The Economics of AI: Two-Week Online Course =========================================== A two-week online course on what AI applications cost and what they are worth. Smarter records every model call as a `charge `__, with its tokens and its cost in USD, against the user, the application and the account that made it, priced from a table of `prices per million tokens `__. Self-hosted GPU nodes are charged by the hour from the `price of each compute profile `__, and `Budget manifests `__ turn spending limits into enforced controls, so students measure real costs and test real policies rather than estimate them. There are six 30-minute recorded lectures and a 90-minute live session each week. Week 1 measures costs, and week 2 builds business cases and controls. No programming is needed. See :doc:`../course-formats` for the format, the grading scale and the course policies, and :doc:`../ai-economics` for an overview of the subject. At a Glance ----------- .. list-table:: :widths: 25 75 * - **Students** - Business, economics, finance and management students and professionals. * - **Deployment** - A shared Smarter instance run by the instructor, with at least three models from two or more providers configured. * - **Workload** - 3 hours of instruction and 4 to 6 hours of assignments each week. * - **Cost** - Expect less than $5 USD of model charges per student, capped by a per-student :doc:`Budget `. Learning Objectives ------------------- By the end of the course, students can: 1. Explain how model providers price requests, and what drives the cost of a conversation. 2. Measure and compare the cost, latency and quality of AI tasks across models. 3. Estimate the full cost per user per month of an AI application, including infrastructure. 4. Build a business case with scenarios and sensitivity analysis. 5. Design a budget policy and implement it as enforced controls. Technical Prerequisites ----------------------- - **Required:** a computer with a current web browser, a reliable connection for video calls, and a spreadsheet program. - **Required:** spreadsheet basics: formulas, references and charts. - **Required:** reading a YAML file well enough to change a value (`Learn YAML in Y minutes `__). - **Helpful:** introductory microeconomics and a basic business case or net present value calculation. - **Not needed:** programming. Schedule -------- The files that the lectures refer to are listed in full under `Smarter in the Source Code`_. .. list-table:: :header-rows: 1 :widths: 10 18 72 * - Week - Item - Content * - 1 - Lecture 1 (30 min) - **The unit of AI cost.** Tokens, input and output prices, cached input, and why long conversations cost more than they seem to. * - 1 - Lecture 2 (30 min) - **Quality, latency and cost.** Model tiers, reasoning models, tools and retrieval as cost multipliers, and comparing models fairly. * - 1 - Lecture 3 (30 min) - **Infrastructure.** Fixed and variable costs, the baseline cost of a cluster (about $350 USD a month for Smarter), marginal cost per user, and self-hosting versus paying per token. * - 1 - Live session 1 (90 min) - Live walk through Smarter's cost records and the dashboard. Groups run a model comparison together. Start Assignment 1. * - 2 - Lecture 4 (30 min) - **The business case.** Measurable benefits, adoption curves, scenarios, sensitivity, and what productivity research does and does not show. * - 2 - Lecture 5 (30 min) - **Controlling spending.** :doc:`Budgets `, warnings and limits, :doc:`cost accounting ` and chargeback. * - 2 - Lecture 6 (30 min) - **The bigger picture.** Falling prices, the data center build-out, vendor concentration, labor market effects, and who captures the value. * - 2 - Live session 2 (90 min) - Capstone presentations (about 5 minutes each, with 2 minutes of questions), then a debate: will AI be cheaper or more expensive for businesses in five years? Assignment 1 is due at the end of week 1, Assignment 2 in the middle of week 2, and Assignment 3 and the capstone at the start of Live session 2. Smarter in the Source Code -------------------------- .. include:: source-code.txt Graded Assignments ------------------ Assignment 1: Measured Model Comparison ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Students run twelve realistic tasks on three models from different providers, record cost, latency and a quality score for each from Smarter's records, and reconstruct one cost from the price list. **Turn in:** the spreadsheet, a chart of cost against quality, and a one-paragraph recommendation. .. list-table:: :header-rows: 1 :widths: 22 8 35 35 * - Criterion - Pts - Exemplary - Developing * - Data - 6 - Complete and taken from Smarter's records. - Missing runs or estimates. * - Price list check - 4 - One cost rebuilt from the price list, with any difference explained. - Not attempted, or unexplained mismatch. * - Quality scoring - 5 - Stated rubric applied consistently. - Impressions. * - Recommendation - 5 - Fits a stated use, with the trade-off explained. - Cheapest or best, without reasons. Assignment 2: Cost per User per Month ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Students estimate the monthly