AI adoption is accelerating—but many organizations are running into a less visible barrier: the work required to make AI succeed doesn’t align neatly with traditional roles, teams, or org charts. As highlighted in a recent InformationWeek interview, this “invisible labor” is quickly becoming a defining challenge in scaling AI.
From governance and model oversight to workflow redesign and cross-functional coordination, AI introduces new responsibilities that cut across IT, clinical, and operational functions. The demand is clear—but ownership often isn’t. Without a defined operating model, even well-funded AI initiatives can stall.
Zack Tisch of Pivot Point Consulting points to this gap as a critical inflection point for organizations moving beyond experimentation:
“The work that makes AI successful often isn’t visible on an org chart—but it’s essential.”
Organizations that recognize—and operationalize—this hidden layer of effort will be the ones that turn AI investment into measurable impact.
Read the full interview to explore what’s driving the invisible labor gap—and how leading organizations are addressing it.
