AI Center of Excellence: Advanced — Building & Running

A blueprint course for standing up an AI Center of Excellence: charter, structure, staffing, and how it interfaces with governance. Learners draft a CoE design for their own organization.

What this course covers

The course runs across 12 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.

Defining the CoE Charter and Strategic Vision — Establish the foundational mission, scope, and business alignment for your organization's AI Center of Excellence.
CoE Organizational Structures: Centralized, Federated, and Hybrid — Analyze different structural models for a CoE to determine which best fits your organizational culture and scale.
Hands-On Practice: Mapping Your CoE Structure — Use the design canvas tool to draft and configure your organization's custom CoE structural model.
Staffing the CoE: Core Roles and Skill Matrices — Identify essential roles—from AI translators to data scientists—and map the necessary technical and business competencies.
Talent Acquisition and Upskilling Strategies — Develop a sustainable staffing roadmap leveraging external hiring, internal upskilling, and vendor partnerships.
Scenario: Resolving CoE Staffing and Capability Gaps — Navigate a realistic scenario where critical skill shortages threaten AI project delivery timelines, making key hiring and outsourcing decisions.
Designing the AI Project Intake Workflow — Establish a standardized pipeline for business units to submit AI use cases for CoE evaluation.
AI Project Prioritization Frameworks — Learn to evaluate proposed AI initiatives using scoring models based on technical feasibility, business value, and risk.
Scenario: Prioritizing the AI Project Backlog — Evaluate and rank a series of competing AI project proposals under tight resource constraints in a simulated decision exercise.
The Governance Interface: Risk, Compliance, and Ethics — Define how the CoE collaborates with legal, risk, and compliance teams to ensure responsible AI deployment.
Establishing CoE and Governance Board Touchpoints — Design the operational touchpoints, gates, and approval workflows between the CoE and corporate governance bodies.
Hands-On Lab: Finalizing and Exporting Your CoE Blueprint — Synthesize charter, structure, staffing, and governance inputs into a cohesive CoE design document directly within the planning tool.

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.

Who it is for

AI program leads, executives. The material is pitched at advanced level, and takes roughly 150 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 guided lab, 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 →
Scaling AI Adoption: Advanced — Pilot to Organization — The course for the hard step after a successful pilot: sequencing rollout, funding enablement, and building support structures. Learners produce a scale plan with economics attached.
AI Upskilling Programs: Advanced — Program Design — A program-design course for the people building AI training at scale: role-based curricula, assessment-driven placement, and measurement that proves impact. Learners design their organization's full upskilling architecture.
Measuring AI Adoption & ROI: Advanced — Leaders and enablement teams learn to measure adoption, productivity, and ROI of AI initiatives. The course covers adoption metrics, productivity baselines, ROI models, dashboards, and reporting. Participants finish able to prove and improve the value of AI investment.
AI Enablement Delivery: Advanced — Train-the-Trainer — Trainers and enablement leads learn to design and deliver effective internal AI training. The course covers curriculum and delivery, hands-on facilitation, assessment, reinforcement, and measuring impact. Participants finish able to teach AI skills that actually stick.
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.
AI Adoption Leadership Assessment — Measures whether a leader can identify use cases, plan a pilot, set guardrails and judge results.
AI Program Leader — Stand up and scale an organizational AI program
Starting an AI Working Group Pathway — Grow from a small working group into a full center of excellence.

Frequently asked questions

How long does this course take?

It runs roughly 150 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-COE.