In this module, you will acquire the analytical discipline that underpins everything that follows. You will learn to decompose any business process into the six elements automation acts on — triggers, inputs, decisions, actions, exceptions, and outputs — capture it with a lightweight mapping notation, and judge whether the process is genuinely ready for AI augmentation. The lab has you map and classify a provided invoice-exception process and write a readiness assessment.

In this module, you will take on the practical work of finding and qualifying the right processes to automate. You will run structured discovery interviews, conduct non-intrusive observation, and interpret process mining output at a business-analysis level, then move from a long list of candidates to a defensible prioritized shortlist using a value-versus-feasibility framework you can defend in front of stakeholders. The lab combines a simulated interview, a mining reconciliation, and a scoring exercise.

In this module, you will turn a chosen process into an AI-augmented future-state design and then into a fundable business case. You will decide where humans stay in the loop and at what confidence thresholds, design exception paths so the assistant fails gracefully, estimate ROI you can defend, and frame risk and adoption honestly so decision makers can act. The lab produces a complete future-state map and a business case for a process from earlier labs.

In this final module, you will assemble everything from Modules 1 through 4 into a cumulative project: a Process Opportunity Portfolio. The deliverable is a discovery summary, a prioritized shortlist with scoring rationale, a future-state design with human-in-the-loop checkpoints and exception paths, and a business case with a recommendation on which process should advance into the build phase. The module closes with a wrap-up featuring an SME interview, a day-in-the-life view of an Automation Business Analyst, and a bridge into Course 2's hands-on build work.