AI Enablement for Managers: Make AI Work on Your Team

Name: AI Enablement for Managers: Make AI Work on Your Team
Rating: 4.5 (88 reviews)

AI change management training for leading AI adoption, reskilling employees, and integrating AI into workflows

Created byNicolle Merrill

Last updated 2/2026

English

English [Auto],Lithuanian [Auto],

What you'll learn

Indentify where AI can transform team workflows
Define clear metrics to track AI’s impact
Equip and support AI champions on the team
Guide the team in producing and judging quality AI outputs
Build trust and transparency by communicating AI’s purpose, value, and limits
Ensure AI adoption on the team ladders up to business goals
Foster a culture of continuous learning by integrating AI upskilling into everyday work
Coach team members in building AI-related skills
Model responsible AI use
Differentiate between AI hype and realistic opportunities to guide team adoption

Course content

7 sections • 30 lectures • 2h 36m total length

Introduction to the course2:41
Lead your non-technical team through AI adoption with practical change management tactics, coaching, and use-case standardization, while building prompting skills and responsible AI practices for real impact.

How generative AI has changed the workplace6:43
The role of managers in AI transformation (+ team assessment)6:53
Managers guide AI adoption by fostering experimentation, clarifying how AI fits into work, and removing barriers. Use a team assessment to measure adoption stage and guide integration of AI workflows.
Five ways managers support AI use on their teams2:21
Facilitate AI fluency, communicate guidelines and guardrails, coach teams, identify AI use cases and workflows, and manage AI risk to support effective AI adoption.
CHECKLIST: Your first week: Getting started with AI on your team1:22

Building AI fluency skills across your team2:53
Build AI fluency across your team by developing AI literacy, prompting, data fluency, and critical evaluation, guided by ongoing experimentation and adaptability with generative AI tools.
Improving your team's prompting & iteration skills4:47
Improve your team's prompting and iteration skills by learning to give clear instructions, iterate on outputs, and use structured prompts with persona, task, context, and format.
Building your team's data literacy skills4:30
Build data literacy by learning to select data to personalize ai outputs and connect data to tools like drive and Notion.
Championing critical evaluation & human oversight7:55
Develop critical evaluation and human oversight to vet AI outputs for bias, inaccuracy, and appropriateness, and clarify when humans should override AI in workflows.
Generative AI's impact on your (and your team’s) work7:59
Discover how generative AI shifts work from doing to managing AI outputs, setting standards for tool use, and mapping AI use to business goals while sharpening communication and critical thinking.
TEMPLATE: Team AI practice session1:26

Communicating Responsible AI use7:37
Managers establish guardrails and responsible AI policies to guide tool use and data privacy. They communicate policies clearly, answer questions, and model safe AI use for fairness and accuracy.
TEMPLATE: Team AI use guidelines1:16
Defining quality work with AI4:15
Define what good AI outputs look like for your team to prevent work slop and protect productivity and trust. Use one-on-one and team reviews, prompts, and formatting to ensure quality.

Creating psychological safety on your team7:22
Creating a learning environment for AI6:10
Create a learning environment for AI by fostering psychological safety and curiosity, enabling hands-on experimentation with prompts and shared learnings. Support hack weeks, team discussions, and celebrations of AI learnings.
Coaching teams through responsible AI use5:00
Coach teams through responsible ai use by modeling its application, guarding data privacy, and answering questions tied to daily work. Guide iteration and upskill to sustain learning.
Finding AI champions to support team AI adoption5:04
Identify AI champions as curious, self-directed power users who experiment with generative AI, share practical tips, and accelerate team learning and adoption.
Navigating awkward conversations about AI10:14

Understanding AI use cases and workflows5:50
Identifying AI use cases on your team8:35
TEMPLATE: AI Use Case Proposal Form0:48
Transforming AI use cases into AI workflows8:05
This is an example of an onboarding prompt template that you would create to standardize your AI workflow. Prompt templates make it easier for people to use AI and standardize prompts and their outputs.
Evaluating data for your AI workflows2:47
Choosing AI tools for your team5:14
Using AI Agents on your team15:17
Documenting AI workflows1:55
Document AI workflows to standardize processes, capturing step-by-step where AI assists and where humans lead, prompts, tools, quality checkpoints, and examples of strong outputs as a living resource.
Measuring AI success4:07
Track AI success by measuring time saved, quality, and adoption, then benchmark against your business goal and report results to leadership.

Requirements

No technical background required. Experience with Generative AI is helpful but not required.

Description

Managing AI on a team is no longer optional. Managers are now responsible for how AI changes work.

Your team is already experimenting with AI. Some employees are using it daily. Others are hesitant or unsure. Leadership is asking for results, but there is no clear playbook for how teams should actually use AI.

Your role as a manager now includes guiding how AI fits into your team's workflows, roles, and skills.

This course shows you how to lead AI adoption as a management challenge rather than a technical one. You will learn how to redesign work with AI, support role evolution, and help your team build the skills needed as AI becomes part of everyday work.

It is designed primarily for managers leading non-technical teams.

You will learn how to:

Identify where AI can improve team workflows and where it should not be used
Redesign work with AI instead of simply adding tools to existing processes
Help team members build the AI skills needed for their roles
Address resistance and employee concerns about AI
Turn scattered experiments into consistent team workflows
Set expectations for quality, risk, and responsible AI use
Communicate clearly with leadership about your team's progress

These strategies come from working with managers who are leading real teams through AI adoption and navigating the challenges that come with changing workflows and evolving job responsibilities.

This course is for you if:

You manage people who do knowledge work
Your organization is pushing AI adoption
You need to figure out how AI fits into your team's workflows
You are responsible for helping your team adapt their roles and skills
You want a practical system for managing this change

No technical background required. This course focuses on managing people, redesigning work with AI, and guiding your team through AI adoption.

Who this course is for:

People managers (mid-level or frontline managers) who directly lead teams and are responsible for performance and employee development.
Managers with a mandate to increase AI adoption and meet strategic priorities
Talent teams who support employee growth, reskilling, and career pathways in an AI-powered workplace

AI Enablement for Managers: Make AI Work on Your Team

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 3min

Guiding teams through AI implementation and change4 lectures • 17min

Upskilling teams for AI fluency6 lectures • 30min

Enabling teams to use AI responsibly3 lectures • 13min

Coaching teams on AI use5 lectures • 34min

Integrating AI into your team workflows9 lectures • 53min

Creating a continous learning environment2 lectures • 7min

Requirements

Description

Who this course is for: