California is doing something no other state has tried: asking residents, directly and at scale, how artificial intelligence is changing their work, then promising to write the answers into policy. The move marks a shift in posture. AI’s effect on jobs is no longer being treated as a question for the next decade. It is being managed as a present-day economic problem in the state that builds the technology and absorbs its consequences first.
A State Soliciting Input on Its Own Disruption
The mechanism is Engaged California, the state’s digital democracy program, which Governor Gavin Newsom opened to all residents in May for its first statewide project. Through engaged.ca.gov/ai, Californians can create a profile and answer questions about how AI is showing up in their jobs and what they think the state should do about it. The stated purpose is to feed that feedback to policy leaders rather than let it sit in a comment box.
The outreach is one piece of a larger framework. On May 21, Newsom signed Executive Order N-6-26, which his office described as the first of its kind, directing state agencies to study AI’s workforce impact and recommend responses on defined timelines. The order builds on a March 2026 directive that addressed civil rights and privacy in the state’s AI procurement, and it pulls labor groups, economists, universities, and industry into the same review.
What the Order Actually Requires
The executive order is directive in nature, assigning agencies concrete deadlines. The Labor and Workforce Development Agency has 180 days to review the state’s WARN Act, the law requiring advance notice of mass layoffs, and to recommend updates that would flag job losses earlier. The Employment Development Department has 90 days to launch a public dashboard tracking AI’s employment effects across sectors, drawing on unemployment insurance data and, where useful, figures published by AI labs.
By October 15, 2026, the Government Operations Agency must develop recommendations on incentive structures, including the possibility of directing a share of AI company revenue toward deployments that serve the public. The same date applies to a review of how collective bargaining is handling new technology, with the state explicitly looking to learn from unionized workplaces. The order also calls for modernized job-training programs and expanded support for the long-term unemployed.
The Labor Numbers Behind the Anxiety
The urgency is grounded in measurable strain. The Public Policy Institute of California reports the state’s unemployment rate at 5.3 percent in April, against a national rate near 4.3 percent, and California has sat above 5 percent for more than 19 consecutive months. There are 1.9 unemployed workers for every job opening in California, compared with 1.1 nationally, and roughly 30 percent of unemployed residents have been searching for at least half a year.
The pain concentrates in the sectors that define the state’s brand. PPIC estimates information-sector jobs, spanning both technology and Hollywood, fell about 17 percent between mid-2022 and February 2026. The San Francisco Bay Area is the only region of the state with net job loss since 2022, weighed down by tech and professional services. Counting discouraged and underemployed workers, more than 10 percent of Californians were underutilized in early 2026, well above the headline figure.
A note of caution belongs here. PPIC has found no strong evidence that AI is the cause of the current slowdown, which began before generative tools went mainstream and tracks more closely with inflation, business uncertainty, and shifting demand. The state is building infrastructure for a disruption whose timing and scale remain contested, which is part of why it is gathering data rather than declaring conclusions.
The Budget Connection
The workforce effort runs parallel to a fiscal one. Newsom’s revised 2026–27 budget leans on tech-driven tax revenue while warning that the windfall is fragile, citing the risk of an AI-related stock correction as a reason to bank reserves rather than spend them. The state is, in effect, treating AI as both the source of its current strength and its most likely future shock, hedging on the revenue side while studying the labor side.
That dual stance captures California’s particular position. It hosts the firms shipping the models and the workers most exposed to them, which leaves it managing the upside and the fallout at once. The policies taking shape here, from a modernized layoff-notice law to a public AI jobs dashboard, will be read closely by other states and federal staff who expect to face the same pressures later. Whether California’s experiment becomes a template or a cautionary tale, it has chosen to confront the question in public, with residents’ own accounts as the starting material.
