AI Economics: Evaluating Costs, Benefits, and ROI

Integrating artificial intelligence into your business operations can drive incredible value, but without a clear financial strategy, costs can quickly spiral out of control. This course helps you demystify the economics of AI so you can confidently evaluate investments and justify project budgets. You will transition from guessing at AI expenses to systematically analyzing the Total Cost of Ownership (TCO) and Return on Investment (ROI). You will learn how to weigh the financial and operational trade-offs of building proprietary models versus buying off-the-shelf solutions or extending existing platforms. What you'll learn: - Understand foundational AI economic concepts and key terminology before diving into financial models. - Calculate the Total Cost of Ownership (TCO) for AI, including hidden infrastructure, data pipeline, and maintenance costs. - Estimate the tangible and intangible business benefits of AI implementations to project realistic ROI. - Evaluate the financial trade-offs of modern AI architectures, such as API usage fees versus open-source hosting and vector database costs. - Formulate a structured build, buy, or extend decision framework tailored to your organization's resources. - Assess risk factors, compliance costs, and potential liabilities associated with deploying AI solutions. The course begins with core definitions and cost categories, then guides you through building practical evaluation frameworks, comparing implementation paths, and assessing modern cloud and API pricing structures. Designed for business analysts, project managers, and aspiring technology leaders who are new to AI procurement, this course requires no prior programming or advanced finance experience. Start reading today to master the financial side of AI implementation and guide your organization toward profitable technology investments.