations in the region are clear: you need a documented position on what may and may not leave.
4. What is already running inside the firm?
Most firms do not know how much AI they already have. Tools ship inside existing software - email, document suites, CRM, accounting. Some of it uploads client data to external models. An inventory of current AI use is the first governance artefact a firm should produce.
A practical starting point
One credible approach used in the region is an AI readiness assessment: a fixed-scope, evidence-based review of where a firm is ready and where it is not, producing a roadmap. The assessment should be honest - the value is in what you are told not to do.
Disclosure. Syntxe is independent. For an example of the assessment approach and the region's regulatory detail, see Fuzzelogic's AI assessment for regulated businesses and their AI governance for boards guide.