Insights

The pricing that most organizations have been evaluating AI against was never fully accurate. For the past several years, the leading AI platforms have been priced below the actual cost of delivery, subsidized by capital investment with a strategic logic that was always more about market position than sustainable unit economics. That arrangement is under increasing pressure. The capital markets are asking for returns that current pricing models don't support, and the subsidy that made early AI experimentation feel low-risk is becoming less reliable. For credit unions evaluating these platforms against the same pricing assumptions that shaped decisions twelve months ago, the risk exposure can be extreme: the cost structure of a deployment committed to today may not resemble the cost structure operated against in two years. On a member-owned balance sheet with board-level budget approval, that is not an abstract risk.