According to a recent LinkedIn post from Maven AGI, the company is drawing attention to two recent Gartner forecasts on the economics of AI in customer service. The post notes that Gartner projects cost per AI resolution could exceed $3 by 2030 and that more than half of customer service organizations may double technology spend by 2028 without materially reducing headcount.
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The post suggests that, if both forecasts hold, technology spending might rise while labor costs remain largely unchanged, potentially eroding the expected cost advantage of AI over offshore human agents. Maven AGI’s commentary introduces the concept of a “resolution gap,” defined as the difference between interactions AI touches and issues it fully resolves.
According to the post, closing this resolution gap is positioned as critical to ensuring AI spend substitutes for, rather than layers on top of, agent payroll. For investors, this framing underscores a key efficiency hurdle in enterprise AI adoption and highlights a potential demand driver for solutions that improve end-to-end resolution rates.
The company’s LinkedIn post also points readers to a new analysis on the Maven AGI blog that reportedly details the underlying spend math and examples of “resolution-first” implementations in production. If the market increasingly focuses on measurable resolution outcomes, vendors able to demonstrate clear reductions in total support cost per resolved issue could strengthen their competitive position and pricing power within the customer service technology stack.