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

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.

Also in this track

All AI Leadership training courses →
Leading Teams Through AI Adoption — People managers and team leads learn to guide their team through adopting AI in daily work. The course covers setting vision and expectations, redesigning workflows, coaching, addressing fear, and building momentum. Participants finish able to turn AI from a curiosity into a habit on their team.
Running Effective AI Pilots — This course turns AI experimentation into disciplined pilots: tight scope, defined metrics, and honest go/no-go readouts. Learners design a pilot plan for a real use case in their org.
Navigating AI Job-Change Anxiety — A candid course for leaders on the human side of AI adoption: acknowledging real change, holding honest role conversations, and building reskilling paths. Learners practice the hard conversations in role-play.
Board-Level AI Literacy — Governance-grade AI fluency for boards and the C-suite: enough technical grounding to oversee strategy and risk credibly. The course centers on the questions directors should ask and the answers that should worry them.
Running an AI Champions Program — Enablement and program leads learn to stand up and run an internal AI champions network. The course covers selecting champions, enabling them, building community, running feedback loops, and scaling. Learners finish able to grow grassroots AI capability across the org.
AI Adoption Leadership Assessment — Measures whether a leader can identify use cases, plan a pilot, set guardrails and judge results.
Leadership & AI Strategy — Set direction and govern AI adoption
AI Program Leader — Stand up and scale an organizational AI program

Frequently asked questions

How long does this course take?

It runs 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.

How is it assigned to a team?

An administrator assigns it from the Vero dashboard to one person, a team, a department or the whole company, and sees progress and results per person and per skill.

Can we customise it with our own documents and terminology?

Yes. 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.

Course code ADO-UC.