cost per user of an AI assistant for organizations of 50, 500 and 5,000 users, combining measured model charges, a usage assumption, and infrastructure, and explain how the cost per user changes with scale. **Turn in:** the spreadsheet and a one-page explanation with a chart. .. list-table:: :header-rows: 1 :widths: 22 8 35 35 * - Criterion - Pts - Exemplary - Developing * - Model charges - 5 - From measurements, with a stated usage assumption. - Guessed. * - Infrastructure - 5 - Fixed and variable costs separated. - Infrastructure ignored. * - Scale analysis - 6 - Shows and explains economies of scale. - Three numbers without explanation. * - Assumptions - 4 - Stated and reasonable. - Hidden. Assignment 3: Budget Policy ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Students design a budget policy for a team of twenty with two AI applications, implement it in Smarter, use up a small budget to show the limit working, and propose the warnings that should come first. **Turn in:** a one-page policy, the budget manifests and screenshots of the limit. .. list-table:: :header-rows: 1 :widths: 22 8 35 35 * - Criterion - Pts - Exemplary - Developing * - Policy - 6 - Limits based on expected use, with reasons. - Arbitrary. * - Implementation - 6 - Manifests enforce the policy. - Do not match the policy. * - Evidence - 4 - Limit reached and shown. - Not shown. * - User experience - 4 - Warnings and messages designed for the user. - Users cut off without warning. Capstone Projects ----------------- Students choose one, and present it in Live session 2. Capstone A: An Investment Proposal for an AI Application ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ **Learning objective.** Build an evidence-based investment proposal, from measured unit costs to a three-year financial model, and present it to decision makers. Students choose a use case in a real or realistic company, build a prototype assistant in Smarter, measure its cost and quality on twenty-five realistic tasks, and use the measurements in a financial model. **What students turn in:** - The prototype manifest and the measured task results. - A three-year financial model with scenarios and sensitivity analysis. - A three-page investment memo, and a five-minute presentation. **How it is graded (100 points):** .. list-table:: :header-rows: 1 :widths: 22 8 35 35 * - Criterion - Pts - Exemplary - Developing * - Measured unit costs - 20 - From the prototype on realistic tasks, quality checked. - From price lists. * - Financial model - 25 - Complete, with scenarios and sensitivity. - Missing categories or scenarios. * - Assumptions and risks - 20 - Stated, sourced, tested; risks include price changes and vendor lock-in. - Hidden assumptions; risks ignored. * - Memo - 20 - Clear recommendation a CFO could act on. - No recommendation. * - Presentation - 15 - Persuasive and on time. - Overruns or reads slides. Capstone B: Build, Buy or Self-Host ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ **Learning objective.** Compare the total cost of ownership of different ways to provide an AI capability, and identify the volume at which the best choice changes. A fictional organization needs an internal assistant for 2,000 employees. Students compare three options: a commercial chat product with per-seat pricing, an assistant built on Smarter with a commercial model provider, and an assistant on Smarter with a self-hosted open model on rented GPU nodes. They measure what they can in Smarter, and research the rest. **What students turn in:** - A total cost of ownership model for each option over three years, including people. - A break-even chart showing which option is cheapest at different usage levels. - A three-page recommendation, and a five-minute presentation. **How it is graded (100 points):** .. list-table:: :header-rows: 1 :widths: 22 8 35 35 * - Criterion - Pts - Exemplary - Developing * - Cost completeness - 25 - Licenses, model charges, infrastructure, people and switching costs. - Only the obvious costs. * - Evidence - 20 - Measured where possible, sourced otherwise. - Unsourced numbers. * - Break-even analysis - 20 - Correct, with the crossover points explained. - Missing or wrong. * - Non-financial factors - 15 - Privacy, control, quality and risk weighed. - Cost only. * - Recommendation and presentation - 20 - Clear, conditional and on time. - No clear choice. Recommended Texts ----------------- - **Required:** Ajay Agrawal, Joshua Gans and Avi Goldfarb, *Prediction Machines: The Simple Economics of Artificial Intelligence* (updated edition, Harvard Business Review Press, 2022). Week 1: parts 1 and 2. Week 2: parts 3 to 5. - **Required:** J.R. Storment and Mike Fuller, *Cloud FinOps* (2nd edition, O'Reilly, 2023), chapters on the FinOps lifecycle and unit economics, in week 2. - **Optional:** Ethan Mollick, *Co-Intelligence* (Portfolio, 2024), on AI and work. - **Smarter documentation:** :doc:`/smarter-platform/cost-accounting`, :doc:`/smarter-resources/smarter-budget`, :doc:`/smarter-resources/smarter-provider` and :doc:`/smarter-resources/smarter-llmhost`. Further Study ------------- .. include:: further-study.txt