Capability 2.2.6
Enterprise & Business
Definition
Proprietary datasets held by private companies for in-house AI training, modelling and deployment. Includes operational, customer and sensor data across sectors, such as mining, telecommunications and finance.
Examples
- Examples include customer data at banks, sensor data from mining or utilities, and operational data from telecommunications networks.
Indicators
- Although difficult to measure directly, the inclusion of this category acknowledges that a substantial portion of Australia’s AI capacity resides within business-owned data ecosystems. Recognising their existence ensures a more complete picture of national data capability, even where transparency or benchmarking is not currently possible
- Standardised metadata schema
- Federated compliance and scalability (legal and institutional interoperability)
- FAIR compliance (findable, accessible, interoperable, reusable)
- CARE compliance (collective benefit, authority to control, responsiblilty and ethics)
- Provenance and lineage tracking
- Consent frameworks
- Onshore hosting and secure processing environments (e.g. SURE)
- Clear licensing
- Longevity and version control
- Domain specific data standards
- Machine readiness formatting
National AI Plan
PLAN COMMITMENT
Limited commitment
See general comment at 2.2.1 (Language, Arts, Culture & History). Links AI adoption in business to the use of high-quality, trusted data (Action 4, p18), but does not include specific initiatives to unlock enterprise and business data, with references remaining broad and adoption-focused. Warrants attention to work with the private sector to better understand current maturity (given this capability could generate very high agency and leverage).
Stocktake
No existing research surfaced through consultation.
Is the Stocktake missing evidence?
Share additional information for potential future Assessments