AI Business Operations Fundamentals

Description

Every operations team is being told to "use AI", and most are left to work out alone where it saves real time and where it quietly creates new problems. An assistant that sorts support emails can free up hours every week; the same assistant, trusted blindly, can invent an order number, promise a refund your policy does not allow or file a safety report as a routine question. This course teaches the practical judgment that separates the two. You learn what AI assistants are good and bad at, how to give them clear operations tasks, how to check their work, how to decide which ideas are worth a pilot, and how to use AI safely with customer and company data.

What you will be able to do

• Tell rules, predictive AI and generative AI apart and pick the right one for an operations problem.
• Put a business cost on AI mistakes and decide how much human review a task really needs.
• Write prompts with a role, a task, constraints, examples and a fixed output format, and prove their effect with measured accuracy.
• Turn AI replies into clean, validated tables and catch invented values with lookups and spot checks.
• Map a process from its event log, score AI ideas on value, feasibility and risk, and estimate time saved and return on investment honestly.
• Mask personal data, ground answers in policy text, test decision rules for unfair outcomes and apply an acceptable-use policy.

How the course is taught

You do not need to be a programmer. Every lesson follows the same rhythm: a real situation from operations, a precise explanation with a plain-words summary, a short prepared code demo that you run in Google Colab and that is explained line by line, exercises that ask you to change values and prompts, and the key points to remember. All the work happens inside one fictional business, the outdoor retailer Trailhead Outfitters, so the tickets, policies and processes feel like a real company rather than toy examples.

There is no AI account, API key or payment anywhere in the course. An offline stand-in assistant, supplied as a small file, answers prompts like a chat assistant and imitates the typical weaknesses of real ones, from vague answers to invented details, so you can practise catching them. Every output printed in the lessons comes from actually running the code, so what you read is what you will see. Calls to real hosted assistants are shown for reference but not run.

What is included

Short lessons that move from what AI can do in operations, through working with an AI assistant and choosing and sizing use cases, to using AI safely with company data, followed by a guided project in which you build and measure a triage playbook for a support inbox. You also get the offline stand-in assistant, a set of labeled support tickets, the fictional company's support policy and AI acceptable-use policy, an order-to-ship event log, a list of AI ideas to score, starter and solution notebooks with self-checks for the project, and a quiz drawn from a question bank at the end of every module.

Who it is for

This course is for operations, customer service, supply chain, finance and HR staff who are expected to bring AI into their work, and for the team leads and managers who must decide which AI ideas to back. If you have ever been asked "can't we just use AI for that?" and wished you had a clear, confident answer, this is where you get it. You will finish with a method you can reuse on your own team's processes: map the work, size the idea, write a clear prompt, check the output and route the risky cases to a person. It is the free first step of the AI for Business Operations path, so there is nothing to lose by starting today. Enroll now, open the first lesson and start making AI work for your operations instead of around them.