An October 2026 economic platform, written through Arizona's history of offshoring and the Great Recession, organized around five pillars: raise wages and benefits, create blue-collar jobs, restore worker trust in government in the age of AI, expand entrepreneurship outside superstar cities, and help workers find jobs faster. AI is one pillar of a broader labor agenda rather than the organizing subject, but the AI chapter opens with an unusually blunt premise for a Democratic senator — 'we must slow AI development and regulate it' — before framing the real question as whether workers or elites are in the driver's seat. Its AI agenda is labor-side: a New Deal-style public service jobs program for displaced workers funded by some combination of a data center tax, a token tax, or an excise tax on large AI company revenue; a corporate robot tax; sectoral bargaining over workplace technology; conditions — up to hard caps and bans on complete automation — on industries deploying highly displacing technology; mandatory human review of AI hiring, firing, and discipline; and a modernized unemployment insurance system partly funded by AI taxes. Its data center provisions are among the most aggressive on the map: a 10% excise tax on data center gross receipts, repeal of bonus depreciation and SALT deductions for data centers, full cost recovery for grid upgrades, a requirement to bring new generation, and a ban on key Chinese chips and components.
Key Provisions
New Deal-style public service jobs program for AI-displaced workers in care, coaching, addiction counseling, and community work, funded by a data center tax, a token tax, and/or an excise tax on large AI company revenue
10% excise tax on data center gross receipts, repeal of data center bonus depreciation and SALT deductions, full cost recovery for generation, transmission, and distribution upgrades, and a requirement to bring additional energy to the grid that survives project abandonment
Corporate 'robot' tax that preserves payroll contributions for automated-away jobs, with revenue supporting displaced workers
Mandatory bargaining between employers and elected worker representatives — ideally by sector — over workplace technology and data privacy
Safety and workforce conditions on industries deploying highly displacing technology, including prohibitions on complete automation, human-operator requirements, no-net-job-and-wage-loss rules, and hard caps on deployment
Ban on relying exclusively on AI or algorithmic management for hiring, discharge, or discipline, with meaningful human review required; minimum limits on worker data collection and a ban on surveillance wage setting
Unemployment insurance floor of six months at 75% wage replacement, extended to part-time, self-employed, and new entrants, partly funded by taxing data centers, AI tokens, or AI company revenue
Right to a U.S.-based human customer-service agent on request, AI disclosure on job postings, a 120-day WARN Act notice period, and a right for individuals to set a price companies must pay to use their personal data
Regulatory Philosophy
Bargain over the machines rather than regulate the models. Gallego treats AI as the next round of the offshoring and automation that hollowed out Arizona's blue-collar economy, and answers it with labor-law tools: sectoral bargaining over technology adoption, human-review mandates, deployment conditions written into industry permission, and taxes that make automation pay what labor pays. The rhetorical commitment to 'slow AI development' is real, but the instruments act on deployment and on the infrastructure buildout rather than on model development — there is no testing, licensing, or frontier-safety provision anywhere in the plan. Data centers are treated as a revenue base and a ratepayer threat, not a land-use question.
Data center gross receipts; employers that automate; a menu of token and AI-revenue taxes
Why it lands there
The only firm base in the plan is data center gross receipts, and with depreciation and SALT repeal stacked on top, the hyperscalers carry the heaviest and most specific burden on this map short of a moratorium. The labor instruments — the robot tax, technology bargaining, human-review mandates, and deployment caps — assess the employer doing the automating, which is the app layer and enterprise adopters, not the labs. The frontier layer appears only through the floated token tax and revenue excise, which are options rather than commitments. The ban on Chinese chips and components in data centers shifts demand toward domestic suppliers, so the chip layer is touched as a beneficiary rather than a payer.
Gallego vs. Casar: the same jobs program, two theories of the tax
Both route AI revenue into federally funded public service jobs doing care and community work that automation cannot easily reach. Casar has already written the tax: an excise on foundation-model developers, measured in tokens or revenue and indexed to unemployment. Gallego leaves the jobs program's funding as a menu, and his one fully specified AI tax lands somewhere else entirely — a 10% excise on data center gross receipts, which assesses the hyperscalers that own the buildings rather than the labs that train the models. Gallego also reaches the adoption decision itself, through sectoral technology bargaining and deployment caps, which Casar's purely fiscal bill never touches.
+Puts workers inside the adoption decision through sectoral technology bargaining, rather than compensating them after the fact — a lever almost no other proposal on the map reaches
+The deployment-conditions provision is the only one in the landscape that contemplates hard caps on automation in specific industries, giving policymakers a tool between laissez-faire and a moratorium
+Names a precise tax base where others leave it blank — a 10% excise on data center gross receipts — and pairs it with the full set of cost-recovery rules that keep grid costs off ratepayers
+Human review of AI-driven hiring, discharge, and discipline, plus limits on worker data and surveillance wage setting, addresses the AI harms workers are already experiencing rather than speculative ones
+Treats the AI bet as a financial risk as well as a displacement risk — asking what happens to workers if the productivity gains never arrive — which almost no proposal on the map considers
Weaknesses
From the perspective of political opposition
−Despite opening with 'we must slow AI development and regulate it,' the plan contains no instrument that does either — no testing, licensing, safety standards, or liability provisions for the models themselves
−The funding mechanism for its flagship jobs program is a menu ('data center tax, token tax, and/or excise tax'), and the same menu is spent a second time on unemployment insurance, so the revenue is committed twice without being raised once
−A 10% gross-receipts excise on data centers stacked with repeal of depreciation and SALT deductions is designed to deter the buildout, which sits awkwardly with the plan's own enthusiasm for Arizona's chip and AI manufacturing boom
−Deployment conditions as strong as hard caps and bans on complete automation are proposed without saying who decides which industries qualify, through what process, or on what evidence
−It is a campaign-style platform, not legislation — most AI items begin with 'explore,' 'consider,' or 'promote,' and none is drafted
−Silent on child safety, copyright, deepfakes, preemption, and catastrophic risk