Recommendation 20260916-005: Strengthening Responsiveness to AI Labor Impacts in Austin — original pdf

Recommendation

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RECOMMENDATION TO COUNCIL Economic Prosperity Commission Recommendation Number: 20260916-005: Strengthening Responsiveness to AI Labor Impacts in Austin WHEREAS, Austin has a high concentration of knowledge workers, early-career professionals, and technology companies, placing the city at high exposure risk for labor disruptions due to artificial intelligence; and WHEREAS, the Austin metropolitan area entered 2026 with ~1.41M nonfarm jobs and 3.4% unemployment, and office and administrative support represent 12.4% of employment, with a computer and mathematical workforce at nearly twice the national concentration; and WHEREAS, recession-like labor disruptions due to artificial intelligence adoption in the workplace could pose a risk to future city budgets and revenue, sales tax, property tax, and fees, while simultaneously driving up demand for social services, housing assistance, and public safety response; and WHEREAS, the City Council’s resolution of April 24, 2025 (agenda item 55) directed attention to AI oversight, workforce considerations, and digital equity, and the Commission’s analytical report, Impact of Artificial Intelligence on Austin Residents (July 2026), attached as backup, provides the supporting baseline, assessment, and recommendations; and WHEREAS, previous City Council resolutions have addressed AI oversight and digital equity in the workplace for the City of Austin as an employer, and this recommendation is intended to serve as a starting point for policies to help individuals navigate AI-driven labor disruptions and to help the City itself withstand these disruption risks; and WHEREAS, published exposure research and 2025-26 payroll evidence show AI is already changing tasks and hiring, first in clerical, customer support, business and financial, and early-career technical occupations, including a ~20% national employment decline for software developers aged 22 to 25 since late 2022, while the scale of broad job loss and the ease of transition remain debated and the worst effects have yet to be seen; and WHEREAS, those who are experiencing the earliest disruptions have limited economic security: office and administrative support workers represent the region’s highest AI exposure with the lowest ability to withstand reduced hours or hiring, and median rent absorbs ~41% of that group’s annual mean wage, posing economic-security risk to lower-buffer households; and . WHEREAS, national economic modeling corroborates these local risks and opportunities: Anthropic’s Economics team, in a scenario framework reviewed by leading labor economists, models a 2030 U.S. economy in which workers displaced from AI-exposed knowledge occupations must navigate transitions into occupations such as electricians and nurses that remain largely insulated from automation WHEREAS, this trajectory is supported by other leaders in this space, such as Anthropic CEO Dario Amodei has estimated that AI could eliminate up to half of entry-level positions in technology, finance, law, and consulting within one to five years, potentially raising national unemployment into the 10 to 20 percent range absent intervention, while Microsoft co-founder Bill Gates has separately identified preparing for AI’s labor market impact as among the world’s foremost priorities, that governments are behind, and has cautioned that waiting until unemployment rises sharply, communities are hurting, and public trust has eroded will be too late; and WHEREAS, data center and electrical infrastructure buildout is generating demand for electricians, mechanical and cooling, controls, and network trades, the construction supersector grew 5.0% over the year to April 2026, and these trades offer durable non-degree pathways; and WHEREAS, evaluated workforce programs in other U.S. jurisdictions, including randomized evidence from San Antonio and New York, indicate that transitions succeed when training is tied to verified employer demand, participants are supported through to completion, results are measured by wage replacement rather than placement counts, and reporting requirements are set at the outset. NOW, THEREFORE, BE IT RESOLVED that the Economic Prosperity Commission recommends that the Austin City Council direct the City Manager to: 1. Publish a quarterly Austin AI labor market dashboard built on a skills-exposure methodology rather than hiring and unemployment claims data alone, including an early-career module tracking outcomes for workers under 30 in the most exposed occupations; 2. Explore and establish transition pathways and support for impacted workers with Workforce Solutions Capital Area, Austin Community College, public libraries, and major employers, reported on wage replacement rather than placement counts; 3. Expand registered apprenticeship and pre-apprenticeship capacity in the trades tied to data and electrical infrastructure buildout, reserving slots for workers transitioning from exposed occupations; 4. Embed applied AI-tool fluency within existing workforce credentials, with open access for residents whose employers do not provide tools; and 5. Identify funding sources for the transition pathway and apprenticeship expansion described in items 2 and 3 above including state and federal workforce development grants and Workforce Solutions Capital Area pass-through funds rather than relying on General Fund . dollars, given the risk that AI-driven labor disruption may simultaneously constrain city revenue. BE IT FURTHER RESOLVED that the Commission recommends these actions be designed and evaluated according to the conditions identified in its report: training tied to verified employer demand, support sufficient to reach completion, wage replacement as the reported outcome, dedicated intermediary capacity, and outcome reporting established at the outset. BE IT FURTHER RESOLVED that the Commission transmits its analytical report, Impact of Artificial Intelligence on Austin Residents: Labor Market Baseline, AI Impact Assessment, and Policy Recommendations (July 2026), as backup supporting this recommendation. Date of Approval: September 16, 2026 Motioned By: Commissioner Joshi Seconded By: Chair Gonzales Vote: 6-0 For: Chair Gonzales, Vice Chair Randall, Commissioner Joshi, Commissioner Pleuthner, Commissioner Roberts, Commissioner Valdez-Sanchez Against: None. Abstain: None. Off the dais: Commissioner Zapata Absent: Commissioner Shakeel Attest: Chelsea Pfeifer, Staff Liaison