Are your AI metrics telling the whole story?

Many organizations measure AI success primarily through efficiency and output: hours saved, tasks completed, tickets closed, and code produced. Those metrics matter, but are not enough to show whether AI-enabled work is sustainable, trusted, equitable, and strengthening the workforce over time. Catalyst’s research on women using AI at work points to a critical measurement gap: AI can appear successful on productivity dashboards while creating hidden costs for employees and the organization.

As found in previous Catalyst research on sustaining growth in times of disruption, technology alone does not deliver sustainable transformation. Leading organizations go beyond narrow measures and instead look at the full picture to determine AI success and to reveal where apparent progress may be masking added workload, credibility pressure, talent risk, and other hidden costs. Developing these more advanced measures can help leaders ensure that AI is enabling people and the organization to adapt, innovate, and grow over time.