AI Value - FinOps AI
- Course Code FINOPS-AI
- Duration 1 day
Course Delivery
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Course Delivery
This course is available in the following formats:
-
Company Event
Event at company
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopMaster the true cost of AI in production - Scale AI Prod without "Bill Shock"
As AI flows into each company, there is an urgent need to avoid: "for every $1 of revenue generated, $ 4 spent on infrastructure! ".
This course will help you master concepts, use cases, and cost drivers for AI value.
During the training you will use a pragmatic framework as an optimization lever and get inspiration from actionable use cases: lower costs, higher ROI.
Updated 09/10/2026
Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
Course Schedule
TopTarget Audience
TopThis course is targeting all people interested to discover how to understand and measure the AI Value.
Course Objectives
TopAfter this course, participants should be able to:
- Gain expertise in optimized AI cost management
- Translate complex AI cost structures into reliable insights
- Take informed strategic decisions (KPIs, governance)
Course Content
TopModule 1:
- Strategic introduction: challenges, ecosystem, multimodal, conceptual basics
- Tokenization, inference (input/output), prompts, benchmarking...
- AI Architecture, tech stacks, Tokenonomics (cost per Token, KV cache...)
Module 2:
- AI FinOps Framework architecture, rate optimizations, usage, licenses, benchmarks
- Unit Economics and KPIs for ROI calculations and associated Operating Model
- Governance patterns: context engineering, prompt, RAG, fine-tuning, linear > agentic
Module 3:
- Use case #1 - LLM + context vs. LLM + RAG: injection vs. indexing cost comparison
- Use case #2 - SLM vs. LLM: quant/qual comparison on a Business IT process
- Use case #3 - A/B workflow comparisons: models, injection, guardrails...
Course Prerequisites
TopParticipants should have some level of awareness about AI and Finances mechanisms and concepts like KPIs, ROI.
Test Certification
TopNo certification
Follow on Courses
TopNo specific recommendation
Further Information
Top- Course book provided to participants
