Learning Objectives

By the end of this 180-minute seminar, participants will be able to articulate the economic, demographic, and social dynamics of AI-driven workforce transformation in the United States, drawing on Bureau of Labor Statistics projections, OECD Jobs Strategy evidence, and Department of Labor Employment and Training Administration data. Learners will map federal instruments including the Workforce Innovation and Opportunity Act, Trade Adjustment Assistance for Workers, Registered Apprenticeship, Pell Grants, and Perkins V to AI reskilling pathways. Participants will identify equity risks addressed by the Blueprint for an AI Bill of Rights, EEOC guidance on AI hiring tools, and the OSTP principle on algorithmic discrimination protections, and will design workforce monitoring aligned with the NIST AI RMF MEASURE function. Learners will critique national strategies including Singapore's SkillsFuture, Germany's dual education system, the UK Lifelong Learning Entitlement, and Canada's Future Skills Centre. Finally, learners will construct a 24-month workforce transformation plan for their own agency or jurisdiction that aligns with EO 14110 directives, OMB M-24-10 accountability obligations, and collective bargaining obligations under the Federal Service Labor-Management Relations Statute with AFGE, NTEU, and relevant state unions.

Key Topics Covered

This seminar covers labor market impacts of generative and task-specific AI drawing on BLS, Brookings, and McKinsey Global Institute analyses; the distribution of displacement and augmentation by occupation and demographic group; federal and state workforce instruments including WIOA Title I and Title II, TAA, Registered Apprenticeship, YouthBuild, Job Corps, Senior Community Service Employment Program, and WIOA performance metrics; AI in public workforce delivery including the AJC one-stop system, Unemployment Insurance modernization, and veterans' Transition Assistance Programs; equity protections aligned with Blueprint for an AI Bill of Rights and EEOC guidance; education system alignment covering Perkins V CTE, Pell Grants, short-term Pell expansions, Department of Education competency frameworks, and NSF AI institutes; retraining program design including stackable credentials, competency-based assessment, Registered Apprenticeship incorporation of AI, employer-led training, and community college partnerships; case studies covering Michigan MIDAS, IRS ID.me accessibility, VA claims modernization, Allegheny County child welfare, and international programs; and policy responses covering AI impact assessments, OMB M-24-10 requirements for rights-impacting AI affecting federal employees, union consultation obligations, and social safety net modernization.

Why This Matters for Government

The AI transition will touch every federal, state, and local workforce. Bureau of Labor Statistics analysis and OECD 2023 Employment Outlook estimate that roughly 27 percent of jobs in advanced economies are at high exposure to generative AI, with additional tasks subject to augmentation. The distribution is uneven. Clerical, customer service, and paralegal roles see disproportionate task exposure. Many of these roles are disproportionately held by women and workers of color. The Blueprint for an AI Bill of Rights principle on algorithmic discrimination protections, EEOC technical assistance on AI workplace tools, and Department of Labor Office of Federal Contract Compliance Programs guidance all point to systemic equity obligations that scale with deployment. Executive Order 14110 directs federal agencies to address workforce impact and to support worker voice, training, and safety nets. OMB Memorandum M-24-10 requires rights-impacting AI to include worker consultation and human oversight where workforce decisions are affected. The Federal Service Labor-Management Relations Statute requires that covered changes be negotiated with certified bargaining units such as AFGE and NTEU.

The federal workforce itself is changing. Agencies including GSA, DHS, VA, IRS, SSA, and DOD are deploying generative AI assistants for drafting, customer contact, and case triage. The GSA AI Centers of Excellence document ongoing deployments. The VA is piloting AI-assisted claim processing for more than 1.3 million annual disability claims. The IRS piloted generative AI for taxpayer correspondence. Each deployment reshapes jobs and requires training, change management, and bargaining unit consultation. The cost of getting this wrong is measured in failed implementations such as the Michigan MIDAS unemployment fraud system, the IRS ID.me accessibility reversal, and international cases such as the Dutch childcare benefits scandal where automation displaced judgment without adequate workforce or citizen protection.

Education system alignment is a decade-long project. K-12 computer science standards, AP computer science, and NSF funded AI institutes all contribute. The Department of Education's National Educational Technology Plan and the Perkins V Career and Technical Education framework anchor state plans. Pell Grant eligibility for short-term programs, competency-based assessment, and the Lumina Foundation Degrees When Ready work all interact. Community colleges are the workhorses of mid-career retraining, with the American Association of Community Colleges documenting AI-specific programs at hundreds of institutions. Registered Apprenticeship under the Department of Labor has expanded to AI roles with the Apprenticeship USA initiative.

