AI for Federal Employee Relations Course (Self-Paced)
IDTECH8009SP

Module 1: ER, Not LR: Setting the Frame

• Distinguish Employee Relations work from Labor Relations work using an ER vs. LR decision aid
• Review common ER work products, including proposal letters, decision letters, PIPs, leave letters, reasonable accommodation correspondence, and grievance responses
• Identify where AI can support ER workflows and where it should not be used
• Understand why bargaining, ULPs, CBA analysis, and arbitration preparation are outside the scope of this course
• Review how this course pairs with the companion AI for Federal Labor Relations Specialists course
• Complete an ER-or-LR sorting exercise using sample workplace scenarios

Module 2: Guardrails First: Privacy, PII, and Records

• Review Privacy Act and PII considerations related to ER case files
• Identify sensitive case details that should not be entered into public AI tools
• Understand agency AI-use policies, approved tools, and sanitized sandbox options
• Explore recordkeeping considerations for AI-generated drafts and ER case documentation
• Consider bias, fairness, and EEOC guidance related to AI in employment decisions
• Sanitize a sample ER fact pattern by removing names, SSNs, medical information, dates, and other identifying details

Module 3: AI-Assisted ER Letter Drafting

• Review the core elements of defensible ER correspondence, including notice, specificity, due process, and Douglas factors where applicable
• Build structured prompts using role, context, constraints, format, and a review checklist
• Explore AI-assisted drafting for a proposed removal letter under 5 CFR 752
• Explore AI-assisted drafting for a performance improvement plan under 5 CFR 432
• Identify common AI drafting issues, including vague specifications, missing due-process elements, and tone mismatch
• Draft a leave or AWOL letter from a provided fact pattern and self-check it against a defensible-letter rubric

Module 4: Case Research with AI

• Use AI to summarize MSPB decisions, EEOC decisions, and ER-relevant agency policy materials
• Apply a verification workflow that requires every cited authority to be checked against an accessible source
• Compare AI-generated research outputs to OPM Employee Relations reference materials and agency policy
• Recognize hallucination patterns common in legal and HR research
• Use AI to organize key issues from a Chapter 75 fact pattern
• Draft a one-page issue memo and verify two cited authorities against the original source materials

Module 5: Performance and Conduct Documentation

• Turn vague supervisor notes into specific, behavior-based documentation
• Use AI to support performance documentation while preserving accuracy and reviewability
• Structure PIP content around measurable standards, reasonable opportunity, and contemporaneous documentation
• Draft Douglas-factor-aware conduct narratives for disciplinary documentation
• Organize reasonable accommodation interactive-process notes from an ER perspective
• Convert a messy supervisor email into a structured performance memo and review it against a rubric

Module 6: Capstone and Personal Prompt Library

• Build a five-prompt ER starter library for recurring casework
• Create reusable prompts for ER letters, PIPs, case research, documentation cleanup, and reasonable accommodation notes
• Apply a final review checklist covering privacy, accuracy, due process, tone, and records
• Choose a recurring sanitized ER task and build an AI prompt to support that workflow
• Test and revise the prompt based on output quality and compliance considerations
• Create a practical 30-60-90 day adoption plan for responsible AI use in ER work