Enterprises weigh three AI infrastructure models as cost scrutiny grows
A new framework for enterprise AI spending proposes tracking 'effective cost per useful outcome' rather than raw compute costs. It outlines three approaches companies use to run AI workloads: building a bespoke in-house stack, using on-demand hyperscaler consumption, or deploying an integrated private AI platform with dedicated capacity.