When writer Dillon Thompson’s nearly $2,000 ebike vanished after FedEx confirmed its delivery — signed for by a mysterious “M.M.” who wasn’t Thompson, his fiancée, or anyone in their building — what followed wasn’t just a frustrating lost-package story. It became a months-long case study in one of the most pressing AI customer service challenges facing consumers right now: the replacement of human support with chatbots that can’t actually solve problems.
Summary
Key takeaways
- FedEx confirmed delivery of Thompson’s ebike, but the package never arrived; nearly three months later, he recovered only the shipping cost, roughly one-tenth of the bike’s price.
- 31% of customer service leaders have already reduced or plan to reduce headcount because of AI adoption, according to an April survey.
- A May report found 59% of consumers frustrated with AI customer service agents and 85% preferring human contact.
- Experts warn that companies betting heavily on immature AI chatbots risk damaging their reputations and locking themselves into costly, underperforming systems.
A Delivered Package That Never Arrived
The confirmation text came on a Wednesday evening. FedEx said the bike had been delivered and signed for. Thompson was standing in his kitchen, air-frying chicken, with no bike in sight. When he checked outside his apartment, nothing was there. When he checked the order, the signature belonged to “M.M.” — initials that matched no one at the address.
Whether the bike was stolen, misdelivered, or lost somewhere in FedEx’s network was almost beside the point. What mattered was finding someone — anyone — who could help fix it.
That search turned into something far more exhausting. Over the following months, Thompson worked through chatbot queues at FedEx, the bicycle company, his bank, his credit card provider, and even the Atlanta Police Department. The police interaction was particularly striking: when he called to file a missing property report, a chatbot answered, took his information, and told him to wait for an officer to call back. The first callback never came. The second came during a work meeting, left no voicemail, and when Thompson tried to return it, he landed back in the same chatbot queue.
He eventually filed two police reports — one by phone, one through the department’s website — with minimal result. FedEx did open a formal claim, but resolved it with an automated email that essentially confirmed the bike was missing and told him to contact the shipper. The shipper could only recover the shipping cost, roughly one-tenth of what Thompson paid. His bank and credit card company ran him through their own chatbot-heavy processes, ending with a single human agent who told him the loss fell on FedEx’s watch. After nearly three months, Thompson had recovered only a fraction of his investment.
The Industry Shift Powering the Frustration
Thompson’s experience isn’t an anomaly — it reflects a deliberate structural shift happening inside customer service departments across major companies.
An April survey of customer service leaders found that 31 percent have already reduced or are planning to reduce headcount specifically because of AI adoption. Many are redirecting human agents into different roles or adding responsibilities to existing staff rather than outright laying people off. But the direction of travel is clear.
Some executives have been direct about their intentions. A recent statement to Bloomberg indicated that AI will likely replace a “large percentage” of customer service work at major companies, identifying it as one of the business sectors most exposed to the technology’s disruption. That kind of thinking, from the top of major organizations, is accelerating deployment even where the tools aren’t ready.
When Friction Becomes a Feature, Not a Bug
There’s a darker dimension to some of these deployments. Industry practitioners use the term sludge to describe friction deliberately engineered into customer service flows — processes designed not to help but to discourage. AI hasn’t invented this tactic, but it has amplified it significantly.
Ryan Hamilton, a marketing professor and consumer psychology researcher at Emory University, puts it plainly: “Sludge existed before AI. But AI, like with everything else, has just sort of ramped up the dystopian nature of it.” Whether Thompson’s ordeal was the product of intentional sludge, organic system failure, or some combination of both, the effect on the consumer is functionally the same.
What Consumers Actually Think About AI Support
The numbers from consumer research are unambiguous. A May report covering consumers from the US, UK, and Canada found that 59 percent are frustrated with AI customer service agents. More strikingly, 85 percent said they would prefer to speak with a real person. These aren’t marginal dissatisfiers — they represent the dominant consumer experience with a technology being deployed at massive scale.
The gap between what companies are building and what customers actually want is significant, and growing. Companies are accelerating AI rollout while the majority of users are actively expressing a preference for the human interactions being removed.
Expert Warnings on AI Overreliance
Hamilton believes many of the companies deploying these systems are operating on optimism rather than evidence — assuming an all-in approach to AI chatbots will eventually pay dividends. The problem is that reputational damage accumulates in the meantime.
“They kind of assume that AI will catch up, or it won’t be that bad,” Hamilton said. “And it can, in some circumstances, be quite bad.” He also raises a competitive concern: as AI call centers become standardized across industries, companies lose the ability to differentiate on service quality. “Everyone is going to have the same AI call center, no matter what industry you’re in,” he warned.
Ravi Dhar, a professor at Yale and director of the school’s Center for Customer Insights, points to another force keeping companies committed to underperforming systems: a sunk-cost dynamic. Global AI spending is expected to ramp up sharply this year, and that level of investment creates pressure to justify the spend — even when outcomes aren’t meeting expectations.
“If you’re a CEO,” Dhar noted, “you’re getting questions from all of the investors, from Wall Street, like, ‘Hey, what is your AI strategy, and is it showing any return on investment?'” That investor pressure can become a reason to stay the course rather than pull back, even when consumers are signaling clear dissatisfaction.
When FedEx was asked to comment on Thompson’s case, the company issued a statement acknowledging that “complex situations require human care and deeper support,” and said it uses technology to “amplify” its team members’ capabilities. The company added it is “continuously refining” its processes. Meanwhile, Thompson’s bike is still missing and the gap in his account remains unfilled — a concrete reminder that well-crafted statements and functional customer service are not the same thing.
The real question isn’t whether AI will eventually get better at handling complex service failures. It probably will. The question is how much consumer trust companies are willing to burn through in the interim — and whether, by the time the technology matures, their reputations will have enough left to recover.
FAQ
What happened to the author’s ebike after FedEx confirmed delivery?
Despite FedEx sending a delivery confirmation and recording a signature, Dillon Thompson never received his ebike. The package was signed for by someone with the initials “M.M.,” which matched no one at the address. The bike was never recovered, and FedEx confirmed it was missing but directed Thompson to the shipper for reimbursement.
How did AI chatbots affect the author’s attempts to recover the lost package?
AI chatbots dominated every customer service channel Thompson encountered — FedEx, the bicycle company, his bank, his credit card issuer, and even the Atlanta Police Department. This created long delays, dead ends, and made it extremely difficult to reach a human representative capable of resolving the issue. Nearly three months later, he had recovered only the shipping cost, roughly one-tenth of the bike’s price.
What do surveys say about consumer attitudes toward AI customer service agents?
A May report covering consumers from the US, UK, and Canada found that 59 percent are frustrated with AI customer service agents, and 85 percent said they would prefer to speak directly with a human representative when seeking support.
What risks do experts warn about from extensive reliance on AI chatbots in customer service?
Experts including Ryan Hamilton of Emory University and Ravi Dhar of Yale warn that over-reliance on immature AI chatbots can damage company reputations, erode service quality, and trap organizations in suboptimal systems due to sunk-cost pressure from large AI investments. Hamilton also cautions that widespread AI call center adoption could eliminate service quality as a competitive differentiator across industries.
Article produced with the assistance of artificial intelligence and reviewed by the editorial team.
