Managing AI-Augmented Teams & Workflows

People managers learn to redesign roles and workflows for human-plus-AI teams. The course covers workflow redesign, role evolution, quality and oversight, capacity, and team norms. Learners finish able to reorganize work so people and AI each do what they do best.

What this course covers

The course runs across 8 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.

Mapping the Human-AI Workflow — Deconstruct current team workflows to identify bottlenecks and isolate high-value human tasks from automatable AI tasks.
Redesigning Roles: From Doers to Editors — Shift team responsibilities from manual execution to AI prompting, curation, and strategic oversight.
Establishing Quality & Oversight Protocols — Design and implement 'human-in-the-loop' quality gates to mitigate hallucination, bias, and compliance risks.
Managing Capacity & Reallocating Saved Time — Calculate team capacity gains from AI integration and strategically reallocate human hours to high-leverage creative and strategic work.
Co-Creating Team Norms & AI Ethics — Establish clear boundaries, performance expectations, and transparent guidelines for ethical AI tool utilization within the team.
Handling Team Resistance & Anxiety — Address employee fears of displacement through open communication, upskilling roadmaps, and psychological safety.
Iterative Workflow Optimization — Set up feedback loops to continuously monitor, audit, and refine human-plus-AI collaboration models over time.
Capstone Scenario: The Department Overhaul — Synthesize all concepts by leading a simulated department through a complete role and workflow redesign under constrained resources.

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 Ethics, Generative AI Concepts, Critical Thinking, Content Strategy, Data Analysis.

AI Ethics
Generative AI Concepts
Critical Thinking
Content Strategy
Data Analysis

Who it is for

People managers. The material is pitched at intermediate level, and takes roughly 120 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 branching scenario, role play 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.
Manager's AI Leadership Program — Lead a team's day-to-day AI adoption

Frequently asked questions

How long does this course take?

It runs roughly 120 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-MGR.