AI GUIDE FOR BOARDS IN SINGAPORE
Section V: Organisational Resilience and Capability
Data Sensitivity Classification: Examples
Minimal restrictions; integrity and version control still required Governance expectations
Classification Description
Examples
Public
Marketing materials, published
Information approved for unrestricted public disclosure Non-public information intended for internal organisational use Sensitive business or customer information requiring stronger protection Highly sensitive information where unauthorised disclosure could cause signi cant legal, regulatory, operational, or reputational harm
reports, public website content
Internal
Restricted to employees and
Internal policies, operational procedures, sta communications
authorised contractors
Con dential
Access controlled on a need-to-know basis; encryption and monitoring typically required Strictest controls including enhanced encryption, privileged-access management, segregation, and heightened monitoring
Financial data, customer records, contracts, business plans
Restricted (or Highly Con dential)
Personal data, regulated nancial information, security credentials, merger and acquisition data, critical intellectual property
11.3.2 Access controls
Boards should ensure management has enterprise-wide classi cation standards, consistent labelling practices and aligned controls with data sensitivity levels. Eective classi cation helps determine who can access data, how it may be used, retention requirements, encryption standards and whether AI systems are permitted to process the data.
Boards should ensure that access rights are role-based and appropriately restricted. Privileged access should be monitored, as should access to external providers. AI teams and systems o en require broad access to enterprise information. Without appropriate controls, this can signi cantly expand the organisation’s attack surface and governance risk.
Boards should understand which datasets are considered strategically critical to AI performance and operational continuity.
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