AI literacy for managers and team leaders

For managers and team leaders: choose good AI use cases, set clear team rules, assure quality, lead the change lawfully and measure what really improves.

For: Managers, supervisors and team leaders responsible for how their teams adopt and use AI tools

  • 2 contact hours
  • 6 modules
  • 8 interactives
  • 5 job aids
  • Updated October 11, 2026

What you will be able to do

  • Explain what AI can and cannot reliably do for a team and select use cases using a value-and-risk assessment.
  • Set team expectations for AI use that comply with organizational policy, address unapproved tool use, and plan staff upskilling.
  • Design risk-tiered quality assurance and clear accountability for AI-assisted work, including incident response.
  • Lead AI-related change by addressing staff concerns and respecting employees' NLRA Section 7 rights, including in unionized workplaces.
  • Measure AI's impact on team outcomes fairly and recognize legal and ethical red flags that require escalation.
  • Build and run a 90-day action plan for responsible AI adoption on your team.

This course gives managers the AI literacy they need to lead, not just use, AI at work. You will learn how to judge which use cases are worth pursuing, set team expectations that match your organization's policy, build staff skills, design quality assurance and accountability for AI-assisted work, lead the change with your team, and measure impact honestly. A dedicated module covers the National Labor Relations Act (NLRA): employees' Section 7 rights to discuss and act together on working conditions, including AI and monitoring, and your duties in unionized workplaces.

It is written for frontline supervisors, middle managers and team leads in any sector, including those who manage unionized teams. It assumes basic familiarity with AI tools; no technical background is required.

Generic AI-for-leaders content often stops at strategy. This course is about the manager's real week: the staff member using a personal chatbot, the duplicate payment an AI extraction caused, the break-room conversation about a new monitoring tool, the director who wants a productivity number. Each scenario is grounded in US law and the NIST AI Risk Management Framework, and you leave with a team AI rules starter, a use-case intake worksheet, a QA checklist, a manager prompt sheet and a 90-day action plan.

What you’ll be able to do Monday morning

  1. List every AI tool your team uses, approved or not, without blaming anyone for past use.
  2. Run one proposed use case through the value-and-risk intake worksheet.
  3. Share written team expectations: approved tools, data rules, review and disclosure.
  4. Assign a review tier and a named reviewer to each AI-assisted output your team produces.
  5. Check any planned AI monitoring or productivity tool with HR or labor relations before it launches.
  6. Draft the first 30 days of your AI action plan and share it with your team.

Curriculum

6 modules · 24 lessons · about 2 contact hours

01What do managers need to know about AI, and which uses are worth pursuing?Free preview15 min
  1. What can AI reliably do for a team, and what can't it?
  2. How do you choose use cases worth pursuing?
  3. What are a manager's responsibilities for AI on the team?
  4. How should you respond to an AI target from above?
  • Sort activity: Which lane does this use case belong in?

Diagram · In practice checklist · 2-question knowledge check

02How do you set team expectations and build AI skills?15 min
  1. What should team AI expectations cover?
  2. How do you handle unapproved AI use without driving it underground?
  3. How do you build your team's AI skills?
  4. How do you keep expectations current as tools change?
  • Self-assessment: How ready are you to lead AI on your team?

Diagram · In practice checklist · 2-question knowledge check

03How do you assure quality and accountability for AI-assisted work?15 min
  1. How do you match review to risk?
  2. How do you keep human review from becoming a rubber stamp?
  3. Who is accountable, and how do you document it?
  4. What should happen when an AI-related incident occurs?
  • Spot the issue: Spot the weaknesses in an AI review procedure

Diagram · In practice checklist · 2-question knowledge check

04How do you lead AI change and respect employees' rights under the NLRA?17 min
  1. Why do people resist AI changes, and what actually helps?
  2. What does Section 7 of the NLRA protect?
  3. What changes in a unionized workplace?
  4. How do you communicate AI changes well?
  • Ethics dilemma: The drivers' group chat
  • Decision tree: Who do I involve before this AI change?

