01
AI use has grown informally
Staff are using public tools, but data handling, acceptable use and ownership are unclear.
Practical AI governance
Put proportionate controls around the AI your business uses
We help small businesses understand where AI is already being used, classify material risks and introduce policies and controls that people can follow in real work.
- AI inventory and ownership
- Risk-based policies and review
- Evidence, monitoring and incident paths
In brief
What does proportionate AI governance look like for an SME?
Proportionate AI governance gives people clear decisions, responsibilities and controls without copying an enterprise framework that the organisation cannot operate.
It normally begins with an inventory of systems and uses, then applies stronger review where AI affects customers, employees, regulated activity, sensitive data or consequential decisions.
What you leave with
- Visibility of sanctioned and unsanctioned AI use
- Clear accountability for approval, operation and review
- Controls matched to impact rather than a blanket prohibition
Good fit
When this service is useful
The work is shaped around a concrete decision or workflow. These are common starting points, not eligibility rules.
02
Customers are asking questions
You need a coherent explanation of how AI is selected, tested, monitored and governed.
03
A higher-impact system is planned
The proposed use may affect people, sensitive information or important business decisions and needs stronger assurance.
Engagement outputs
What the work can produce
Exact scope follows discovery. Deliverables are selected to resolve the decision at hand and leave your team with usable evidence.
AI system and use inventory
A practical record of tools, use cases, owners, data, suppliers, affected groups and current controls.
Risk classification approach
Decision criteria that direct low-, medium- and higher-impact uses into appropriate review.
Policies and operating procedures
Plain-language acceptable use, procurement, development, evaluation, monitoring and incident guidance.
Governance roadmap
Prioritised actions, evidence gaps and ownership designed around the organisation’s actual capacity.
How we work
A staged path from uncertainty to evidence
Each stage has a clear purpose. Findings can change the next step, including narrowing or stopping work when the case is weak.
- 01
Discover use
Identify tools, experiments, vendors, data flows and decisions that already depend on AI.
- 02
Classify risk
Assess impact, data sensitivity, autonomy, affected groups, reversibility and regulatory context.
- 03
Design controls
Assign ownership, evaluation, approval, monitoring and escalation proportionate to each class.
- 04
Embed practice
Train responsible teams, test the workflow and schedule evidence-based review as systems change.
Questions
Common questions about ai governance consulting
Is this legal advice?
No. Simlyst provides operational and technical AI governance consulting. Where legal interpretation is required, we recommend involving suitably qualified legal counsel.
Do small businesses really need AI governance?
Any business using AI benefits from knowing which systems are in use, what data they receive, who owns the outcome and what happens when the system fails. The depth of control should match the risk.
Can governance keep pace with changing tools?
Yes, when it is based on use, impact and evidence rather than a fixed list of approved brands. Inventories and reviews still need named owners and regular maintenance.
Start with the decision, not the technology
Make the next AI decision with clearer evidence
Tell us what you are trying to improve, what has already been attempted and where uncertainty is blocking progress. We will use that context to decide whether Simlyst is a useful fit.