AI Implementation for People Managers

Name: AI Implementation for People Managers
Rating: 4.1 (53 reviews)

AI workflows: use-case discovery, pilot design, team norms, performance dashboards.

Created byEduardo Aponte, PhD

Last updated 1/2026

English

English [Auto],

What you'll learn

Will understand how to identify high-ROI AI opportunities by analyzing pain, volume, variance, and rework in team workflows.
Will prioritize use cases using ICE scoring, basic feasibility checks, and clear risk tiering for fast, safe execution.
Will apply manager-friendly prompting patterns to create reliable drafts for meetings, emails, and reporting with “show your work” checks.
Will design practical pilots with scope, owners, guardrails, baselines, and success criteria using one-page OKRs.
Will implement team norms for responsible use, including data hygiene, prompt logs, review sign-offs, and escalation paths.
Will measure and improve results with dashboards, A/B tests, pilots vs. control, and ongoing benefit tracking.

Course content

4 sections • 15 lectures • 1h 33m total length

What GenAI Can Do for Teams7:12
Explore how genai copilots and retrieval tools automate routine team work, draft messages, summarize documents, and extract action items while highlighting limits, data hygiene, and governance.
Finding High-ROI Use Cases7:08
Identify candidate workflows by examining pain, volume, variance, and rework, then rank them with ICE scoring and quick feasibility checks for a focused pilot.
Prompting Patterns for Managers5:12
Learn practical prompting patterns to generate reliable, reusable AI outputs for daily management, including prompts that show its work, audience and outcome planning, and structured decision workflows.
Exercise — Create a Starter Prompt Library for Your Team2:14
Pilot Design & Success Criteria4:57
Design a safe ai pilot by selecting one narrow workflow step and defining clear boundaries. Track impact with 3–5 metrics and assign owners, baselining before and outlining a four-week plan.

Smart Document Processing7:07
Learn to leverage smart document processing with OCR, ML, and AI to convert invoices, receipts, and statements into structured data, validate with deterministic checks, and automate posting and review.
Effective Communication with AI12:45
Learn essential leader communication skills, including active listening, clear and concise messaging, constructive feedback, non-verbal cues, and empathy to build trust, align goals, and motivate teams.
Performance Loops & Dashboards5:29
Design AI dashboards as a speedometer, tracking throughput, quality, cycle time, and reward to spot bottlenecks and guide action with thresholds. Use a four-signal loop: measure, review, adjust, measure again.

Communicating the Why (and the How)5:49
Communicate the why and how of introducing AI to address role-specific benefits, safety, and ethics. Outline quality controls, upskilling, and clear governance for responsible use.
Role-Play Scenario: Communicating the Why (and the How) of GenAI
Upskilling Pathways & Role Design6:12
Define upskilling pathways with skill maps and lightweight rituals to connect today’s work to tomorrow’s value. Build AI-enabled team roles through observable behaviors, microlearning, and weekly office hours.
Team Norms & Responsible Use5:48
Set clear norms for responsible AI use, outlining acceptable tools and data. Establish a structured, review-based workflow with templates and escalation to ensure accuracy and policy compliance.
Coaching & Performance Management5:40
Coach ai-assisted work as you guide a team member, with clear expectations and fast feedback to shape drafts into reliable results; set goals, include sources, and use a quality rubric.

Lightweight Governance for Managers5:37
Implement lightweight governance for ai with a simple intake, tiered approvals, and weekly monitoring to safely scale automation; define roles, triage outputs, and retirement actions to maintain trust and speed.
Privacy, Security & Shadow-AI Prevention6:02
Minimize privacy risks by shrinking prompt scope, redacting sensitive fields, using placeholders, and preferring approved sources; enforce short memory, strict access, and clear confidential data definitions to prevent shadow AI.
Proving Impact & Continuous Improvement6:16
Prove AI impact through controlled A/B pilots and control groups with clear success metrics, track benefit over time, and maintain continuous improvement across operations, quality, and business value.

Requirements

No previous experience is necessary.

Description

Welcome to “AI Implementation for People Managers.” If you lead a team and want AI to cut busywork, speed decisions, and improve quality—without risking brand, data, or trust—this course is for you. We stay practical and tool-agnostic: no coding, no hype, just playbooks you can use next week.

You’ll start by learning what GenAI can and cannot do for everyday teamwork, then map high-ROI opportunities using simple workflow diagnostics and ICE scoring so you pick smart, safe starters. From there, we put AI to work in your real flow—meetings, email, and documents—turning SOPs and wikis into answerable knowledge, adding lightweight automations with a human in the loop, and tracking results with a clear dashboard for throughput, quality, cycle time, and rework.

Because change is about people, you’ll get talk tracks by role, address common fears around quality, jobs, and ethics, and build a practical upskilling rhythm with micro-learning and office hours. You’ll also establish team norms—acceptable use, data hygiene, prompt logs, and review sign-offs—so outputs stay consistent and safe.

Finally, you’ll run lightweight governance from intake to retirement, set privacy and security defaults that prevent shadow AI, and prove impact with fair pilots, A/B tests, and benefit tracking. By the end, you’ll have a one-page pilot brief with OKRs, a starter prompt library, and a repeatable operating model to scale what works—safely, measurably, and fast.

AI Implementation for People Managers

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Course content

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Governance, Risk & Scaling Sustainably3 lectures • 18min

Requirements

Description

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