Institutional AI Governance Framework
Create a repeatable governance system covering inventory, ownership, risk, approvals, evidence and monitoring.
Programme components
AI inventory
Designed as a configurable programme component with clear participants, outputs, governance and measurement.
Explore related capability →Roles and accountability
Designed as a configurable programme component with clear participants, outputs, governance and measurement.
Explore related capability →Risk classification
Designed as a configurable programme component with clear participants, outputs, governance and measurement.
Explore related capability →Approval and exception processes
Designed as a configurable programme component with clear participants, outputs, governance and measurement.
Explore related capability →Vendor/model governance
Designed as a configurable programme component with clear participants, outputs, governance and measurement.
Explore related capability →Monitoring and reporting
Designed as a configurable programme component with clear participants, outputs, governance and measurement.
Explore related capability →Programme design
Define population, institutions, outcomes and constraints.
Build modules, governance, delivery and measurement.
Run phased activity with clear owners and support.
Track participation, capability, adoption and outcomes.
Who it can serve
Academy integration
Institutional programmes can incorporate DataLgorithmics Academy courses, custom cohorts, leadership briefings, technical pathways and assessments.
Explore Academy catalogueGovernance and evidence
Programme scope should define responsibilities, privacy, security, procurement, participant data handling, evaluation, reporting and evidence requirements before delivery begins.
Design a Institutional AI Governance Framework
Discuss target participants, geography, programme objectives and delivery requirements.
Discuss this programme