Course description
ChatGPT Edu pricing is not published by OpenAI, Claude for Education has no public list price, Gemini for Education is included free in Google Workspace for Education, and Microsoft 365 Copilot for academic users has a stated per-user price. That mix is why campus AI budgets are hard to compare and why 41 percent of institutions told EDUCAUSE in late 2024 that they do not know how their AI costs are covered. This course teaches a vendor-neutral method for building a three-year campus AI total cost of ownership model. You will read the one fully public case, the California State University contracts with OpenAI as reported by LAist and CalMatters, and turn the reported totals into per-user arithmetic that you label as your own. You will compare per-seat, consumption and owned-platform pricing under different utilization assumptions, inventory the hidden lines (integration, training, support, evaluation, exit), and account for inference prices that Epoch AI found falling 9x to 900x a year. You will leave with a sensitivity-tested workbook and a one-page brief a CFO can act on, with every price dated.
About this course
ChatGPT Edu pricing is not published by OpenAI, Claude for Education has no public list price, Gemini for Education is included free in Google Workspace for Education, and Microsoft 365 Copilot for academic users has a stated per-user price. That mix is why campus AI budgets are hard to compare and why 41 percent of institutions told EDUCAUSE in late 2024 that they do not know how their AI costs are covered. This course teaches a vendor-neutral method for building a three-year campus AI total cost of ownership model. You will read the one fully public case, the California State University contracts with OpenAI as reported by LAist and CalMatters, and turn the reported totals into per-user arithmetic that you label as your own. You will compare per-seat, consumption and owned-platform pricing under different utilization assumptions, inventory the hidden lines (integration, training, support, evaluation, exit), and account for inference prices that Epoch AI found falling 9x to 900x a year. You will leave with a sensitivity-tested workbook and a one-page brief a CFO can act on, with every price dated.
What you will be able to do
- Build a dated price sheet for the four major campus AI offerings that separates published list prices, campus chargeback rates and contract-reported totals, and states what is unknown.
- Convert a public contract's reported total and user count into a per-user annual figure, label it as derived arithmetic, and state the assumptions (term length, user definition, utilization) that the figure does not carry.
- Model the same campus population under per-seat, consumption and owned-platform pricing and show how each cost line responds to utilization, headcount and price change.
- Inventory the non-license costs of a campus AI deployment (integration, data governance review, training, support, evaluation, exit) and assign each an owner and an estimate source.
- Run a sensitivity analysis on a three-year TCO workbook with an AI agent and verify that every output traces to a formula and a dated source.
- Write a one-page TCO brief for a CFO that includes the ROI measures agreed before purchase and the re-verification schedule for every price in it.
Who this course is for
Roles: chief financial and chief business officers, CIOs and IT finance leads, procurement and contracts officers, provosts and vice provosts who sponsor AI initiatives, budget analysts, and institutional research staff asked to measure return.
Institutions: public university systems negotiating system-wide licenses, regional public universities, private nonprofit colleges, and community college districts buying chatbots or assistants for the first time.
Before you start: comfort with a spreadsheet and with reading a vendor contract. No technical background is required. The lab uses an AI agent through a browser on a supplied sample budget workbook.
Format
- Estimated time: 10 to 12 hours.
- Level: intermediate. Assumes you hold or advise on a budget; assumes nothing about AI.
- Hands-on: one lab on a supplied sample budget workbook (a fictional 12,000-student campus with three pricing scenarios), five templates you keep, two discussions, and a capstone on your own institution's numbers.
- Structure: 4 sections, each ending in an AI conversation assessment, then a capstone assessment.
Self-paced. Every lesson is taught by an AI tutor that opens with a short story and works through one idea and one question at a time. Each section ends with an AI conversation assessment, and the course closes with a capstone assessment. Section assessments count for 60% and the capstone for 40%; 70% passes. There are no multiple-choice quizzes.
Currency of this course
Last verified 2026-09-28. Prices last verified: 2026-09-28. Vendor list prices, promotions and contract terms move every term. Every price in this course carries the date it was read, and every per-user figure derived from a public contract is labelled as the course's own arithmetic. Re-check each vendor page and the cited contract reporting before putting any number in a budget.
Outline
Section 0 · Start here
- 0.1 Orientation
Section 1 · Why campus AI cost needs a model
- 1.1 The state of AI budgeting
- 1.2 The one fully public case: California State University
- 1.3 Section 1 assessment
Section 2 · The price sheet: what vendors publish and what they do not
- 2.1 Published prices, chargebacks and unknowns
- 2.2 Three pricing models
- 2.3 Section 2 assessment
Section 3 · The hidden lines: utilization, integration, support and exit
- 3.1 Utilization is where per-seat arithmetic breaks
- 3.2 Integration, training, support and custom builds
- 3.3 Price trends and contract term
- 3.4 Section 3 assessment
Section 4 · Building and defending the TCO model
- 4.1 The three-year workbook
- 4.2 Governance, ROI and the brief
- 4.3 Section 4 assessment
Section 5 · Capstone & wrap-up
- 5.1 Capstone
- 5.2 Capstone assessment
- 5.3 Wrap-up