Course Description

Generative artificial intelligence can help federal organizations improve analysis, communication, service delivery, and internal operations. It also introduces questions about accuracy, privacy, security, bias, workforce impact, records management, and accountability. Managers need enough practical understanding to identify worthwhile applications, recognize inappropriate uses, and guide responsible experimentation within agency policy.

This course gives leaders a plain-language understanding of how generative AI works, what it does well, and where it can produce incomplete, inaccurate, or misleading results. Participants examine management and mission use cases and apply a structured framework that considers expected value, feasibility, data sensitivity, risk, human review, and organizational readiness.

Participants work through federal workplace scenarios and assess one potential use case from their own organization. They leave with clear questions to ask, safeguards to establish, and a practical action plan for evaluating or introducing AI while retaining human judgment and accountability.

Learning Objectives

Successful completion of this course will increase your knowledge and ability to:

• Explain generative AI capabilities and limitations in practical management terms.
• Identify management and mission activities that may benefit from generative AI support.
• Evaluate potential use cases based on value, feasibility, data requirements, risk, and organizational readiness.
• Recognize concerns involving privacy, security, bias, accuracy, intellectual property, records management, and workforce impact.
• Define appropriate human review, decision authority, documentation, and accountability for AI-assisted work.
• Develop responsible next steps for evaluating a selected AI use case within agency policy.

Course Outline- Half Day Agenda

1. Overview

• Course Objectives
• Introduction
• Opening Activity

2. Module 1: Understanding Generative AI

• What generative AI is and how it produces responses
• Common capabilities and limitations
• Why confident output may still be incomplete or wrong
• Exercise: Distinguishing appropriate and inappropriate uses

3. Module 2: Identifying Valuable Use Cases

• Management, administrative, analytical, and service-delivery applications
• Matching the tool to the work and the desired outcome
• Value, feasibility, data, and readiness considerations
• Activity: Use Case Opportunity Screen

4. Module 3: Managing Risk and Responsible Use

• Privacy, security, sensitive information, and access controls
• Accuracy, bias, transparency, intellectual property, and records considerations
• Human review and accountability for decisions and work products
• Scenario Exercise: Leadership Decisions for Responsible AI Use

5. Module 4: Leading Adoption

• Setting expectations and defining acceptable use
• Preparing employees, processes, and performance measures
• Moving from controlled experimentation to operational use
• Action Plan: Responsible Next Steps for a Selected Use Case

6. Action Plan

Workshop Participants

TMG considers the optimal number of participants to be 14-20 for facilitation of this workshop. A maximum of 24 is allowed.

Training Materials

A comprehensive workbook accompanies this course that serves as a reference guide for course content.

TMG Training Sessions Delivered to You Virtually or On-Site.

The date you choose. The location you want. The results you need! TMG virtual or on-site training is the perfect solution for training ten employees or launching a company-wide training effort. It’s affordable, completely customizable and absolutely hassle-free. You can count on organizational results that are immediate and measurable.