AI Cannot Replace Human Judgment in Carrier Vetting Post-Montgomery

H. Robinson and other digital brokers are aggressively deploying AI across operations—from appointment scheduling to load tracking—but legal experts and industry analysts warn this technological investment must extend to carrier vetting to avoid repeating the negligence that led to the company's recent unanimous Supreme Court loss in *Montgomery*. The case established that brokers cannot be categorically shielded from negligent hiring claims when selecting unsafe carriers; this creates a structural liability exposure if companies optimize for speed and margin while leaving carrier safety decisions disconnected from their sophisticated data environments.

The core tension is that modern freight brokers collect enormous datasets on carrier behavior, payment patterns, fraud indicators, and operational history—yet may fail to apply the same analytical rigor to safety vetting. Justice Kavanaugh's concurrence emphasizes that brokers must exercise ordinary care and ask hard questions when risk indicators surface, suggesting that full automation with rigid pass/fail rules falls short of legal defensibility. The plaintiff's counsel in *Montgomery* made an explicit distinction: AI that identifies chameleon carriers and fraud patterns enhances safety, while AI that merely accelerates onboarding and capacity expansion without meaningful vetting compounds liability.

For supply chain professionals, this ruling signals a structural shift in broker accountability. Companies that leverage AI to improve margins, tracking, and productivity while leaving carrier selection as a manual or disconnected function face mounting litigation risk and regulatory scrutiny. The post-*Montgomery* environment demands that brokers align their data governance, technology investment, and human oversight across all operational layers—including the carrier selection process that directly impacts road safety and legal exposure.