Diagram · In practice checklist · 2-question knowledge check

05How do you measure AI's impact and spot red flags?15 min
  1. How do you measure AI's impact fairly?
  2. Which legal and ethical red flags should managers escalate?
  3. How do you escalate well?
  4. How do you balance enthusiasm and caution on your team?
  • Spot the issue: Spot the red flags in an AI pilot report

Diagram · In practice checklist · 2-question knowledge check

06What does a 90-day manager action plan look like?16 min
  1. Days 1 to 30: How do you understand and set ground rules?
  2. Days 31 to 60: How do you pilot and train?
  3. Days 61 to 90: How do you measure, decide and scale?
  4. How do you sustain responsible AI use after 90 days?
  • Branching scenario: Gwendolyn's 90 days

Diagram · In practice checklist · 2-question knowledge check

Final assessment: 23 questions, 70% to pass, then your certificate

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Gwendolyn's 90 days

A branching scenario from this course. Your choices are not saved.

Free sample activity

Gwendolyn's 90 days

You are Gwendolyn Assefa, office director at a home care agency. You have 90 days to lead your office team's adoption of an approved AI assistant. Make her key decisions.

Inside the course

Practice activities

  • Sort activity1
  • Self-assessment1
  • Spot the issue2
  • Ethics dilemma1
  • Decision tree1
  • Branching scenario1

Job aids you keep

  • Team AI Expectations (Policy Starter for Managers)Policy starter
  • AI-Use Checklist: Use-Case Intake WorksheetWorksheet
  • Verification Checklist: Quality Assurance for AI-Assisted Team WorkChecklist
  • Prompt Sheet for ManagersPocket card
  • 90-Day Manager AI Action PlanWorksheet

Credit and approval status

Certificate of completion

This course awards a certificate of completion for 2 contact hours of instruction. It has not been approved or accredited by IACET, the Society for Human Resource Management (SHRM), the Project Management Institute (PMI), any licensing board, professional association or state agency. It is general management education on AI; it does not replace your organization's AI policy, legal advice or labor-relations guidance. Check with your employer or professional body whether this course can count toward your training or continuing education requirements.

Pathways we may pursue include IACET accreditation of our course development process and SHRM recertification provider status. Holders of PMI certifications may be able to self-report learning activities under PMI's own current rules. No approval exists today; we will show any approval on this page only after it is granted.

Our full approvals list

Questions about this course

Does this course count for SHRM, PMI or other continuing education?

It earns a certificate of completion for 2 contact hours of instruction. It is not approved by SHRM, PMI, IACET or any licensing board today. Some professional bodies let members self-report learning under their own rules, and many employers accept management training like this. Check their current requirements before you enroll. We will show any approval on this page only after it is granted.

Who is this course for?

Frontline supervisors, middle managers and team leads who are responsible for how their teams use AI, in any sector. It's especially useful if your organization has just approved AI tools, if staff are already using AI informally, or if you manage a unionized team.

Is this legal training on the NLRA?

No. It explains, in plain terms, how the NLRA's Section 7 and duty-to-bargain rules can apply to AI and monitoring so you recognize when to involve HR or labor relations. It is not legal advice. Your organization's labor-relations and legal teams decide how the law applies to specific situations.

How is it different from your AI governance course?

This course is for people who manage teams day to day. The AI governance course is for those who design organization-wide AI programs, risk registers and policies. Managers often take this course and refer governance questions to their organization's AI governance lead.

How long does it take, and how is it assessed?

About two hours, including scenarios, a dilemma, a decision tree and a 23-question final assessment. You need 70% to pass and can retake it. Passing unlocks a certificate of completion with the course title, date and 2 contact hours. An optional task helps you draft a 90-day plan for your own team.

Does it cover my state's rules on employee monitoring or AI in hiring?

It gives examples, such as New York's monitoring-notice law and Illinois's AI employment law, and flags that public-sector labor rules differ. It doesn't survey every state. Check with HR or counsel for the rules that apply where your team works.

This course is general education and training awareness on AI literacy and AI adoption for managers from CE Courses Hub. It is not legal, technical or professional advice and does not replace your employer's AI policies, your licensing board's rules, or advice from a qualified professional. Completing it earns a certificate of completion for the stated contact hours; it is not approved or accredited by any licensing board, state agency or accreditor unless an approval is shown on the course page. Check with your board, employer or state agency whether this course meets your specific requirement.