In a recent insight, Moorhouse highlights that Generative AI has rapidly moved from experimentation into practical use, with many organisations already seeing early benefits. However, as adoption grows, costs are rising in ways that can be difficult to predict or explain.
The firm highlights that AI is no longer a future bet, it’s an active investment. Boards expect progress, regulators expect oversight and markets expect returns. But the economics of AI don’t behave like traditional technology spend. Costs scale with usage, not licences. In more complex setups, such as multi-agent systems, token consumption can increase rapidly and unpredictably. What looks like a technical issue is often something deeper: how work is structured, how automation is applied, and how decisions are governed. If those foundations are weak, AI doesn’t fix the problem, it accelerates it. You can’t solve this through forecasting alone. If workflows are inefficient, AI will simply make them more expensive, faster.
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