FinOpsPod

Episode 42 James Barney - The AI Episode James Barney discusses the complexities and nuances of applying FinOps principles to AI usage in the cloud, explores various models of AI consumption, such as SaaS and self-hosted solutions, and delves into the challenges of accurately tracking and managing AI costs. Insights are shared from James Barney's recently contributed paper on AI cost management, emphasizing the importance of understanding AI's impact on cloud expenditures and business value. The conversation also touches on the necessity of open dialogue within organizations and the potential for AI to enhance non-customer-facing processes. Practical advice is given on how to approach AI cost management conversations and the value of learning by doing.Note - views expressed by James are his alone and not those of his employer.03:59 Understanding AI Cost Structures05:38 FinOps Strategies for AI Workloads12:10 Balancing Innovation and Cost Control18:08 Tracking and Reporting AI Costs19:34 Understanding AI Workloads21:39 Guardrails for AI Usage22:45 The Role of Context in AI25:16 Politeness in AI Interactions28:03 Exploring AI Tokens31:35 Challenges in AI Cost Management35:41 Community Involvement in AIJames Barney | LinkedInCost Estimation of AI WorkloadsHow to Forecast AI Services Costs in CloudHow to Build a Generative AI Cost and Usage Tracker