AI Operations Strategy and Governance

Description

Most companies no longer ask whether AI can help their operations. They ask which of the many ideas to fund, how to know whether a pilot really worked, why a tool that worked for one team stalls in the next, and how to keep a growing set of AI tools safe, compliant and worth their cost. These are leadership questions, and they are rarely answered with numbers. This course teaches you to answer them the way a careful operations leader would: put a defensible value and a full cost on every use case, measure pilots against a control group instead of anecdotes, scale only through gates with owners, bring people along with honest change plans, and govern every tool with a risk assessment, an inventory and monitoring after launch.

What you will be able to do

• Build an AI business case with total cost of ownership, net present value and payback, and test it against optimistic estimates with a simulation.
• Measure the value of a pilot with a baseline and a control group, and design pilots with success criteria, guardrails and stop rules fixed in advance.
• Decide between building, buying and partnering with a weighted comparison, and evaluate vendor proposals on three-year cost and contract terms.
• Set scaling gates, plan rollouts in waves, choose an operating model and assign ownership with a checked RACI.
• Diagnose stalled rollouts from adoption data, redesign roles task by task, track an adoption funnel and write change messages without overpromises.
• Assess AI risk per use case, map the portfolio to the structure of the EU AI Act, ISO/IEC 42001 and the NIST AI RMF, keep an AI inventory and audit trail, and monitor value and incidents after launch.

How the course is taught

Every lesson follows the same rhythm: a real situation from a company's first year with AI, a precise explanation with a plain-words summary, a prepared code demo you run in Google Colab, exercises that change assumptions and see what happens, and the key points to remember. The whole course follows the fictional outdoor retailer Trailhead Outfitters as it moves from a handful of AI tools to a managed portfolio: its twelve use cases, two pilots with control groups, a sixteen-week rollout across four teams in which one team stalls, and three vendor proposals with very different small print. You never write a program from scratch; you run, read and adapt explained code.

The analysis is honest about its limits. When a before-and-after comparison understates a pilot's effect, the lesson shows why; when the teams' own estimates are optimistic, the simulation takes the optimism out and shows what the portfolio is still worth. Regulations are explained at the level of their structure, as preparation for a conversation with legal counsel, not as legal advice. No AI account, API key or payment is needed: an offline stand-in assistant drafts announcements and summaries, including the overpromises you will learn to catch. Every output in the lessons comes from actually running the code.

What is included

Short lessons that move from building the business case, through piloting and scaling, to leading the change and governing AI after launch, followed by a guided project in which you write Trailhead's AI rollout plan for its leadership team. You also get Trailhead's AI use-case portfolio, weekly results of two pilots with control groups, sixteen weeks of adoption data from four teams, three vendor proposals, a helper module with the course's techniques, the offline stand-in assistant, 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 leaders, heads of shared services, transformation and program managers who are responsible for AI in their organisation, and for the risk, compliance and IT governance staff who oversee it. It is also the natural last step of the AI for Business Operations path, for anyone who has automated tasks and supported decisions with AI and now wants to lead its adoption. If you have ever been asked to justify an AI budget, watched a promising pilot drift for months, or wondered whether anyone knows every AI tool in use at your company, this course gives you the methods and the confidence to answer. You will leave with a complete, checked rollout plan and a way of working you can apply to your own portfolio next week. Enroll now and turn AI in your operations into a program that leadership can fund, people can trust and auditors can follow.