# AI for Federal HR Classification Course (Self-Paced)

Canonical URL: <https://www.graduateschool.edu/courses/ai-for-federal-hr-classification-course-self-paced>

## Overview

This one-day course introduces federal employees to the practical use of artificial intelligence in federal position classification. You will learn what AI is, how it works at a basic level, and how AI tools can support classification work by helping analyze position descriptions, identify duties and KSAs, suggest occupational series and grade levels, and improve consistency in classification decisions. The course includes demonstrations and hands-on activities that show how AI can be used to compare traditional and AI-assisted workflows, draft and refine position descriptions, and support classification research using official standards and guidance.

Students should expect an applied, practice-oriented class focused on responsible use of AI in a federal HR setting. The course covers legal, ethical, privacy, and policy considerations, including human oversight, bias mitigation, transparency, and compliance with OPM standards and broader federal AI guidance. Throughout the course, you will review examples, participate in exercises and scenario-based discussions, evaluate AI-generated outputs, and develop an action plan for integrating AI tools into classification workflows in a way that is accurate, transparent, and aligned with federal requirements.

No prior AI or technical background required.

## What you'll learn

- Define artificial intelligence and its key concepts relevant to federal HR and position classification.
- Explain how AI tools can be used across sectors for position classification and job analysis.
- Identify legal, ethical, and policy considerations in applying AI to HR processes.
- Demonstrate how to use AI-assisted tools to develop and analyze position descriptions and suggest occupational series/grades.
- Apply AI-generated insights to improve accuracy and consistency in classification decisions.
- Evaluate AI outputs to ensure compliance with OPM standards.
- Develop an action plan for integrating AI solutions into classification workflows.
- Analyze real-world scenarios to develop corrective actions and preventive measures that improve ongoing compliance.

## Curriculum

#### Module 1: Introduction to AI in Federal HR

- Identify common examples and everyday uses of AI.
- Define what Artificial Intelligence (AI) is.
- Explain, at a basic level, how AI works.
- Apply this knowledge in the introductory exercise “Search vs AI.”

#### Module 2: AI Applications in Position Classification

- Explore how AI tools assist in reviewing and classifying federal position descriptions.
- Traditional vs. AI-assisted classification workflows.
- How AI reads and interprets duties, factors, and KSAs.
- Demonstration of an AI model suggesting occupational series and grade levels.
- Ensuring compliance with OPM classification standards.

#### Module 3: Ethics, Oversight, and Legal Consideration for AI

- Recognize ethical and legal responsibilities when using AI in federal HR processes.
- Recognize data-privacy and confidentiality requirements when using AI.
- OMB and OPM guidance on federal AI use.
- Recognizing and mitigating bias in AI systems.
- The role of human oversight in AI-supported decisions.

#### Module 4: AI in Classification

- Learn effective ways to phrase your chat when requesting a draft position description.
- Identify and address any inconsistencies in the generated results.
- Enhance your request through thoughtful refinement.
- Evaluate and compare the factor levels within the position description.

#### Module 5: Integrating AI Solutions Into a Classification Program

- Assess current classification processes to identify areas where AI can improve accuracy, consistency, and efficiency.
- Outline how AI-assisted tools will be selected, tested, and implemented, ensuring compliance with Office of Personnel Management (OPM) standards and federal HR policies.
- Incorporate change management strategies, including training staff, addressing concerns, and gradually introducing new technologies to minimize disruption.
- Emphasize stakeholder engagement by detailing methods to communicate with and involve HR professionals, managers, and employees throughout the process to ensure buy-in and successful adoption.
- Use the action plan as a roadmap for transitioning to AI-enhanced classification workflows in a transparent, collaborative, and federally compliant manner.

## Instructors

### Steve Pesklo — Instructor

Steve is an energetic trainer who focuses on applying technical concepts to everyday work practices. He is the founder and president of SoftLake Solutions, a company that specializes in providing data and AI applications to identify fraud for Internal Audit, Criminal Investigations, Forensic Accounting, Privacy, and Compliance.

Steve brings a large amount of experience across multiple industries and government agencies. He is an expert in implementing large data analysis projects across the world, including Inland Revenue in the UK and Argentina, New Zealand, Africa and across Europe. Previously, he was the manager of Data Architecture and Data Services for a large mortgage company. He is a frequent speaker on data analytics and project management topics and speaks fluent German. He has been teaching at the Graduate School for over 10 years.

Steve has an M.B.A. from the University of St. Thomas and a B.S. in Computer Science from California Lutheran University and the Universität Salzburg in Austria. He is certified as a Certified Fraud Examiner (CFE), Project Management Professional (PMP), and a Certified ScrumMaster (CSM).

## Pricing

**Tuition:** $899