While executives debate job displacement, CIOs face a quieter challenge: AI work that spreads across teams blurs ownership and doesn't fit the The invisible laborg chart.

The loudest conversations about AI and jobs focus on what disappears. Inside IT, the more immediate problem is what quietly multiplies. As AI capabilities spread across the stack, they splinter work into new, poorly defined skill demands: prompt engineering here, orchestration there and model evaluation somewhere in between. None of it aligns neatly with existing roles, reporting lines, or hiring frameworks.

The result is an accumulation of invisible labor. Critical, unscoped work is absorbed by already stretched teams, bypassing formal ownership and eluding traditional workforce planning. For CIOs, the risk isn't just a skills gap. It's an operating model that can no longer see, measure or manage the work required to run AI at scale.

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