Session
Move Fast Without Breaking Trust
How to govern workforce AI while the business experiments
PAWorld26 San Francisco · 23–24 September 2026 · San Francisco
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About this session
Blanket prohibition suppresses useful experimentation, while uncontrolled access creates avoidable risk. Ashley Tucker will set out the decisions and operating mechanisms needed before workforce-AI experiments scale: permitted and prohibited uses, data access, anonymisation, validation, auditability, escalation, monitoring and stop authority. A worked scenario will show how business, People Analytics, Technology, Privacy, Legal and Risk responsibilities fit together. The session will also examine what evidence would show that governance is enabling useful experimentation and reducing risk rather than merely producing policy.
Learning outcomes
- Build an approval and escalation map for a workforce-AI experiment.
- Distinguish technical validation, data approval, legal review and business accountability.
- Identify the evidence and stop conditions required before experimentation scales.
This session will explore
- Why blanket prohibition and uncontrolled experimentation both fail.
- A practical map of permitted uses, data access, anonymisation, validation and escalation.
- One worked scenario showing who approves, monitors, challenges and can stop a use case.
- The evidence needed to know whether governance is enabling value and reducing risk.
- Failure modes, limitations and the conditions for wider scale.
Context
A Day 2 Decision Room / Studio technical and foundation session.
Speakers and contributors
Ashley TuckerPresenterDirector, Consulting InsightsVisa