Retraining and continuous learning programs must reach displaced and at-risk workers. WIOA Title I provides adult, dislocated worker, and youth funding through local workforce development boards. TAA supports trade-affected workers; advocates have pushed for an AI analog. Pell Grants now include short-term programs under limited pilots. State models include California's High Road Training Partnerships, New York's Office of Strategic Workforce Development, and Colorado's Opportunity Now initiative. Singapore's SkillsFuture, the UK Lifelong Learning Entitlement launching in 2025, Canada's Future Skills Centre, and Germany's dual system offer international benchmarks. Each reflects distinct political economy and cannot be copied without adaptation.

Labor market monitoring must be upgraded. BLS occupational employment and wage statistics, JOLTS, and the American Community Survey provide national baselines. State labor market information offices add local detail. The Department of Commerce National AI Research Resource Task Force has called for more granular measurement. The GAO AI Accountability Framework emphasizes performance monitoring as a governance obligation. Workforce boards and state labor departments need new dashboards that combine BLS data with real-time signals.

Equity is central. The Blueprint for an AI Bill of Rights protections against algorithmic discrimination apply to workforce AI. EEOC guidance on AI hiring tools, disability accommodations, and selection procedures imposes Title VII, ADA, and ADEA obligations. The Department of Labor OFCCP enforces affirmative action obligations for federal contractors. Disparate impact testing, reasonable accommodation protocols, and transparency about AI use in hiring and promotion are legal necessities. The IRS ID.me case showed how biometric enrollment without accessibility testing excluded veterans, older Americans, and citizens without smartphones. The COMPAS case and Houston HISD teacher evaluation litigation illustrate the due process and discrimination risks when AI is used to affect livelihoods.

Policy responses cluster in four areas: modernizing the safety net through UI reform, expanding and targeting training investments, requiring transparency and worker voice in AI deployment, and building federal capacity for workforce impact assessment. Each agency has a role. The Department of Labor leads training and UI. The Department of Commerce leads standards and measurement. The Department of Education leads postsecondary alignment. OMB leads federal procurement and governance through M-24-10 and EO 14110. CISA and NIST lead security and risk management frameworks. GAO provides accountability oversight. State labor departments, community college systems, and workforce boards execute.

Practical case studies include Allegheny County's workforce reskilling for child welfare workers deploying the Allegheny Family Screening Tool; the VA's AI assistant rollout with AFGE consultation; the IRS customer service generative AI pilot with NTEU consultation; and Michigan's post-MIDAS reforms including independent review, human oversight, and expanded adjudicator training. Each illustrates how governance, bargaining, and training together determine whether AI deployment transforms jobs constructively or destructively.

Overview

The seminar opens by framing the workforce transition as simultaneously an economic, equity, and governance challenge. Participants review BLS task-level exposure data, OECD occupational projections, and Brookings and McKinsey estimates. The discussion centers on distribution: which occupations, which demographics, which regions. The Bureau of Economic Analysis regional data and the Appalachian Regional Commission materials anchor the regional conversation. Participants connect this to the Blueprint for an AI Bill of Rights, EO 14110 directives on worker impact, and M-24-10 human oversight obligations.

Federal Instruments and Agency Roles

A structured review covers WIOA Title I and II, TAA for Workers, Registered Apprenticeship, Pell Grants and Perkins V, the Department of Labor Employment and Training Administration, the Department of Commerce National AI Research Resource, OMB M-24-10, CISA and NIST AI RMF, and GAO oversight. Participants map which instrument serves which worker population and where coordination gaps exist. The session draws on the GSA AI Centers of Excellence case library.

International Case Studies

Participants examine Singapore's SkillsFuture credits and lifelong learning architecture, Germany's dual education system under AI pressure, the UK Lifelong Learning Entitlement, Canada's Future Skills Centre, Australia's apprenticeship expansion, and South Korea's Digital New Deal. Each is analyzed for transferable principles rather than copyable blueprints, with explicit attention to institutional context and political feasibility.

Equity, Bargaining, and Worker Voice

The seminar addresses EEOC guidance on AI hiring tools, OFCCP affirmative action obligations, ADA accommodations, and Title VII disparate impact. Federal bargaining obligations under the Federal Service Labor-Management Relations Statute are examined in detail, with AFGE and NTEU examples. State examples include California AB 2930 proposals, Colorado AI employment protections, and Illinois Artificial Intelligence Video Interview Act. The Dutch childcare benefits scandal and Michigan MIDAS are analyzed as cautionary tales.

24-Month Workforce Strategy Design

Participants build a plan covering baseline assessment, impacted population identification, bargaining unit consultation, training design, vendor selection aligned with FedRAMP and M-24-10, communications, metrics, and governance. Plans include go or no-go gates, equity monitoring aligned with Blueprint principles, and escalation paths for incidents. Each plan is peer-reviewed.

Start Your CLUB Certification

This lecture is part of L5: AI Visionary, 160 hours of advanced government AI training aligned with NIST AI RMF, OMB M-24-10, EO 14110, GAO AI Accountability Framework, and the Blueprint for an AI Bill of Rights.

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