According to a survey by Benchmarkit and Mavvrik, over 85% of organizations misestimate AI costs by more than 10%, with nearly a quarter off by 50% or more. The inaccuracy in budgeting stems from several sources, including unexpected costs related to data platforms and operational requirements. CIOs, in particular, are under pressure as these large cost overruns can undermine their credibility and future project approvals.
Experts suggest that underestimating the costs of AI initiatives threatens stakeholder trust, which is essential for securing future investments. This situation is akin to managing any core infrastructure, where planning and a realistic scope are vital. The stakes are high, as organizations that fail to manage AI costs may also see impacts on their overall financial health, with many reporting that AI expenditures have eroded gross margins by significant percentages.
Best practices for controlling AI costs include employing observability technologies to monitor expenses closely, adopting FinOps practices to enhance transparency across teams, and initiating pilot projects to gain a clearer understanding of actual resource consumption. CIOs should emphasize the importance of disciplined visibility into costs and communicate proactively with departments to avoid unexpected charges. Fostering an environment of cross-team transparency can help organizations better manage their AI investments, ensuring sustainable growth without jeopardizing budgetary constraints.
👉 Pročitaj original: CIO Magazine
