AI ROI framework

Master B2B’s reporting on AI spending has made the case that raw cost comparisons are misleading on their own. A widely cited example is a small startup that drew criticism for its AI token bill, which looked expensive next to a single employee’s salary until the speed, scale, and output the tooling enabled were factored in. A more complete ROI framework weighs the outcome delivered, revenue enabled, time saved, or errors avoided, against the full cost, not just the sticker price of the tool but any organizational change needed to use it well. The hosts have also cautioned against measuring agentic and AI investments primarily by incremental revenue, since much of the early return in B2B shows up as efficiency and cost-to-serve improvement rather than new sales.