Sr. Financial Analyst, Corporate FP&A - Enterprise AI

Job Summary

Summary Posted: May 26, 2026 Weekly Hours: 40 Role Number: 20... Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. This is a rare opportunity to shape something new. As Apple deploys AI tools internally at scale, someone needs to be the financial architect of that. You will develop and refine the frameworks, processes, and partnerships that help Apple leadership understand, manage, and plan how its people are using AI day-to-day: the tools they're using, the tokens they're consuming, the efficiencies they're driving, and what it all costs. This role is distinct from the teams working on Apple's AI model development investments and those managing AI costs in customer-facing products. Your lens is the enterprise. You will sit within Corporate FP&A, partnering with IS&T and finance teams across Apple to create a consolidated, coherent view of enterprise AI usage and its associated costs.

Description

Description Develop and refine the forecasting methodology for internal AI usage: Own the approach to forecasting Apple's internal AI consumption assessing current methods, identifying gaps, and building a more robust and scalable model that reflects key cost drivers and how usage evolves over timeStrengthen financial controls: Develop and enhance controls around enterprise AI usage including token consumption, cost attribution, and access governance ensuring visibility and discipline as usage scales Partner with IS&T and other Finance teams on metrics: Work collaboratively to define and interpret the metrics that matter adoption rates, token usage, cost by team or function, and efficiency trends Quantify efficiency and ROI: Partner with business unit leaders to develop frameworks for measuring the productivity gains that enterprise AI tools are driving, translating usage data into a meaningful picture of return on investment Consolidate enterprise AI costs: Design and operationalize the process for consolidating AI-related spend across finance teams company-wide Drive reporting: Develop and maintain reporting that gives senior leadership a clear view of enterprise AI costs, usage trends, and efficiency impact