Overview

Most agencies run two distinct performance systems: an employee performance system (appraisals, ratings, awards) and an equally important organizational performance system — the agency's mission, programs, and operations governed by the GPRA Modernization Act and the Evidence Act. Artificial intelligence is already transforming that organizational layer. Federal agencies reported more than 3,600 AI use cases in 2025, with tools that forecast program demand, speed citizen services, detect improper payments, and analyze public input at scale.

This 4-hour interactive course equips government leaders to apply AI to organizational and program performance — improving efficiency, productivity, decision-making, and mission results — within current federal AI policy and governance. Through real agency examples and a hands-on capstone, participants build an executive-ready roadmap to put AI to work against their agency's priority goals.

Syllabus

Module 1 — From Appraisals to Mission: the Organizational Performance System

The two performance systems: employee appraisal vs. organizational/program performance
GPRA Modernization Act, Evidence Act, and PMIAA: strategic plans, Agency Priority Goals, performance.gov, and quarterly data-driven reviews
Who owns organizational performance: COO, Performance Improvement Officer, Chief Data Officer, Evaluation Officer
Where AI fits: the federal AI landscape and the Chief AI Officer role

Module 2 — AI Use Cases Across the Organization

Mission and program analytics and forecasting (caseloads, backlogs, demand)
Operational productivity (generative-AI drafting and summarization, knowledge management, process automation)
Decision support and resource allocation
Customer experience and service delivery (contact centers, constituent services)
Program integrity (improper-payment and fraud detection — with due-process safeguards)
Evidence-building and program evaluation (Evidence Act learning agendas)
Public input at scale (analyzing regulatory and public comments)

Module 3 — Governing and Leading Enterprise AI

Federal AI governance: NIST AI RMF and the GAO AI Accountability Framework
Current policy: Executive Order 14179 and OMB M-25-21 — AI governance boards, use-case inventories, and risk management for high-impact AI
Portfolio governance and proportional human oversight at enterprise scale
Change leadership and stakeholder engagement for AI adoption