AI Transformation Capstone: Executive Brief

IBM via Coursera

Go to class Write review

Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

Unlock All Certificates

In this IBM capstone, step into the role of a senior transformation leader at a sample global enterprise. Wrangle many business units, real constraints, AI initiatives stuck between pilot and scale, and produce a board-ready AI Transformation Executive Brief. This guided project asks you to apply leadership skills you developed in the previous courses of the Professional Certificate. Select and justify two or three high-value use cases, backed by an honest read of organizational readiness. Lay out a phased transformation roadmap and the operating-model decisions each phase demands. Define a governance and risk framework that names accountability, decision rights, and top risks with their mitigations. Close with a change-and-value plan: an ROI model and concrete KPIs for years one and two. Your brief will showcase how you apply frameworks, reason strategically, integrate across themes, and communicate with executive clarity. Finish with a portfolio-grade work sample you can put in front of employers and board, demonstrating that you can do adapt to your enterprise’s changing AI landscape, focused on the metrics that matter.

Syllabus

Choose the Bets: Select and Justify AI Use Cases.
- Your board has asked what the return on the enterprise's AI investment has been, and leadership can show activity but not value. In this stage you take the seat of a Chief AI & Transformation Officer and write the first section of an AI Transformation Executive Brief: use cases and readiness. Seven AI initiatives are already running across the enterprise, and you are handed the evidence on each of them and a verdict on none. You score all seven on data, talent, infrastructure, workflow and value, pointing every score at the passage behind it; you give each one a disposition — invest, govern, defer, policy or retire — and you name the two or three you would fund and say what you chose them over. Then you write it the way a board reads: one page where every sentence decides, with your assumptions, findings and open questions filed underneath it.
Sequence the roadmap
- A portfolio of funded AI initiatives is not yet a plan. In this stage of the capstone you decide when the enterprise does what it has already chosen to do, and what each phase has to prove before the next one is allowed to start. Working from a readiness pack that separates a workflow problem from a data problem, you place every initiative you funded into three fixed phases, land a quick win first, and name for each phase what it grounds and what its evidence releases. You choose one operating-model decision per phase — who owns delivery, what the work runs on, how money is released, who is made able — and you state the investment by phase and the incremental benefit by year. The output is the second section of your AI Transformation Executive Brief: a one-page roadmap and operating model a board could fund phase by phase, against gates carrying the authority to stop.
Govern the Risks
- A portfolio with owners nobody named and systems nobody authorized is not governed, however many principles it endorses. In this stage of the capstone you decide who is accountable for each AI system and for the program itself, what each system may decide without a person in the path, and which five risks a board is asked to carry. Working from two evidence packs — a hiring screen that cannot reconstruct its own contribution to a decision, and an operations agent taking thousands of actions a week and asking to take more — you set a decision-rights setting for every system touching consequential decisions, separate the autonomy a system was authorized to have from the autonomy its records can actually support, and build a five-row risk register in which every mitigation names a condition somebody could later test rather than an activity somebody could merely run. The output is the third section of your AI Transformation Executive Brief.
Prove the value
- A program with a roadmap and a governance framework still has to say what it is worth. In this stage of the capstone you decide how the change is made and how the value is proven — the point at which the brief stops describing intent and starts committing to numbers a board can hold you to. Working from an adoption survey, a set of documented metric baselines and a generated ROI workbook, you finish a change plan around the management layer that has to act differently, classify every benefit line as hard ROI, soft ROI or strategic option value with the reason attached, and name the assumption that closes each gap between what a sponsor claims and what is observed today. You then set a KPI for every bet, each carrying a baseline and targets for both years. The output is the fourth section of your AI Transformation Executive Brief: a one-page change and value plan in which every figure can be checked.
Assemble and present
- Four good sections are not yet a brief. In this stage of the capstone you assemble the use-case, roadmap, governance and value sections into one AI Transformation Executive Brief and find out, for the first time, whether they were ever really one argument. You place each section into the master template slot for slot, gather and deduplicate the appendices behind it, and then run an integration check by category rather than by section — candidate names, phase names, owners, KPI names and figures, each with a recorded result — repairing every mismatch in the section that carries it rather than in the summary. You confirm that each of the five questions leadership could not answer has a place in the brief a reader can be pointed to. Then, last, you write the one page that opens with the answer: what the enterprise can document today, what you propose, what you are not proposing, the risks you are carrying, and what you need from the board.