Identifying & Prioritizing AI Use Cases
This course helps managers and leads find, evaluate, and prioritize high-value AI use cases. It covers opportunity mapping, weighing value against effort, risk screening, running pilots, and building business cases. Learners finish able to point AI effort where it actually pays off.
What this course covers
This course helps managers and leads find, evaluate, and prioritize high-value AI use cases. It covers opportunity mapping, weighing value against effort, risk screening, running pilots, and building business cases. Learners finish able to point AI effort where it actually pays off.
The course runs across 7 topics, each one a short adaptive session rather than a recorded lecture. The tutor explains the idea, works an example, checks understanding, and adjusts the next step to the answer given.
- Opportunity Mapping: Spotting AI Potential — Learn to analyze team workflows, identify operational bottlenecks, and map potential AI opportunities to solve real business friction points.
- Pitching the AI Concept to Stakeholders — Practice presenting an initial AI concept to cross-functional stakeholders, addressing early pushback, and aligning on business objectives.
- Evaluating Value vs. Effort — Evaluate and score proposed AI use cases by weighing projected business impact against technical complexity and implementation effort.
- Risk Screening and Feasibility Assessment — Screen potential use cases for data privacy, security, ethical implications, and technical feasibility before committing resources.
- Prioritization and Roadmapping Decisions — Navigate trade-offs in a scenario-based exercise to select the optimal 'quick wins' and strategic initiatives for the AI roadmap.
- Defining Pilot Scope and Success Metrics — Formulate clear hypotheses, define measurable KPIs, and scope a low-risk pilot to validate the selected AI use case quickly.
- Building and Presenting the AI Business Case — Synthesize pilot data and risk assessments into a compelling business case to secure executive sponsorship and budget.
Skills you build
Results are measured against named skills in the OneRange taxonomy of more than 10,000 skills, so a manager sees proficiency per skill rather than a completion tick. This course maps to AI Risk Management, Measuring AI ROI, AI Strategy, AI Business Case Development, Identifying AI Use Cases, AI Opportunity Identification.
- AI Risk Management
- Measuring AI ROI
- AI Strategy
- AI Business Case Development
- Identifying AI Use Cases
- AI Opportunity Identification
Who it is for
Managers, leads, ops. The material is pitched at intermediate level, and takes roughly 90 minutes at a typical pace. Because every session adapts, someone who already knows a topic moves through it quickly instead of sitting through an explanation they do not need.
It sits in the Adoption & Leadership track of the Vero AI Catalog, and can be assigned to one person, a team, or the whole company.
How it is delivered and assessed
Delivery is conversational and interactive, including role play, branching scenario exercises. There is no video to sit through and no slide deck to click past.
Understanding is checked with a lab assessment of 5 items, with a pass mark of 70%.
Administrators can copy this course into their own library and adapt it — edit the outline, change the duration, swap the assessment format, or ground it in internal documentation so answers cite the company's own source material.
Related
- Browse the full Vero AI Catalog
- How the OneRange platform assesses and measures skill
- What OneRange Vero is
Course code ADO-UC.