One big factor every CAIO will have to consider is cost; deploying AI models is expensive because cloud providers and proprietary genAI use cases require a lot of computing power — high-end, expensive computing power. And the chips that power learning and inference processes in large language models can cost thousands of dollars. (Nvidia makes most of the GPUs for the AI industry, and its primary data center workhorse chip costs $10,000; the company’s lock on the AI chip market is, however, being challenged by others who hope to undercut it with lower chip prices.)
All federal agencies will have CAIOs
It’s not just private companies looking to hire. In March, US President Joseph R. Biden Jr. gave all federal agencies two months to appoint CAIOs who be responsible for promoting AI innovation, coordinating with other agencies, and managing risks associated with the technology. The 60-day deadline highlighted the urgent need for governance as AI continues its meteoric adoption.
“While AI is improving operations and service delivery across the Federal Government, agencies must effectively manage its use,” Biden’s memo said. “The risks… esult from any reliance on AI outputs to inform, influence, decide, or execute agency decisions or actions, which could undermine the efficacy, safety, equitableness, fairness, transparency, accountability, appropriateness, or lawfulness of such decisions or actions.”