AI readiness audit in Hong Kong
Prepare a workflow owner, data inventory, access boundaries and baseline before commissioning an AI pilot.
Author：WeTech technical team · Updated： (Hong Kong time (GMT+8))
An AI readiness audit should establish whether a task can be piloted responsibly. Require a defined task, data owner, usable samples, human fallback and current-process baseline. Record gaps with an owner and remedy rather than relying on one readiness score.
When to use this guide
For businesses choosing a first AI project or resolving unclear data, permissions and acceptance ownership.
Readiness audit deliverables
| Area | Question | Deliverable |
|---|---|---|
| Workflow | Who uses it and handles failure? | Current process and owner |
| Data | Are samples usable and authorised? | Source, format and access inventory |
| Baseline | What volumes, errors and review steps exist? | Measurement definitions and sample log |
| Decision | Which gaps block the pilot? | Remedies, owners and entry conditions |
Audit tasks before tools
Map inputs, outputs, decisions and exceptions before choosing technology. Keep deterministic checks and approvals explicit. Document access difficulty and the consequences of mistakes for each candidate, so a visually impressive task does not outrank a usable, bounded workflow.
Start with an inventory
Share field definitions, document types, update frequency, sample availability and access methods first. Separate originals from test copies and assign deletion responsibility. De-identification does not automatically remove re-identification risks. Treat an unconfirmed data owner as an unresolved dependency.
Turn findings into a pilot boundary
The report should name a proposed pilot, exclusions, blocking issues, acceptance owner and stop conditions. Link recommendations to observations or samples. A readiness review is not a security certification or a measured savings result; those require separate evidence and tests.
Illustrative scenario
Illustrative scenario: supplier scans use inconsistent formats and have no update owner. Start with a sample inventory and named document owner, then pilot draft field extraction. Automatic payment approval remains outside scope. This is a hypothetical planning example.
Frequently asked questions
Can we start with untidy documents?
Yes, with an inventory that identifies cleaning, access and sample gaps. Development may need to wait.
Do we need a large dataset?
Representative, authorised samples matter first. The task and evaluation method determine the required quantity.
Does the audit include development?
Inventory, pilot and production development are separate deliverables and should be priced explicitly.
Brand and public case scope
WeTech Consulting, also called WeTech or WeTech AI HK, provides AI and IT consulting in Hong Kong. WeProperty HK and WeCredit HK are self-developed products. Their cases support the observable features listed: property, estate and transaction-reference entry points for WeProperty; submission, review and public-data masking for WeCredit. WeCredit is not a TU credit-rating service or a final determination of facts.
WeProperty HK · WeCredit HK (case studies in Traditional Chinese)
Reference sources
- NIST AI Risk Management Framework
- PCPD：Artificial Intelligence: Model Personal Data Protection Framework
Official documents support the technical, risk and measurement concepts. Checklists, estimation methods and illustrative scenarios are WeTech planning recommendations, not official prices or client results. Check the supplier’s current plan and terms. Sources reviewed: (GMT+8)
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