Session
Measuring Performance in the Age of AI: Lessons from Togetherwork
What activity data can and cannot tell us about performance, workload and trust
PAWorld26 NYC · 4–5 November 2026 · New York City
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– · Work Design
About this session
As AI changes how work gets done, familiar activity measures may become harder to interpret. David Kuhl explores performance measurement in the Togetherwork context, considering activity alongside actual outcomes, workload and employee experience. Examine how to choose useful measures, recognise misleading conclusions and set fair boundaries before managers act.
Learning outcomes
- Distinguish an activity signal from a performance conclusion.
- Identify a fairness or context question to resolve before using a measure.
- Specify evidence needed to substantiate a claimed business benefit.
This session will explore
- Activity data considered alongside outcomes, workload and employee experience.
- Measure selection and the risk of drawing misleading conclusions.
- Fair boundaries and the evidence needed for responsible performance decisions.
Context
Activity measures can be easy to collect and difficult to interpret. Decisions about performance need to account for outcomes, employee experience and changing work before managers infer that visible activity represents value.
Speakers and contributors
David KuhlPresenterEVP, Chief People OfficerTogetherWork