Future pathway · Governance and assurance
PEI Responsible AI & Governance Leader Certificate
Establish practical AI oversight through clear controls, human accountability, privacy-aware practice, assurance, and decision rights.
Governance and assurance pathway in development
Join the interest list ↗What you will be able to do
Build capability
that holds up.
- 01
Identify material AI risks and convert them into proportionate, workable controls.
- 02
Define oversight, escalation, review, and accountability across the AI lifecycle.
- 03
Create assurance practices that support useful innovation rather than policy that sits unused.
Proposed learning pathway
From understanding
to applied practice.
- 01
Risk in context
Recognise the operational, privacy, quality, fairness, and accountability risks that matter for a particular AI use case.
- 02
Controls and decision rights
Design policies, approvals, access, documentation, and accountability that match the risk and the work.
- 03
Human oversight and assurance
Establish review points, testing, escalation, incident learning, and evidence for responsible operation.
- 04
Governance that enables progress
Build practical governance into delivery and adoption so it supports responsible use rather than slowing every decision.
How it will be earned
Recognition should follow real evidence.
PEI is designing every assessment-based certificate to reflect more than course attendance. Final requirements and scoring criteria will be published before this pathway opens.
- 01
Complete the governance learning pathway.
- 02
Develop a proportionate governance and assurance case for a realistic AI scenario.
- 03
Demonstrate sound control and oversight decisions in a future applied assessment.
Continue exploring
Start building the
right foundation.
Explore the related learning pathway, then join its founding interest list when it fits your next move.