U.S. BPO jobs still offshored despite Trump promises: Expivia CEO
FLORIDA, UNITED STATES — Years after former President Donald Trump vowed to bring jobs back to America, domestic BPO operators say the promise remains unfulfilled.
While manufacturing saw gains, United States contact centers still grapple with offshoring pressures—even as AI and rising nearshore costs shift the playing field.
Policy promises fall short for U.S. BPOs
Despite Trump’s 2017 America First Tax Relief Plan, which aimed to incentivize onshoring by taxing offshore profits, domestic contact centers saw little tangible benefit.
Thomas Laird, Chief Executive Officer (CEO) of Pennsylvania-based Expivia, a 600-seat contact center, expressed disappointment, noting that while manufacturing jobs rebounded, BPOs were left waiting.
“You know, I would love to see some of (those jobs) come back onshore with the understanding that it would not just boost onshore, but also boost how quickly AI gets implemented. … It would be a win-win from that standpoint,” he said, arguing that reshoring could accelerate AI integration and boost local employment.
The U.S. loses an estimated 300,000 jobs annually to offshoring, per data from Radix. Laird believes federal support could have balanced the scales, but without it, domestic BPOs must rely on cultural preference—70 to 80% of U.S. customers prefer American agents, internal studies show.
Even as AI looms, Laird predicts demand for human-centric service, akin to U.S. banks branding as human-first, will endure in sensitive sectors like healthcare and emergency response.
Wage pressures and AI reshape competitive edge
Rising labor costs in nearshore hubs like Latin America are narrowing the price gap with U.S. centers, says Laird. While offshore locations remain cheaper, Expivia’s $15 to $17 per hour agent wages now compete with pricier nearshore markets.
The firm targets regions with low minimum wages and light taxation, leveraging rural labor pools for cost efficiency.
Laird foresees agents handling complex issues earning “the highest wages in the company” as automation handles routine tasks.
However, he warns that hasty AI adoption risks backfiring without proper infrastructure, citing unresolved data security concerns in large language models. By 2027, he expects stabilization—if firms invest now in knowledge bases and phased implementation.
“There’s still a lot of things that need to be worked out with security,” he said.
