The Federal Data Strategy 2026–2030 framework establishes AI-readiness as a core data management requirement, mandating machine-readable formats and metadata standards across all federal data assets.
The White House Chief Data Officer Council released the Federal Data Strategy 2026–2030 on March 7, 2026, establishing AI-readiness as a core data management requirement alongside existing goals of data quality, privacy protection, and interoperability.
The strategy defines AI-ready data as data that is available in machine-readable formats, documented with DCAT-US compliant metadata, labeled with appropriate classification and sensitivity designations, and maintained with lineage records. Agencies must assess their data assets against this definition by December 2026.
The strategy introduces a Data Maturity Index that agencies will self-report annually, covering dimensions of data governance, data quality, data accessibility, and AI-readiness. OMB will use the index to identify agencies requiring technical assistance.
Interagency data sharing is a central theme, with the strategy calling for expansion of the interagency data access program from 12 to 40 participating agencies by 2028. New Interagency Data Sharing Agreement templates will be published by OMB to reduce the current 18-month average time to execute agreements.
GovAcademy's Government Data Strategy and Analytics course (GA-013) and Interagency Data Sharing Agreements course (GA-036) are directly aligned to the new strategy's requirements. Both courses have been updated to include the AI-readiness assessment methodology.
Public Sector Data Visualization (GA-048) addresses the strategy's citizen-facing data transparency goals, covering federal data publishing standards and open data requirements under the OPEN Government Data Act.
The CDO Council has endorsed GovAcademy's data management catalog as meeting the professional development standards recommended in the Federal Data Strategy's human capital appendix.